diff --git a/docs/_posts/ahmedlone127/2024-09-01-012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_en.md b/docs/_posts/ahmedlone127/2024-09-01-012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_en.md new file mode 100644 index 00000000000000..60cb68055051c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English 012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000 DeBertaForSequenceClassification from diogopaes10 +author: John Snow Labs +name: 012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000` is a English model originally trained by diogopaes10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_en_5.5.0_3.0_1725210154954.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_en_5.5.0_3.0_1725210154954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|615.4 MB| + +## References + +https://huggingface.co/diogopaes10/012-microsoft-deberta-v3-base-finetuned-yahoo-8000_2000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_pipeline_en.md new file mode 100644 index 00000000000000..b543ea537ded87 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English 012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_pipeline pipeline DeBertaForSequenceClassification from diogopaes10 +author: John Snow Labs +name: 012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_pipeline` is a English model originally trained by diogopaes10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_pipeline_en_5.5.0_3.0_1725210205867.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_pipeline_en_5.5.0_3.0_1725210205867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|012_microsoft_deberta_v3_base_finetuned_yahoo_8000_2000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|615.4 MB| + +## References + +https://huggingface.co/diogopaes10/012-microsoft-deberta-v3-base-finetuned-yahoo-8000_2000 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-abert_test_en.md b/docs/_posts/ahmedlone127/2024-09-01-abert_test_en.md new file mode 100644 index 00000000000000..0cff044d60d5d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-abert_test_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English abert_test AlbertEmbeddings from hizella +author: John Snow Labs +name: abert_test +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, albert] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`abert_test` is a English model originally trained by hizella. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/abert_test_en_5.4.2_3.0_1725205737924.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/abert_test_en_5.4.2_3.0_1725205737924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = AlbertEmbeddings.pretrained("abert_test","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = AlbertEmbeddings.pretrained("abert_test","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|abert_test| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[albert]| +|Language:|en| +|Size:|41.6 MB| + +## References + +https://huggingface.co/hizella/aBERT_test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-abert_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-abert_test_pipeline_en.md new file mode 100644 index 00000000000000..b82161d6dd6e6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-abert_test_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English abert_test_pipeline pipeline AlbertEmbeddings from hizella +author: John Snow Labs +name: abert_test_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`abert_test_pipeline` is a English model originally trained by hizella. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/abert_test_pipeline_en_5.4.2_3.0_1725205740253.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/abert_test_pipeline_en_5.4.2_3.0_1725205740253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("abert_test_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("abert_test_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|abert_test_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|41.6 MB| + +## References + +https://huggingface.co/hizella/aBERT_test + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-action_classifier_v0_en.md b/docs/_posts/ahmedlone127/2024-09-01-action_classifier_v0_en.md new file mode 100644 index 00000000000000..59564d8cb75695 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-action_classifier_v0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English action_classifier_v0 MPNetEmbeddings from futuredatascience +author: John Snow Labs +name: action_classifier_v0 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`action_classifier_v0` is a English model originally trained by futuredatascience. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/action_classifier_v0_en_5.5.0_3.0_1725224727285.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/action_classifier_v0_en_5.5.0_3.0_1725224727285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("action_classifier_v0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("action_classifier_v0","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|action_classifier_v0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/futuredatascience/action-classifier-v0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-action_classifier_v0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-action_classifier_v0_pipeline_en.md new file mode 100644 index 00000000000000..e9cb6b5784e68d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-action_classifier_v0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English action_classifier_v0_pipeline pipeline MPNetEmbeddings from futuredatascience +author: John Snow Labs +name: action_classifier_v0_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`action_classifier_v0_pipeline` is a English model originally trained by futuredatascience. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/action_classifier_v0_pipeline_en_5.5.0_3.0_1725224749119.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/action_classifier_v0_pipeline_en_5.5.0_3.0_1725224749119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("action_classifier_v0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("action_classifier_v0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|action_classifier_v0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/futuredatascience/action-classifier-v0 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-address_ner_en.md b/docs/_posts/ahmedlone127/2024-09-01-address_ner_en.md new file mode 100644 index 00000000000000..5484421f7a4647 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-address_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English address_ner DistilBertForTokenClassification from walter133 +author: John Snow Labs +name: address_ner +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`address_ner` is a English model originally trained by walter133. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/address_ner_en_5.4.2_3.0_1725172307773.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/address_ner_en_5.4.2_3.0_1725172307773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("address_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("address_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|address_ner| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/walter133/address-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-address_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-address_ner_pipeline_en.md new file mode 100644 index 00000000000000..49edeafade5993 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-address_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English address_ner_pipeline pipeline DistilBertForTokenClassification from walter133 +author: John Snow Labs +name: address_ner_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`address_ner_pipeline` is a English model originally trained by walter133. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/address_ner_pipeline_en_5.4.2_3.0_1725172321158.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/address_ner_pipeline_en_5.4.2_3.0_1725172321158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("address_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("address_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|address_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/walter133/address-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-aec_ner_distilbert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-aec_ner_distilbert_base_pipeline_en.md new file mode 100644 index 00000000000000..237d57f4112eb6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-aec_ner_distilbert_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English aec_ner_distilbert_base_pipeline pipeline DistilBertForTokenClassification from mehrzad-shahin +author: John Snow Labs +name: aec_ner_distilbert_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aec_ner_distilbert_base_pipeline` is a English model originally trained by mehrzad-shahin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aec_ner_distilbert_base_pipeline_en_5.4.2_3.0_1725172581976.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aec_ner_distilbert_base_pipeline_en_5.4.2_3.0_1725172581976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("aec_ner_distilbert_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("aec_ner_distilbert_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|aec_ner_distilbert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/mehrzad-shahin/aec-ner-distilbert-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-aigc_detector_env2_en.md b/docs/_posts/ahmedlone127/2024-09-01-aigc_detector_env2_en.md new file mode 100644 index 00000000000000..4fd95f45dd0b64 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-aigc_detector_env2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English aigc_detector_env2 RoBertaForSequenceClassification from yuchuantian +author: John Snow Labs +name: aigc_detector_env2 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aigc_detector_env2` is a English model originally trained by yuchuantian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aigc_detector_env2_en_5.4.2_3.0_1725194005423.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aigc_detector_env2_en_5.4.2_3.0_1725194005423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("aigc_detector_env2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("aigc_detector_env2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|aigc_detector_env2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|462.3 MB| + +## References + +https://huggingface.co/yuchuantian/AIGC_detector_env2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-aigc_detector_env2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-aigc_detector_env2_pipeline_en.md new file mode 100644 index 00000000000000..6a7a48697fa00e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-aigc_detector_env2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English aigc_detector_env2_pipeline pipeline RoBertaForSequenceClassification from yuchuantian +author: John Snow Labs +name: aigc_detector_env2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aigc_detector_env2_pipeline` is a English model originally trained by yuchuantian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aigc_detector_env2_pipeline_en_5.4.2_3.0_1725194037886.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aigc_detector_env2_pipeline_en_5.4.2_3.0_1725194037886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("aigc_detector_env2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("aigc_detector_env2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|aigc_detector_env2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|462.4 MB| + +## References + +https://huggingface.co/yuchuantian/AIGC_detector_env2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-airbnb_reviews_helpfulness_classifier_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-airbnb_reviews_helpfulness_classifier_roberta_base_en.md new file mode 100644 index 00000000000000..5213724933f901 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-airbnb_reviews_helpfulness_classifier_roberta_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English airbnb_reviews_helpfulness_classifier_roberta_base RoBertaForSequenceClassification from lihuicham +author: John Snow Labs +name: airbnb_reviews_helpfulness_classifier_roberta_base +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`airbnb_reviews_helpfulness_classifier_roberta_base` is a English model originally trained by lihuicham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/airbnb_reviews_helpfulness_classifier_roberta_base_en_5.4.2_3.0_1725194700306.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/airbnb_reviews_helpfulness_classifier_roberta_base_en_5.4.2_3.0_1725194700306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("airbnb_reviews_helpfulness_classifier_roberta_base","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("airbnb_reviews_helpfulness_classifier_roberta_base", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|airbnb_reviews_helpfulness_classifier_roberta_base| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|427.9 MB| + +## References + +https://huggingface.co/lihuicham/airbnb-reviews-helpfulness-classifier-roberta-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-airbnb_reviews_helpfulness_classifier_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-airbnb_reviews_helpfulness_classifier_roberta_base_pipeline_en.md new file mode 100644 index 00000000000000..330955eac35acc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-airbnb_reviews_helpfulness_classifier_roberta_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English airbnb_reviews_helpfulness_classifier_roberta_base_pipeline pipeline RoBertaForSequenceClassification from lihuicham +author: John Snow Labs +name: airbnb_reviews_helpfulness_classifier_roberta_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`airbnb_reviews_helpfulness_classifier_roberta_base_pipeline` is a English model originally trained by lihuicham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/airbnb_reviews_helpfulness_classifier_roberta_base_pipeline_en_5.4.2_3.0_1725194740534.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/airbnb_reviews_helpfulness_classifier_roberta_base_pipeline_en_5.4.2_3.0_1725194740534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("airbnb_reviews_helpfulness_classifier_roberta_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("airbnb_reviews_helpfulness_classifier_roberta_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|airbnb_reviews_helpfulness_classifier_roberta_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|427.9 MB| + +## References + +https://huggingface.co/lihuicham/airbnb-reviews-helpfulness-classifier-roberta-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_en.md b/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_en.md new file mode 100644 index 00000000000000..7f858ebbf6fc39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_base_qa_2 AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_2 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_en_5.4.2_3.0_1725193194931.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_en_5.4.2_3.0_1725193194931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_k_fold_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_k_fold_1_pipeline_en.md new file mode 100644 index 00000000000000..5416f34003ddfa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_k_fold_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_2_k_fold_1_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_2_k_fold_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2_k_fold_1_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_1_pipeline_en_5.4.2_3.0_1725193501384.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_1_pipeline_en_5.4.2_3.0_1725193501384.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_2_k_fold_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_2_k_fold_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_2_k_fold_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-2-k-fold-1 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_pipeline_en.md new file mode 100644 index 00000000000000..3f3b5fcd6fd34e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_2_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_pipeline_en_5.4.2_3.0_1725193197186.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_pipeline_en_5.4.2_3.0_1725193197186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-2 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_3_pipeline_en.md new file mode 100644 index 00000000000000..ff5a7dbd8b6fb2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_3_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_3_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_3_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_3_pipeline_en_5.4.2_3.0_1725193138142.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_3_pipeline_en_5.4.2_3.0_1725193138142.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-3 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_base_v2_cased_ner_en.md b/docs/_posts/ahmedlone127/2024-09-01-albert_base_v2_cased_ner_en.md new file mode 100644 index 00000000000000..c134e96eeed43e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albert_base_v2_cased_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English albert_base_v2_cased_ner AlbertForTokenClassification from TunahanGokcimen +author: John Snow Labs +name: albert_base_v2_cased_ner +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, albert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_cased_ner` is a English model originally trained by TunahanGokcimen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_cased_ner_en_5.4.2_3.0_1725203582357.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_cased_ner_en_5.4.2_3.0_1725203582357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = AlbertForTokenClassification.pretrained("albert_base_v2_cased_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = AlbertForTokenClassification.pretrained("albert_base_v2_cased_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_v2_cased_ner| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/TunahanGokcimen/albert-base-v2-cased-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_base_v2_cased_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-albert_base_v2_cased_ner_pipeline_en.md new file mode 100644 index 00000000000000..0c36a4ad43ccf4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albert_base_v2_cased_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English albert_base_v2_cased_ner_pipeline pipeline AlbertForTokenClassification from TunahanGokcimen +author: John Snow Labs +name: albert_base_v2_cased_ner_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_cased_ner_pipeline` is a English model originally trained by TunahanGokcimen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_cased_ner_pipeline_en_5.4.2_3.0_1725203584701.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_cased_ner_pipeline_en_5.4.2_3.0_1725203584701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_v2_cased_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_v2_cased_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_v2_cased_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.1 MB| + +## References + +https://huggingface.co/TunahanGokcimen/albert-base-v2-cased-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_mongolian_mn.md b/docs/_posts/ahmedlone127/2024-09-01-albert_mongolian_mn.md new file mode 100644 index 00000000000000..d6179f014ea472 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albert_mongolian_mn.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Mongolian albert_mongolian AlbertEmbeddings from bayartsogt +author: John Snow Labs +name: albert_mongolian +date: 2024-09-01 +tags: [mn, open_source, onnx, embeddings, albert] +task: Embeddings +language: mn +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_mongolian` is a Mongolian model originally trained by bayartsogt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_mongolian_mn_5.4.2_3.0_1725205676289.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_mongolian_mn_5.4.2_3.0_1725205676289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = AlbertEmbeddings.pretrained("albert_mongolian","mn") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = AlbertEmbeddings.pretrained("albert_mongolian","mn") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_mongolian| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[albert]| +|Language:|mn| +|Size:|42.1 MB| + +## References + +https://huggingface.co/bayartsogt/albert-mongolian \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_mongolian_pipeline_mn.md b/docs/_posts/ahmedlone127/2024-09-01-albert_mongolian_pipeline_mn.md new file mode 100644 index 00000000000000..2ca94c388faaea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albert_mongolian_pipeline_mn.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Mongolian albert_mongolian_pipeline pipeline AlbertEmbeddings from bayartsogt +author: John Snow Labs +name: albert_mongolian_pipeline +date: 2024-09-01 +tags: [mn, open_source, pipeline, onnx] +task: Embeddings +language: mn +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_mongolian_pipeline` is a Mongolian model originally trained by bayartsogt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_mongolian_pipeline_mn_5.4.2_3.0_1725205678725.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_mongolian_pipeline_mn_5.4.2_3.0_1725205678725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_mongolian_pipeline", lang = "mn") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_mongolian_pipeline", lang = "mn") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_mongolian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|mn| +|Size:|42.1 MB| + +## References + +https://huggingface.co/bayartsogt/albert-mongolian + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_offensive_lm_tapt_en.md b/docs/_posts/ahmedlone127/2024-09-01-albert_offensive_lm_tapt_en.md new file mode 100644 index 00000000000000..ea41bdc31fb055 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albert_offensive_lm_tapt_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English albert_offensive_lm_tapt AlbertEmbeddings from k4black +author: John Snow Labs +name: albert_offensive_lm_tapt +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, albert] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_offensive_lm_tapt` is a English model originally trained by k4black. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_offensive_lm_tapt_en_5.4.2_3.0_1725205803787.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_offensive_lm_tapt_en_5.4.2_3.0_1725205803787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = AlbertEmbeddings.pretrained("albert_offensive_lm_tapt","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = AlbertEmbeddings.pretrained("albert_offensive_lm_tapt","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_offensive_lm_tapt| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[albert]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/k4black/albert-offensive-lm-tapt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_offensive_lm_tapt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-albert_offensive_lm_tapt_pipeline_en.md new file mode 100644 index 00000000000000..fc52a4d7b2622b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albert_offensive_lm_tapt_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English albert_offensive_lm_tapt_pipeline pipeline AlbertEmbeddings from k4black +author: John Snow Labs +name: albert_offensive_lm_tapt_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_offensive_lm_tapt_pipeline` is a English model originally trained by k4black. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_offensive_lm_tapt_pipeline_en_5.4.2_3.0_1725205806280.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_offensive_lm_tapt_pipeline_en_5.4.2_3.0_1725205806280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_offensive_lm_tapt_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_offensive_lm_tapt_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_offensive_lm_tapt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/k4black/albert-offensive-lm-tapt + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_tiny_chinese_ner_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-01-albert_tiny_chinese_ner_pipeline_zh.md new file mode 100644 index 00000000000000..8b8367aa78be7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albert_tiny_chinese_ner_pipeline_zh.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Chinese albert_tiny_chinese_ner_pipeline pipeline BertForTokenClassification from ckiplab +author: John Snow Labs +name: albert_tiny_chinese_ner_pipeline +date: 2024-09-01 +tags: [zh, open_source, pipeline, onnx] +task: Named Entity Recognition +language: zh +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_tiny_chinese_ner_pipeline` is a Chinese model originally trained by ckiplab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_tiny_chinese_ner_pipeline_zh_5.4.2_3.0_1725163486559.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_tiny_chinese_ner_pipeline_zh_5.4.2_3.0_1725163486559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_tiny_chinese_ner_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_tiny_chinese_ner_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_tiny_chinese_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|15.2 MB| + +## References + +https://huggingface.co/ckiplab/albert-tiny-chinese-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albertbase_qa_2_en.md b/docs/_posts/ahmedlone127/2024-09-01-albertbase_qa_2_en.md new file mode 100644 index 00000000000000..70aa3b62196c9c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albertbase_qa_2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albertbase_qa_2 AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albertbase_qa_2 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albertbase_qa_2` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albertbase_qa_2_en_5.4.2_3.0_1725193140223.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albertbase_qa_2_en_5.4.2_3.0_1725193140223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albertbase_qa_2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albertbase_qa_2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albertbase_qa_2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albertbase-qa_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-albertbase_qa_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-albertbase_qa_2_pipeline_en.md new file mode 100644 index 00000000000000..e73c08fb425834 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-albertbase_qa_2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albertbase_qa_2_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albertbase_qa_2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albertbase_qa_2_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albertbase_qa_2_pipeline_en_5.4.2_3.0_1725193142597.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albertbase_qa_2_pipeline_en_5.4.2_3.0_1725193142597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albertbase_qa_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albertbase_qa_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albertbase_qa_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albertbase-qa_2 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_en.md b/docs/_posts/ahmedlone127/2024-09-01-all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_en.md new file mode 100644 index 00000000000000..2341b9b1773cfd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic MPNetEmbeddings from AhmetAytar +author: John Snow Labs +name: all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic` is a English model originally trained by AhmetAytar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_en_5.5.0_3.0_1725224593299.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_en_5.5.0_3.0_1725224593299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/AhmetAytar/all-mpnet-base-v2-fine-tuned_17_textbook_grobid_semantic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_pipeline_en.md new file mode 100644 index 00000000000000..8952fd92c123f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_pipeline pipeline MPNetEmbeddings from AhmetAytar +author: John Snow Labs +name: all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_pipeline` is a English model originally trained by AhmetAytar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_pipeline_en_5.5.0_3.0_1725224620420.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_pipeline_en_5.5.0_3.0_1725224620420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_fine_tuned_17_textbook_grobid_semantic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/AhmetAytar/all-mpnet-base-v2-fine-tuned_17_textbook_grobid_semantic + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-answer_finder_v1_s_english_en.md b/docs/_posts/ahmedlone127/2024-09-01-answer_finder_v1_s_english_en.md new file mode 100644 index 00000000000000..979db7450e5f42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-answer_finder_v1_s_english_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English answer_finder_v1_s_english BertForQuestionAnswering from sinequa +author: John Snow Labs +name: answer_finder_v1_s_english +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`answer_finder_v1_s_english` is a English model originally trained by sinequa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/answer_finder_v1_s_english_en_5.4.2_3.0_1725185315923.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/answer_finder_v1_s_english_en_5.4.2_3.0_1725185315923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("answer_finder_v1_s_english","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("answer_finder_v1_s_english", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|answer_finder_v1_s_english| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|123.8 MB| + +## References + +https://huggingface.co/sinequa/answer-finder-v1-S-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-answer_finder_v1_s_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-answer_finder_v1_s_english_pipeline_en.md new file mode 100644 index 00000000000000..d6e8384bb7da8a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-answer_finder_v1_s_english_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English answer_finder_v1_s_english_pipeline pipeline BertForQuestionAnswering from sinequa +author: John Snow Labs +name: answer_finder_v1_s_english_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`answer_finder_v1_s_english_pipeline` is a English model originally trained by sinequa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/answer_finder_v1_s_english_pipeline_en_5.4.2_3.0_1725185322397.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/answer_finder_v1_s_english_pipeline_en_5.4.2_3.0_1725185322397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("answer_finder_v1_s_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("answer_finder_v1_s_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|answer_finder_v1_s_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|123.8 MB| + +## References + +https://huggingface.co/sinequa/answer-finder-v1-S-en + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-argumentmining_english_vfp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-argumentmining_english_vfp_pipeline_en.md new file mode 100644 index 00000000000000..abd617234c3007 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-argumentmining_english_vfp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English argumentmining_english_vfp_pipeline pipeline RoBertaForSequenceClassification from raruidol +author: John Snow Labs +name: argumentmining_english_vfp_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`argumentmining_english_vfp_pipeline` is a English model originally trained by raruidol. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/argumentmining_english_vfp_pipeline_en_5.4.2_3.0_1725166956510.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/argumentmining_english_vfp_pipeline_en_5.4.2_3.0_1725166956510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("argumentmining_english_vfp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("argumentmining_english_vfp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|argumentmining_english_vfp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/raruidol/ArgumentMining-EN-VFP + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ariabert_fa.md b/docs/_posts/ahmedlone127/2024-09-01-ariabert_fa.md new file mode 100644 index 00000000000000..0ad4fcd06edbf4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ariabert_fa.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Persian ariabert RoBertaEmbeddings from ViraIntelligentDataMining +author: John Snow Labs +name: ariabert +date: 2024-09-01 +tags: [fa, open_source, onnx, embeddings, roberta] +task: Embeddings +language: fa +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ariabert` is a Persian model originally trained by ViraIntelligentDataMining. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ariabert_fa_5.4.2_3.0_1725165627342.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ariabert_fa_5.4.2_3.0_1725165627342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("ariabert","fa") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("ariabert","fa") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ariabert| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|fa| +|Size:|489.7 MB| + +## References + +https://huggingface.co/ViraIntelligentDataMining/AriaBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-article_recognizer_en.md b/docs/_posts/ahmedlone127/2024-09-01-article_recognizer_en.md new file mode 100644 index 00000000000000..16a0e8d8324250 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-article_recognizer_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English article_recognizer DistilBertForSequenceClassification from LaLaf93 +author: John Snow Labs +name: article_recognizer +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`article_recognizer` is a English model originally trained by LaLaf93. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/article_recognizer_en_5.5.0_3.0_1725214175113.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/article_recognizer_en_5.5.0_3.0_1725214175113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("article_recognizer","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("article_recognizer", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|article_recognizer| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/LaLaf93/article_recognizer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-article_recognizer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-article_recognizer_pipeline_en.md new file mode 100644 index 00000000000000..bd1834004de916 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-article_recognizer_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English article_recognizer_pipeline pipeline DistilBertForSequenceClassification from LaLaf93 +author: John Snow Labs +name: article_recognizer_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`article_recognizer_pipeline` is a English model originally trained by LaLaf93. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/article_recognizer_pipeline_en_5.5.0_3.0_1725214188541.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/article_recognizer_pipeline_en_5.5.0_3.0_1725214188541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("article_recognizer_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("article_recognizer_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|article_recognizer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/LaLaf93/article_recognizer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-atte_3_en.md b/docs/_posts/ahmedlone127/2024-09-01-atte_3_en.md new file mode 100644 index 00000000000000..39873c4bc05a40 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-atte_3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English atte_3 RoBertaForSequenceClassification from BaronSch +author: John Snow Labs +name: atte_3 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atte_3` is a English model originally trained by BaronSch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/atte_3_en_5.5.0_3.0_1725211856405.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atte_3_en_5.5.0_3.0_1725211856405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("atte_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("atte_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|atte_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.5 MB| + +## References + +https://huggingface.co/BaronSch/Atte_3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-atte_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-atte_3_pipeline_en.md new file mode 100644 index 00000000000000..09809098e1931b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-atte_3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English atte_3_pipeline pipeline RoBertaForSequenceClassification from BaronSch +author: John Snow Labs +name: atte_3_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atte_3_pipeline` is a English model originally trained by BaronSch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/atte_3_pipeline_en_5.5.0_3.0_1725211881689.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atte_3_pipeline_en_5.5.0_3.0_1725211881689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("atte_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("atte_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|atte_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.5 MB| + +## References + +https://huggingface.co/BaronSch/Atte_3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-automated_labeling_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-01-automated_labeling_distilbert_en.md new file mode 100644 index 00000000000000..5a1a527c8481e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-automated_labeling_distilbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English automated_labeling_distilbert DistilBertForSequenceClassification from brittanyhlc +author: John Snow Labs +name: automated_labeling_distilbert +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`automated_labeling_distilbert` is a English model originally trained by brittanyhlc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/automated_labeling_distilbert_en_5.5.0_3.0_1725213837854.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/automated_labeling_distilbert_en_5.5.0_3.0_1725213837854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("automated_labeling_distilbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("automated_labeling_distilbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|automated_labeling_distilbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.6 MB| + +## References + +https://huggingface.co/brittanyhlc/automated-labeling-distilbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-automated_labeling_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-automated_labeling_distilbert_pipeline_en.md new file mode 100644 index 00000000000000..92713804c19460 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-automated_labeling_distilbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English automated_labeling_distilbert_pipeline pipeline DistilBertForSequenceClassification from brittanyhlc +author: John Snow Labs +name: automated_labeling_distilbert_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`automated_labeling_distilbert_pipeline` is a English model originally trained by brittanyhlc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/automated_labeling_distilbert_pipeline_en_5.5.0_3.0_1725213852654.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/automated_labeling_distilbert_pipeline_en_5.5.0_3.0_1725213852654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("automated_labeling_distilbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("automated_labeling_distilbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|automated_labeling_distilbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.6 MB| + +## References + +https://huggingface.co/brittanyhlc/automated-labeling-distilbert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-autotrain_9jsce_l56hi_en.md b/docs/_posts/ahmedlone127/2024-09-01-autotrain_9jsce_l56hi_en.md new file mode 100644 index 00000000000000..e730ee7c44a2b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-autotrain_9jsce_l56hi_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English autotrain_9jsce_l56hi DistilBertForSequenceClassification from redblackbird +author: John Snow Labs +name: autotrain_9jsce_l56hi +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_9jsce_l56hi` is a English model originally trained by redblackbird. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_9jsce_l56hi_en_5.5.0_3.0_1725213851530.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_9jsce_l56hi_en_5.5.0_3.0_1725213851530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("autotrain_9jsce_l56hi","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("autotrain_9jsce_l56hi", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_9jsce_l56hi| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/redblackbird/autotrain-9jsce-l56hi \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-autotrain_9jsce_l56hi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-autotrain_9jsce_l56hi_pipeline_en.md new file mode 100644 index 00000000000000..555c7244f1f224 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-autotrain_9jsce_l56hi_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English autotrain_9jsce_l56hi_pipeline pipeline DistilBertForSequenceClassification from redblackbird +author: John Snow Labs +name: autotrain_9jsce_l56hi_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_9jsce_l56hi_pipeline` is a English model originally trained by redblackbird. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_9jsce_l56hi_pipeline_en_5.5.0_3.0_1725213866670.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_9jsce_l56hi_pipeline_en_5.5.0_3.0_1725213866670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_9jsce_l56hi_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_9jsce_l56hi_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_9jsce_l56hi_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/redblackbird/autotrain-9jsce-l56hi + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-autotrain_neuralg8_albert2_99588147371_en.md b/docs/_posts/ahmedlone127/2024-09-01-autotrain_neuralg8_albert2_99588147371_en.md new file mode 100644 index 00000000000000..3760a0eed29ce7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-autotrain_neuralg8_albert2_99588147371_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English autotrain_neuralg8_albert2_99588147371 AlbertForQuestionAnswering from Samis922 +author: John Snow Labs +name: autotrain_neuralg8_albert2_99588147371 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_neuralg8_albert2_99588147371` is a English model originally trained by Samis922. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_neuralg8_albert2_99588147371_en_5.4.2_3.0_1725193485536.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_neuralg8_albert2_99588147371_en_5.4.2_3.0_1725193485536.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("autotrain_neuralg8_albert2_99588147371","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("autotrain_neuralg8_albert2_99588147371", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_neuralg8_albert2_99588147371| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/Samis922/autotrain-neuralg8_albert2-99588147371 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-autotrain_neuralg8_albert2_99588147371_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-autotrain_neuralg8_albert2_99588147371_pipeline_en.md new file mode 100644 index 00000000000000..fd9c9dc95a7605 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-autotrain_neuralg8_albert2_99588147371_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English autotrain_neuralg8_albert2_99588147371_pipeline pipeline AlbertForQuestionAnswering from Samis922 +author: John Snow Labs +name: autotrain_neuralg8_albert2_99588147371_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_neuralg8_albert2_99588147371_pipeline` is a English model originally trained by Samis922. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_neuralg8_albert2_99588147371_pipeline_en_5.4.2_3.0_1725193489272.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_neuralg8_albert2_99588147371_pipeline_en_5.4.2_3.0_1725193489272.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_neuralg8_albert2_99588147371_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_neuralg8_albert2_99588147371_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_neuralg8_albert2_99588147371_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/Samis922/autotrain-neuralg8_albert2-99588147371 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-autotrain_swot_deberta_xs_3268991215_en.md b/docs/_posts/ahmedlone127/2024-09-01-autotrain_swot_deberta_xs_3268991215_en.md new file mode 100644 index 00000000000000..7661eae78293e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-autotrain_swot_deberta_xs_3268991215_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English autotrain_swot_deberta_xs_3268991215 DeBertaForQuestionAnswering from chau +author: John Snow Labs +name: autotrain_swot_deberta_xs_3268991215 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_swot_deberta_xs_3268991215` is a English model originally trained by chau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_swot_deberta_xs_3268991215_en_5.5.0_3.0_1725218954538.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_swot_deberta_xs_3268991215_en_5.5.0_3.0_1725218954538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("autotrain_swot_deberta_xs_3268991215","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("autotrain_swot_deberta_xs_3268991215", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_swot_deberta_xs_3268991215| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|250.8 MB| + +## References + +https://huggingface.co/chau/autotrain-swot-deberta-xs-3268991215 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-autotrain_swot_deberta_xs_3268991215_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-autotrain_swot_deberta_xs_3268991215_pipeline_en.md new file mode 100644 index 00000000000000..40a61b49f48cf2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-autotrain_swot_deberta_xs_3268991215_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English autotrain_swot_deberta_xs_3268991215_pipeline pipeline DeBertaForQuestionAnswering from chau +author: John Snow Labs +name: autotrain_swot_deberta_xs_3268991215_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_swot_deberta_xs_3268991215_pipeline` is a English model originally trained by chau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_swot_deberta_xs_3268991215_pipeline_en_5.5.0_3.0_1725218969369.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_swot_deberta_xs_3268991215_pipeline_en_5.5.0_3.0_1725218969369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_swot_deberta_xs_3268991215_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_swot_deberta_xs_3268991215_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_swot_deberta_xs_3268991215_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|250.8 MB| + +## References + +https://huggingface.co/chau/autotrain-swot-deberta-xs-3268991215 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bangla_roberta_question_and_answer_en.md b/docs/_posts/ahmedlone127/2024-09-01-bangla_roberta_question_and_answer_en.md new file mode 100644 index 00000000000000..025f12952c81b9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bangla_roberta_question_and_answer_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bangla_roberta_question_and_answer RoBertaForQuestionAnswering from saiful9379 +author: John Snow Labs +name: bangla_roberta_question_and_answer +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bangla_roberta_question_and_answer` is a English model originally trained by saiful9379. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bangla_roberta_question_and_answer_en_5.4.2_3.0_1725201056353.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bangla_roberta_question_and_answer_en_5.4.2_3.0_1725201056353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("bangla_roberta_question_and_answer","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("bangla_roberta_question_and_answer", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bangla_roberta_question_and_answer| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|246.9 MB| + +## References + +https://huggingface.co/saiful9379/Bangla_Roberta_Question_and_Answer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bangla_roberta_question_and_answer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bangla_roberta_question_and_answer_pipeline_en.md new file mode 100644 index 00000000000000..ff925a0b81bd56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bangla_roberta_question_and_answer_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bangla_roberta_question_and_answer_pipeline pipeline RoBertaForQuestionAnswering from saiful9379 +author: John Snow Labs +name: bangla_roberta_question_and_answer_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bangla_roberta_question_and_answer_pipeline` is a English model originally trained by saiful9379. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bangla_roberta_question_and_answer_pipeline_en_5.4.2_3.0_1725201070371.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bangla_roberta_question_and_answer_pipeline_en_5.4.2_3.0_1725201070371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bangla_roberta_question_and_answer_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bangla_roberta_question_and_answer_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bangla_roberta_question_and_answer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.0 MB| + +## References + +https://huggingface.co/saiful9379/Bangla_Roberta_Question_and_Answer + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bantuberta_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-01-bantuberta_pipeline_xx.md new file mode 100644 index 00000000000000..79b05586f273cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bantuberta_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bantuberta_pipeline pipeline RoBertaEmbeddings from dsfsi +author: John Snow Labs +name: bantuberta_pipeline +date: 2024-09-01 +tags: [xx, open_source, pipeline, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bantuberta_pipeline` is a Multilingual model originally trained by dsfsi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bantuberta_pipeline_xx_5.4.2_3.0_1725191260459.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bantuberta_pipeline_xx_5.4.2_3.0_1725191260459.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bantuberta_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bantuberta_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bantuberta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|416.1 MB| + +## References + +https://huggingface.co/dsfsi/BantuBERTa + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_multilingual_cased_allnli_turkish_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_multilingual_cased_allnli_turkish_pipeline_xx.md new file mode 100644 index 00000000000000..e48dab7c94c7e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_multilingual_cased_allnli_turkish_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_allnli_turkish_pipeline pipeline BertForZeroShotClassification from emrecan +author: John Snow Labs +name: bert_base_multilingual_cased_allnli_turkish_pipeline +date: 2024-09-01 +tags: [xx, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_allnli_turkish_pipeline` is a Multilingual model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_allnli_turkish_pipeline_xx_5.4.2_3.0_1725202675638.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_allnli_turkish_pipeline_xx_5.4.2_3.0_1725202675638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_allnli_turkish_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_allnli_turkish_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_allnli_turkish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|665.1 MB| + +## References + +https://huggingface.co/emrecan/bert-base-multilingual-cased-allnli_tr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_multilingual_cased_allnli_turkish_xx.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_multilingual_cased_allnli_turkish_xx.md new file mode 100644 index 00000000000000..bd83eaffbe0939 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_multilingual_cased_allnli_turkish_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_allnli_turkish BertForZeroShotClassification from emrecan +author: John Snow Labs +name: bert_base_multilingual_cased_allnli_turkish +date: 2024-09-01 +tags: [xx, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_allnli_turkish` is a Multilingual model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_allnli_turkish_xx_5.4.2_3.0_1725202638412.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_allnli_turkish_xx_5.4.2_3.0_1725202638412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("bert_base_multilingual_cased_allnli_turkish","xx") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("bert_base_multilingual_cased_allnli_turkish", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_allnli_turkish| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|665.1 MB| + +## References + +https://huggingface.co/emrecan/bert-base-multilingual-cased-allnli_tr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_multilingual_cased_multinli_turkish_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_multilingual_cased_multinli_turkish_pipeline_xx.md new file mode 100644 index 00000000000000..5f33937592c8ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_multilingual_cased_multinli_turkish_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_multinli_turkish_pipeline pipeline BertForZeroShotClassification from emrecan +author: John Snow Labs +name: bert_base_multilingual_cased_multinli_turkish_pipeline +date: 2024-09-01 +tags: [xx, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_multinli_turkish_pipeline` is a Multilingual model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_multinli_turkish_pipeline_xx_5.4.2_3.0_1725208091000.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_multinli_turkish_pipeline_xx_5.4.2_3.0_1725208091000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_multinli_turkish_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_multinli_turkish_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_multinli_turkish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|665.1 MB| + +## References + +https://huggingface.co/emrecan/bert-base-multilingual-cased-multinli_tr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_multilingual_cased_multinli_turkish_xx.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_multilingual_cased_multinli_turkish_xx.md new file mode 100644 index 00000000000000..d22e75516feb48 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_multilingual_cased_multinli_turkish_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_multinli_turkish BertForZeroShotClassification from emrecan +author: John Snow Labs +name: bert_base_multilingual_cased_multinli_turkish +date: 2024-09-01 +tags: [xx, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_multinli_turkish` is a Multilingual model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_multinli_turkish_xx_5.4.2_3.0_1725208055541.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_multinli_turkish_xx_5.4.2_3.0_1725208055541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("bert_base_multilingual_cased_multinli_turkish","xx") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("bert_base_multilingual_cased_multinli_turkish", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_multinli_turkish| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|665.1 MB| + +## References + +https://huggingface.co/emrecan/bert-base-multilingual-cased-multinli_tr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_spanish_wwm_cased_xnli_es.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_spanish_wwm_cased_xnli_es.md new file mode 100644 index 00000000000000..3024d6a926b00b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_spanish_wwm_cased_xnli_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish bert_base_spanish_wwm_cased_xnli BertForZeroShotClassification from Recognai +author: John Snow Labs +name: bert_base_spanish_wwm_cased_xnli +date: 2024-09-01 +tags: [es, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_xnli` is a Castilian, Spanish model originally trained by Recognai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_xnli_es_5.4.2_3.0_1725202525009.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_xnli_es_5.4.2_3.0_1725202525009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("bert_base_spanish_wwm_cased_xnli","es") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("bert_base_spanish_wwm_cased_xnli", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_cased_xnli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Recognai/bert-base-spanish-wwm-cased-xnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_spanish_wwm_cased_xnli_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_spanish_wwm_cased_xnli_pipeline_es.md new file mode 100644 index 00000000000000..dc9c9c99622eeb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_spanish_wwm_cased_xnli_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish bert_base_spanish_wwm_cased_xnli_pipeline pipeline BertForZeroShotClassification from Recognai +author: John Snow Labs +name: bert_base_spanish_wwm_cased_xnli_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_xnli_pipeline` is a Castilian, Spanish model originally trained by Recognai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_xnli_pipeline_es_5.4.2_3.0_1725202552484.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_xnli_pipeline_es_5.4.2_3.0_1725202552484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_spanish_wwm_cased_xnli_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_spanish_wwm_cased_xnli_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_cased_xnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|409.5 MB| + +## References + +https://huggingface.co/Recognai/bert-base-spanish-wwm-cased-xnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_128k_cased_qa_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_128k_cased_qa_pipeline_tr.md new file mode 100644 index 00000000000000..ed57ee544c6691 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_128k_cased_qa_pipeline_tr.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Turkish bert_base_turkish_128k_cased_qa_pipeline pipeline BertForQuestionAnswering from incidelen +author: John Snow Labs +name: bert_base_turkish_128k_cased_qa_pipeline +date: 2024-09-01 +tags: [tr, open_source, pipeline, onnx] +task: Question Answering +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_128k_cased_qa_pipeline` is a Turkish model originally trained by incidelen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_128k_cased_qa_pipeline_tr_5.5.0_3.0_1725215429283.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_128k_cased_qa_pipeline_tr_5.5.0_3.0_1725215429283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_turkish_128k_cased_qa_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_turkish_128k_cased_qa_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_turkish_128k_cased_qa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|689.0 MB| + +## References + +https://huggingface.co/incidelen/bert-base-turkish-128k-cased-qa + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_128k_cased_qa_tr.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_128k_cased_qa_tr.md new file mode 100644 index 00000000000000..aa997317f923ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_128k_cased_qa_tr.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Turkish bert_base_turkish_128k_cased_qa BertForQuestionAnswering from incidelen +author: John Snow Labs +name: bert_base_turkish_128k_cased_qa +date: 2024-09-01 +tags: [tr, open_source, onnx, question_answering, bert] +task: Question Answering +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_128k_cased_qa` is a Turkish model originally trained by incidelen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_128k_cased_qa_tr_5.5.0_3.0_1725215389437.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_128k_cased_qa_tr_5.5.0_3.0_1725215389437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_base_turkish_128k_cased_qa","tr") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_turkish_128k_cased_qa", "tr") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_turkish_128k_cased_qa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|tr| +|Size:|689.0 MB| + +## References + +https://huggingface.co/incidelen/bert-base-turkish-128k-cased-qa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_allnli_turkish_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_allnli_turkish_pipeline_tr.md new file mode 100644 index 00000000000000..48a82e0b51cb61 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_allnli_turkish_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish bert_base_turkish_cased_allnli_turkish_pipeline pipeline BertForZeroShotClassification from emrecan +author: John Snow Labs +name: bert_base_turkish_cased_allnli_turkish_pipeline +date: 2024-09-01 +tags: [tr, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_cased_allnli_turkish_pipeline` is a Turkish model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_allnli_turkish_pipeline_tr_5.4.2_3.0_1725201803529.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_allnli_turkish_pipeline_tr_5.4.2_3.0_1725201803529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_turkish_cased_allnli_turkish_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_turkish_cased_allnli_turkish_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_turkish_cased_allnli_turkish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|412.3 MB| + +## References + +https://huggingface.co/emrecan/bert-base-turkish-cased-allnli_tr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_allnli_turkish_tr.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_allnli_turkish_tr.md new file mode 100644 index 00000000000000..1e1f494f1884d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_allnli_turkish_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish bert_base_turkish_cased_allnli_turkish BertForZeroShotClassification from emrecan +author: John Snow Labs +name: bert_base_turkish_cased_allnli_turkish +date: 2024-09-01 +tags: [tr, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_cased_allnli_turkish` is a Turkish model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_allnli_turkish_tr_5.4.2_3.0_1725201780553.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_allnli_turkish_tr_5.4.2_3.0_1725201780553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("bert_base_turkish_cased_allnli_turkish","tr") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("bert_base_turkish_cased_allnli_turkish", "tr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_turkish_cased_allnli_turkish| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|412.3 MB| + +## References + +https://huggingface.co/emrecan/bert-base-turkish-cased-allnli_tr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_multinli_turkish_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_multinli_turkish_pipeline_tr.md new file mode 100644 index 00000000000000..13b543880bb601 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_multinli_turkish_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish bert_base_turkish_cased_multinli_turkish_pipeline pipeline BertForZeroShotClassification from emrecan +author: John Snow Labs +name: bert_base_turkish_cased_multinli_turkish_pipeline +date: 2024-09-01 +tags: [tr, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_cased_multinli_turkish_pipeline` is a Turkish model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_multinli_turkish_pipeline_tr_5.4.2_3.0_1725208114365.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_multinli_turkish_pipeline_tr_5.4.2_3.0_1725208114365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_turkish_cased_multinli_turkish_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_turkish_cased_multinli_turkish_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_turkish_cased_multinli_turkish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|412.3 MB| + +## References + +https://huggingface.co/emrecan/bert-base-turkish-cased-multinli_tr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_multinli_turkish_tr.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_multinli_turkish_tr.md new file mode 100644 index 00000000000000..6b13802ed69629 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_multinli_turkish_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish bert_base_turkish_cased_multinli_turkish BertForZeroShotClassification from emrecan +author: John Snow Labs +name: bert_base_turkish_cased_multinli_turkish +date: 2024-09-01 +tags: [tr, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_cased_multinli_turkish` is a Turkish model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_multinli_turkish_tr_5.4.2_3.0_1725208087823.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_multinli_turkish_tr_5.4.2_3.0_1725208087823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("bert_base_turkish_cased_multinli_turkish","tr") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("bert_base_turkish_cased_multinli_turkish", "tr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_turkish_cased_multinli_turkish| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|412.3 MB| + +## References + +https://huggingface.co/emrecan/bert-base-turkish-cased-multinli_tr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_snli_turkish_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_snli_turkish_pipeline_tr.md new file mode 100644 index 00000000000000..16159bcc3f9567 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_snli_turkish_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish bert_base_turkish_cased_snli_turkish_pipeline pipeline BertForZeroShotClassification from emrecan +author: John Snow Labs +name: bert_base_turkish_cased_snli_turkish_pipeline +date: 2024-09-01 +tags: [tr, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_cased_snli_turkish_pipeline` is a Turkish model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_snli_turkish_pipeline_tr_5.4.2_3.0_1725202729484.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_snli_turkish_pipeline_tr_5.4.2_3.0_1725202729484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_turkish_cased_snli_turkish_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_turkish_cased_snli_turkish_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_turkish_cased_snli_turkish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|412.3 MB| + +## References + +https://huggingface.co/emrecan/bert-base-turkish-cased-snli_tr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_snli_turkish_tr.md b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_snli_turkish_tr.md new file mode 100644 index 00000000000000..7a8021497586db --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_base_turkish_cased_snli_turkish_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish bert_base_turkish_cased_snli_turkish BertForZeroShotClassification from emrecan +author: John Snow Labs +name: bert_base_turkish_cased_snli_turkish +date: 2024-09-01 +tags: [tr, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_cased_snli_turkish` is a Turkish model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_snli_turkish_tr_5.4.2_3.0_1725202706853.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_snli_turkish_tr_5.4.2_3.0_1725202706853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("bert_base_turkish_cased_snli_turkish","tr") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("bert_base_turkish_cased_snli_turkish", "tr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_turkish_cased_snli_turkish| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|412.3 MB| + +## References + +https://huggingface.co/emrecan/bert-base-turkish-cased-snli_tr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_cas_model_beta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_cas_model_beta_pipeline_en.md new file mode 100644 index 00000000000000..cd15d640235448 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_cas_model_beta_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_cas_model_beta_pipeline pipeline DistilBertForTokenClassification from vilsonrodrigues +author: John Snow Labs +name: bert_cas_model_beta_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cas_model_beta_pipeline` is a English model originally trained by vilsonrodrigues. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cas_model_beta_pipeline_en_5.4.2_3.0_1725171177551.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cas_model_beta_pipeline_en_5.4.2_3.0_1725171177551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_cas_model_beta_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_cas_model_beta_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cas_model_beta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/vilsonrodrigues/bert_cas_model_beta + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_arabic_marbert_news_article_classification_ar.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_arabic_marbert_news_article_classification_ar.md new file mode 100644 index 00000000000000..4698463f8d48f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_arabic_marbert_news_article_classification_ar.md @@ -0,0 +1,105 @@ +--- +layout: model +title: Arabic BertForSequenceClassification Cased model (from Ammar-alhaj-ali) +author: John Snow Labs +name: bert_classifier_arabic_marbert_news_article_classification +date: 2024-09-01 +tags: [ar, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `arabic-MARBERT-news-article-classification` is a Arabic model originally trained by `Ammar-alhaj-ali`. + +## Predicted Entities + +`Sports`, `Culture`, `Medical`, `Religion`, `Tech`, `Politics`, `Finance` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_arabic_marbert_news_article_classification_ar_5.4.2_3.0_1725204894973.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_arabic_marbert_news_article_classification_ar_5.4.2_3.0_1725204894973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_arabic_marbert_news_article_classification","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_arabic_marbert_news_article_classification","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("ar.classify.bert.news.").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_arabic_marbert_news_article_classification| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|610.9 MB| + +## References + +References + +- https://huggingface.co/Ammar-alhaj-ali/arabic-MARBERT-news-article-classification +- https://data.mendeley.com/datasets/57zpx667y9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_arabic_marbert_news_article_classification_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_arabic_marbert_news_article_classification_pipeline_ar.md new file mode 100644 index 00000000000000..4a3a563d434933 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_arabic_marbert_news_article_classification_pipeline_ar.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Arabic bert_classifier_arabic_marbert_news_article_classification_pipeline pipeline BertForSequenceClassification from Ammar-alhaj-ali +author: John Snow Labs +name: bert_classifier_arabic_marbert_news_article_classification_pipeline +date: 2024-09-01 +tags: [ar, open_source, pipeline, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_arabic_marbert_news_article_classification_pipeline` is a Arabic model originally trained by Ammar-alhaj-ali. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_arabic_marbert_news_article_classification_pipeline_ar_5.4.2_3.0_1725204928842.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_arabic_marbert_news_article_classification_pipeline_ar_5.4.2_3.0_1725204928842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_arabic_marbert_news_article_classification_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_arabic_marbert_news_article_classification_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_arabic_marbert_news_article_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|610.9 MB| + +## References + +https://huggingface.co/Ammar-alhaj-ali/arabic-MARBERT-news-article-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_entity_selection_5771228_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_entity_selection_5771228_pipeline_en.md new file mode 100644 index 00000000000000..0487b4ffebbaaf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_entity_selection_5771228_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classifier_autonlp_entity_selection_5771228_pipeline pipeline BertForSequenceClassification from kamivao +author: John Snow Labs +name: bert_classifier_autonlp_entity_selection_5771228_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_autonlp_entity_selection_5771228_pipeline` is a English model originally trained by kamivao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_entity_selection_5771228_pipeline_en_5.4.2_3.0_1725204835871.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_entity_selection_5771228_pipeline_en_5.4.2_3.0_1725204835871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_autonlp_entity_selection_5771228_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_autonlp_entity_selection_5771228_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_autonlp_entity_selection_5771228_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/kamivao/autonlp-entity_selection-5771228 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_old_data_trained_10022181_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_old_data_trained_10022181_en.md new file mode 100644 index 00000000000000..84b88736a9a2d5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_old_data_trained_10022181_en.md @@ -0,0 +1,104 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from bshlgrs) +author: John Snow Labs +name: bert_classifier_autonlp_old_data_trained_10022181 +date: 2024-09-01 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-old-data-trained-10022181` is a English model originally trained by `bshlgrs`. + +## Predicted Entities + +`No`, `Yes`, `Unsure` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_old_data_trained_10022181_en_5.4.2_3.0_1725204758298.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_old_data_trained_10022181_en_5.4.2_3.0_1725204758298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_autonlp_old_data_trained_10022181","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_autonlp_old_data_trained_10022181","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.v3.by_bshlgrs").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_autonlp_old_data_trained_10022181| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +References + +- https://huggingface.co/bshlgrs/autonlp-old-data-trained-10022181 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_old_data_trained_10022181_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_old_data_trained_10022181_pipeline_en.md new file mode 100644 index 00000000000000..e30ba2a38282b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_old_data_trained_10022181_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classifier_autonlp_old_data_trained_10022181_pipeline pipeline BertForSequenceClassification from bshlgrs +author: John Snow Labs +name: bert_classifier_autonlp_old_data_trained_10022181_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_autonlp_old_data_trained_10022181_pipeline` is a English model originally trained by bshlgrs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_old_data_trained_10022181_pipeline_en_5.4.2_3.0_1725204780787.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_old_data_trained_10022181_pipeline_en_5.4.2_3.0_1725204780787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_autonlp_old_data_trained_10022181_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_autonlp_old_data_trained_10022181_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_autonlp_old_data_trained_10022181_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/bshlgrs/autonlp-old-data-trained-10022181 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_bacnet_klassifizierung_raumlufttechnik_de.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_bacnet_klassifizierung_raumlufttechnik_de.md new file mode 100644 index 00000000000000..631b13e125fe9c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_bacnet_klassifizierung_raumlufttechnik_de.md @@ -0,0 +1,104 @@ +--- +layout: model +title: German BertForSequenceClassification Cased model (from cm-mueller) +author: John Snow Labs +name: bert_classifier_bacnet_klassifizierung_raumlufttechnik +date: 2024-09-01 +tags: [de, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `BACnet-Klassifizierung-Raumlufttechnik` is a German model originally trained by `cm-mueller`. + +## Predicted Entities + +`Wärmerückgewinnung`, `Zuluftuftfilter`, `Ventilator`, `Abluft`, `Vorerhitzer`, `Andere`, `Raum`, `Kühler`, `Erhitzer`, `Befeuchter`, `Zuluftventilator`, `Nacherhitzer`, `Aussenluftklappe`, `Brandschutz`, `Zuluft`, `Abluftventilator`, `RLT_Anlage`, `Brandschutzklappe`, `Abluftfilter` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_bacnet_klassifizierung_raumlufttechnik_de_5.4.2_3.0_1725204520455.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_bacnet_klassifizierung_raumlufttechnik_de_5.4.2_3.0_1725204520455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bacnet_klassifizierung_raumlufttechnik","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bacnet_klassifizierung_raumlufttechnik","de") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.classify.raumlufttechnik.bert.by_cm_mueller").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_bacnet_klassifizierung_raumlufttechnik| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|409.2 MB| + +## References + +References + +- https://huggingface.co/cm-mueller/BACnet-Klassifizierung-Raumlufttechnik \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_bacnet_klassifizierung_raumlufttechnik_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_bacnet_klassifizierung_raumlufttechnik_pipeline_de.md new file mode 100644 index 00000000000000..c886b6a1c41fea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_bacnet_klassifizierung_raumlufttechnik_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German bert_classifier_bacnet_klassifizierung_raumlufttechnik_pipeline pipeline BertForSequenceClassification from cm-mueller +author: John Snow Labs +name: bert_classifier_bacnet_klassifizierung_raumlufttechnik_pipeline +date: 2024-09-01 +tags: [de, open_source, pipeline, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_bacnet_klassifizierung_raumlufttechnik_pipeline` is a German model originally trained by cm-mueller. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_bacnet_klassifizierung_raumlufttechnik_pipeline_de_5.4.2_3.0_1725204546928.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_bacnet_klassifizierung_raumlufttechnik_pipeline_de_5.4.2_3.0_1725204546928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_bacnet_klassifizierung_raumlufttechnik_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_bacnet_klassifizierung_raumlufttechnik_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_bacnet_klassifizierung_raumlufttechnik_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|409.2 MB| + +## References + +https://huggingface.co/cm-mueller/BACnet-Klassifizierung-Raumlufttechnik + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sanskrit_saskta_sub2_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sanskrit_saskta_sub2_en.md new file mode 100644 index 00000000000000..ba3f1f4f7758a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sanskrit_saskta_sub2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_classifier_sanskrit_saskta_sub2 BertForSequenceClassification from researchaccount +author: John Snow Labs +name: bert_classifier_sanskrit_saskta_sub2 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sanskrit_saskta_sub2` is a English model originally trained by researchaccount. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub2_en_5.4.2_3.0_1725204689429.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub2_en_5.4.2_3.0_1725204689429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_sanskrit_saskta_sub2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_sanskrit_saskta_sub2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sanskrit_saskta_sub2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|610.9 MB| + +## References + +https://huggingface.co/researchaccount/sa_sub2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sanskrit_saskta_sub2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sanskrit_saskta_sub2_pipeline_en.md new file mode 100644 index 00000000000000..5ba3a82601030e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sanskrit_saskta_sub2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classifier_sanskrit_saskta_sub2_pipeline pipeline BertForSequenceClassification from researchaccount +author: John Snow Labs +name: bert_classifier_sanskrit_saskta_sub2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sanskrit_saskta_sub2_pipeline` is a English model originally trained by researchaccount. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub2_pipeline_en_5.4.2_3.0_1725204724422.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub2_pipeline_en_5.4.2_3.0_1725204724422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_sanskrit_saskta_sub2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_sanskrit_saskta_sub2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sanskrit_saskta_sub2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|610.9 MB| + +## References + +https://huggingface.co/researchaccount/sa_sub2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sanskrit_saskta_sub5_ar.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sanskrit_saskta_sub5_ar.md new file mode 100644 index 00000000000000..1df547c8505060 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sanskrit_saskta_sub5_ar.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Arabic bert_classifier_sanskrit_saskta_sub5 BertForSequenceClassification from researchaccount +author: John Snow Labs +name: bert_classifier_sanskrit_saskta_sub5 +date: 2024-09-01 +tags: [ar, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: ar +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sanskrit_saskta_sub5` is a Arabic model originally trained by researchaccount. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub5_ar_5.4.2_3.0_1725204738443.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub5_ar_5.4.2_3.0_1725204738443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_sanskrit_saskta_sub5","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_sanskrit_saskta_sub5", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sanskrit_saskta_sub5| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|610.7 MB| + +## References + +https://huggingface.co/researchaccount/sa_sub5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sanskrit_saskta_sub5_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sanskrit_saskta_sub5_pipeline_ar.md new file mode 100644 index 00000000000000..27740a9947e72d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sanskrit_saskta_sub5_pipeline_ar.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Arabic bert_classifier_sanskrit_saskta_sub5_pipeline pipeline BertForSequenceClassification from researchaccount +author: John Snow Labs +name: bert_classifier_sanskrit_saskta_sub5_pipeline +date: 2024-09-01 +tags: [ar, open_source, pipeline, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sanskrit_saskta_sub5_pipeline` is a Arabic model originally trained by researchaccount. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub5_pipeline_ar_5.4.2_3.0_1725204777930.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub5_pipeline_ar_5.4.2_3.0_1725204777930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_sanskrit_saskta_sub5_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_sanskrit_saskta_sub5_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sanskrit_saskta_sub5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|610.7 MB| + +## References + +https://huggingface.co/researchaccount/sa_sub5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sead_l_6_h_384_a_12_qnli_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sead_l_6_h_384_a_12_qnli_en.md new file mode 100644 index 00000000000000..a505d5a3c1c5fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sead_l_6_h_384_a_12_qnli_en.md @@ -0,0 +1,111 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from course5i) +author: John Snow Labs +name: bert_classifier_sead_l_6_h_384_a_12_qnli +date: 2024-09-01 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `SEAD-L-6_H-384_A-12-qnli` is a English model originally trained by `course5i`. + +## Predicted Entities + +`0`, `1` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_384_a_12_qnli_en_5.4.2_3.0_1725204630376.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_384_a_12_qnli_en_5.4.2_3.0_1725204630376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_sead_l_6_h_384_a_12_qnli","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_sead_l_6_h_384_a_12_qnli","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.glue_qnli.6l_384d_a12a.by_course5i").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sead_l_6_h_384_a_12_qnli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|84.3 MB| + +## References + +References + +- https://huggingface.co/course5i/SEAD-L-6_H-384_A-12-qnli +- https://arxiv.org/abs/1910.01108 +- https://arxiv.org/abs/1909.10351 +- https://arxiv.org/abs/2002.10957 +- https://arxiv.org/abs/1810.04805 +- https://arxiv.org/abs/1804.07461 +- https://arxiv.org/abs/1905.00537 +- https://www.adasci.org/journals/lattice-35309407/?volumes=true&open=621a3b18edc4364e8a96cb63 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sead_l_6_h_384_a_12_qnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sead_l_6_h_384_a_12_qnli_pipeline_en.md new file mode 100644 index 00000000000000..0b0f5f73ccc52c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sead_l_6_h_384_a_12_qnli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classifier_sead_l_6_h_384_a_12_qnli_pipeline pipeline BertForSequenceClassification from course5i +author: John Snow Labs +name: bert_classifier_sead_l_6_h_384_a_12_qnli_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sead_l_6_h_384_a_12_qnli_pipeline` is a English model originally trained by course5i. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_384_a_12_qnli_pipeline_en_5.4.2_3.0_1725204635247.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_384_a_12_qnli_pipeline_en_5.4.2_3.0_1725204635247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_sead_l_6_h_384_a_12_qnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_sead_l_6_h_384_a_12_qnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sead_l_6_h_384_a_12_qnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|84.3 MB| + +## References + +https://huggingface.co/course5i/SEAD-L-6_H-384_A-12-qnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sead_l_6_h_384_a_12_rte_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sead_l_6_h_384_a_12_rte_en.md new file mode 100644 index 00000000000000..583859635726d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sead_l_6_h_384_a_12_rte_en.md @@ -0,0 +1,111 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from course5i) +author: John Snow Labs +name: bert_classifier_sead_l_6_h_384_a_12_rte +date: 2024-09-01 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `SEAD-L-6_H-384_A-12-rte` is a English model originally trained by `course5i`. + +## Predicted Entities + +`0`, `1` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_384_a_12_rte_en_5.4.2_3.0_1725204493962.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_384_a_12_rte_en_5.4.2_3.0_1725204493962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_sead_l_6_h_384_a_12_rte","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_sead_l_6_h_384_a_12_rte","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.glue_rte.6l_384d_a12a.by_course5i").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sead_l_6_h_384_a_12_rte| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|84.2 MB| + +## References + +References + +- https://huggingface.co/course5i/SEAD-L-6_H-384_A-12-rte +- https://arxiv.org/abs/1910.01108 +- https://arxiv.org/abs/1909.10351 +- https://arxiv.org/abs/2002.10957 +- https://arxiv.org/abs/1810.04805 +- https://arxiv.org/abs/1804.07461 +- https://arxiv.org/abs/1905.00537 +- https://www.adasci.org/journals/lattice-35309407/?volumes=true&open=621a3b18edc4364e8a96cb63 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sead_l_6_h_384_a_12_rte_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sead_l_6_h_384_a_12_rte_pipeline_en.md new file mode 100644 index 00000000000000..4ca7a544bf7f6a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_sead_l_6_h_384_a_12_rte_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classifier_sead_l_6_h_384_a_12_rte_pipeline pipeline BertForSequenceClassification from course5i +author: John Snow Labs +name: bert_classifier_sead_l_6_h_384_a_12_rte_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sead_l_6_h_384_a_12_rte_pipeline` is a English model originally trained by course5i. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_384_a_12_rte_pipeline_en_5.4.2_3.0_1725204499950.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_384_a_12_rte_pipeline_en_5.4.2_3.0_1725204499950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_sead_l_6_h_384_a_12_rte_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_sead_l_6_h_384_a_12_rte_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sead_l_6_h_384_a_12_rte_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|84.2 MB| + +## References + +https://huggingface.co/course5i/SEAD-L-6_H-384_A-12-rte + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_finetuned_ner_g1_g2_g3_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_finetuned_ner_g1_g2_g3_en.md new file mode 100644 index 00000000000000..b631b836d81fc5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_finetuned_ner_g1_g2_g3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_ner_g1_g2_g3 DistilBertForTokenClassification from avi10 +author: John Snow Labs +name: bert_finetuned_ner_g1_g2_g3 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_g1_g2_g3` is a English model originally trained by avi10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_g1_g2_g3_en_5.4.2_3.0_1725171271767.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_g1_g2_g3_en_5.4.2_3.0_1725171271767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("bert_finetuned_ner_g1_g2_g3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("bert_finetuned_ner_g1_g2_g3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_g1_g2_g3| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/avi10/bert-finetuned-ner-G1-G2-G3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_finetuned_ner_t2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_finetuned_ner_t2_pipeline_en.md new file mode 100644 index 00000000000000..a238ebd07fc6e4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_finetuned_ner_t2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_ner_t2_pipeline pipeline DistilBertForTokenClassification from avi10 +author: John Snow Labs +name: bert_finetuned_ner_t2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_t2_pipeline` is a English model originally trained by avi10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_t2_pipeline_en_5.4.2_3.0_1725160951079.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_t2_pipeline_en_5.4.2_3.0_1725160951079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_ner_t2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_ner_t2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_t2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/avi10/bert-finetuned-ner-T2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_en.md new file mode 100644 index 00000000000000..4b537a6df5bc98 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English BertForQuestionAnswering Base Uncased model (from anas-awadalla) +author: John Snow Labs +name: bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4 +date: 2024-09-01 +tags: [en, open_source, bert, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-few-shot-k-1024-finetuned-squad-seed-4` is a English model originally trained by `anas-awadalla`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_en_5.4.2_3.0_1725185650224.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_en_5.4.2_3.0_1725185650224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = MultiDocumentAssembler() \ + .setInputCols(["question", "context"]) \ + .setOutputCols(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4","en") \ + .setInputCols(["document_question", "document_context"]) \ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, spanClassifier]) + +data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4","en") + .setInputCols(Array("document", "token")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) + +val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.bert.squad.uncased_seed_4_base_1024d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|407.2 MB| + +## References + +References + +- https://huggingface.co/anas-awadalla/bert-base-uncased-few-shot-k-1024-finetuned-squad-seed-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_pipeline_en.md new file mode 100644 index 00000000000000..e221a333c248f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_pipeline pipeline BertForQuestionAnswering from anas-awadalla +author: John Snow Labs +name: bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_pipeline` is a English model originally trained by anas-awadalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_pipeline_en_5.4.2_3.0_1725185671302.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_pipeline_en_5.4.2_3.0_1725185671302.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_qa_base_uncased_few_shot_k_1024_finetuned_squad_seed_4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/anas-awadalla/bert-base-uncased-few-shot-k-1024-finetuned-squad-seed-4 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_qa_burmese_nepal_bhasa_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_burmese_nepal_bhasa_model_pipeline_en.md new file mode 100644 index 00000000000000..405b2d1e275bea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_burmese_nepal_bhasa_model_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_qa_burmese_nepal_bhasa_model_pipeline pipeline BertForQuestionAnswering from aozorahime +author: John Snow Labs +name: bert_qa_burmese_nepal_bhasa_model_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_burmese_nepal_bhasa_model_pipeline` is a English model originally trained by aozorahime. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_burmese_nepal_bhasa_model_pipeline_en_5.4.2_3.0_1725151603726.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_burmese_nepal_bhasa_model_pipeline_en_5.4.2_3.0_1725151603726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_qa_burmese_nepal_bhasa_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_qa_burmese_nepal_bhasa_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_qa_burmese_nepal_bhasa_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/aozorahime/my-new-model + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_en.md new file mode 100644 index 00000000000000..837237b78d02f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForQuestionAnswering model (from anas-awadalla) +author: John Snow Labs +name: bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6 +date: 2024-09-01 +tags: [en, open_source, question_answering, bert, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-512-finetuned-squad-seed-6` is a English model orginally trained by `anas-awadalla`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_en_5.4.2_3.0_1725185344375.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_en_5.4.2_3.0_1725185344375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = BertForQuestionAnswering +.pretrained("bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squad.span_bert.base_cased_512d_seed_6").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|386.6 MB| + +## References + +References + +- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-512-finetuned-squad-seed-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_qa_squad_mbert_model_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_squad_mbert_model_en.md new file mode 100644 index 00000000000000..dd8f83aa060eaa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_squad_mbert_model_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForQuestionAnswering model (from ZYW) +author: John Snow Labs +name: bert_qa_squad_mbert_model +date: 2024-09-01 +tags: [en, open_source, question_answering, bert, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `squad-mbert-model` is a English model orginally trained by `ZYW`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_squad_mbert_model_en_5.4.2_3.0_1725185441451.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_squad_mbert_model_en_5.4.2_3.0_1725185441451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_squad_mbert_model","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = BertForQuestionAnswering +.pretrained("bert_qa_squad_mbert_model","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squad.multi_lingual_bert.by_ZYW").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_qa_squad_mbert_model| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|665.1 MB| + +## References + +References + +- https://huggingface.co/ZYW/squad-mbert-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_qa_squad_mbert_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_squad_mbert_model_pipeline_en.md new file mode 100644 index 00000000000000..183fbeb6387475 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_squad_mbert_model_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_qa_squad_mbert_model_pipeline pipeline BertForQuestionAnswering from ZYW +author: John Snow Labs +name: bert_qa_squad_mbert_model_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_squad_mbert_model_pipeline` is a English model originally trained by ZYW. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_squad_mbert_model_pipeline_en_5.4.2_3.0_1725185476291.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_squad_mbert_model_pipeline_en_5.4.2_3.0_1725185476291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_qa_squad_mbert_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_qa_squad_mbert_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_qa_squad_mbert_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/ZYW/squad-mbert-model + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_qa_unqover_bert_base_uncased_squad_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_unqover_bert_base_uncased_squad_en.md new file mode 100644 index 00000000000000..728b30fc1f2cc4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_unqover_bert_base_uncased_squad_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForQuestionAnswering model (from tli8hf) +author: John Snow Labs +name: bert_qa_unqover_bert_base_uncased_squad +date: 2024-09-01 +tags: [en, open_source, question_answering, bert, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `unqover-bert-base-uncased-squad` is a English model orginally trained by `tli8hf`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_unqover_bert_base_uncased_squad_en_5.5.0_3.0_1725215834398.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_unqover_bert_base_uncased_squad_en_5.5.0_3.0_1725215834398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_unqover_bert_base_uncased_squad","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = BertForQuestionAnswering +.pretrained("bert_qa_unqover_bert_base_uncased_squad","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squad.bert.base_uncased.by_tli8hf").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_qa_unqover_bert_base_uncased_squad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|407.2 MB| + +## References + +References + +- https://huggingface.co/tli8hf/unqover-bert-base-uncased-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_qa_unqover_bert_base_uncased_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_unqover_bert_base_uncased_squad_pipeline_en.md new file mode 100644 index 00000000000000..9ff466844e8400 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_unqover_bert_base_uncased_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_qa_unqover_bert_base_uncased_squad_pipeline pipeline BertForQuestionAnswering from tli8hf +author: John Snow Labs +name: bert_qa_unqover_bert_base_uncased_squad_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_unqover_bert_base_uncased_squad_pipeline` is a English model originally trained by tli8hf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_unqover_bert_base_uncased_squad_pipeline_en_5.5.0_3.0_1725215855981.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_unqover_bert_base_uncased_squad_pipeline_en_5.5.0_3.0_1725215855981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_qa_unqover_bert_base_uncased_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_qa_unqover_bert_base_uncased_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_qa_unqover_bert_base_uncased_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/tli8hf/unqover-bert-base-uncased-squad + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_qa_vanhoan_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_vanhoan_finetuned_squad_en.md new file mode 100644 index 00000000000000..b32d3676ad9a1f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_vanhoan_finetuned_squad_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English BertForQuestionAnswering Cased model (from VanHoan) +author: John Snow Labs +name: bert_qa_vanhoan_finetuned_squad +date: 2024-09-01 +tags: [en, open_source, bert, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `VanHoan`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_vanhoan_finetuned_squad_en_5.5.0_3.0_1725215092021.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_vanhoan_finetuned_squad_en_5.5.0_3.0_1725215092021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_vanhoan_finetuned_squad","en")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_vanhoan_finetuned_squad","en") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_qa_vanhoan_finetuned_squad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|403.7 MB| + +## References + +References + +- https://huggingface.co/VanHoan/bert-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_qa_vanhoan_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_vanhoan_finetuned_squad_pipeline_en.md new file mode 100644 index 00000000000000..2926e4546a730e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_vanhoan_finetuned_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_qa_vanhoan_finetuned_squad_pipeline pipeline BertForQuestionAnswering from VanHoan +author: John Snow Labs +name: bert_qa_vanhoan_finetuned_squad_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_vanhoan_finetuned_squad_pipeline` is a English model originally trained by VanHoan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_vanhoan_finetuned_squad_pipeline_en_5.5.0_3.0_1725215116400.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_vanhoan_finetuned_squad_pipeline_en_5.5.0_3.0_1725215116400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_qa_vanhoan_finetuned_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_qa_vanhoan_finetuned_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_qa_vanhoan_finetuned_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/VanHoan/bert-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_sequence_classifier_env_topic_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-01-bert_sequence_classifier_env_topic_pipeline_zh.md new file mode 100644 index 00000000000000..eefa1c5eae241a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_sequence_classifier_env_topic_pipeline_zh.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Chinese bert_sequence_classifier_env_topic_pipeline pipeline BertForSequenceClassification from celtics1863 +author: John Snow Labs +name: bert_sequence_classifier_env_topic_pipeline +date: 2024-09-01 +tags: [zh, open_source, pipeline, onnx] +task: Text Classification +language: zh +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_env_topic_pipeline` is a Chinese model originally trained by celtics1863. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_env_topic_pipeline_zh_5.4.2_3.0_1725205352321.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_env_topic_pipeline_zh_5.4.2_3.0_1725205352321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sequence_classifier_env_topic_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sequence_classifier_env_topic_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_env_topic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|383.6 MB| + +## References + +https://huggingface.co/celtics1863/env-bert-topic + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_sequence_classifier_env_topic_zh.md b/docs/_posts/ahmedlone127/2024-09-01-bert_sequence_classifier_env_topic_zh.md new file mode 100644 index 00000000000000..d95b00f164895c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_sequence_classifier_env_topic_zh.md @@ -0,0 +1,98 @@ +--- +layout: model +title: Chinese BertForSequenceClassification Cased model (from celtics1863) +author: John Snow Labs +name: bert_sequence_classifier_env_topic +date: 2024-09-01 +tags: [zh, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: zh +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `env-bert-topic` is a Chinese model originally trained by `celtics1863`. + +## Predicted Entities + +`沙尘暴`, `沙漠治理`, `温室气体`, `污水处理`, `地球一小时`, `PM 2.5`, `碳金融`, `环保经济`, `环保行业`, `环评工程师`, `太阳能`, `核污染`, `环境伦理学`, `空气污染`, `重金属污染`, `化学污染`, `自来水`, `水处理`, `环境评估`, `巴黎协定`, `碳排放`, `温室效应`, `雾霾`, `低碳`, `垃圾焚烧`, `污水排放`, `室内空气污染`, `物种多样性`, `垃圾`, `环保组织`, `垃圾分类`, `垃圾处理`, `环境污染`, `净水`, `植树`, `生物多样性`, `环境工程`, `穹顶之下（纪录片）`, `太空垃圾`, `水污染`, `核能`, `气候变化`, `环保督查`, `工业污染`, `水处理工程`, `环境科学`, `环境保护`, `净水器`, `秸秆焚烧`, `自然环境`, `建筑节能`, `碳交易`, `净水设备`, `邻居噪音`, `节能减排`, `风能及风力发电`, `二氧化碳`, `雾霾治理`, `绿色建筑`, `噪音污染`, `噪音`, `污染治理`, `生活`, `全球变暖`, `野生动物保护`, `环境评价`, `生态环境`, `土壤污染`, `垃圾处理器` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_env_topic_zh_5.4.2_3.0_1725205331054.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_env_topic_zh_5.4.2_3.0_1725205331054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_env_topic","zh") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_env_topic","zh") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_env_topic| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|zh| +|Size:|383.6 MB| + +## References + +References + +- https://huggingface.co/celtics1863/env-bert-topic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_sequence_classifier_wiki_paragraphs_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_sequence_classifier_wiki_paragraphs_en.md new file mode 100644 index 00000000000000..4b3535556e7736 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_sequence_classifier_wiki_paragraphs_en.md @@ -0,0 +1,100 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from dennlinger) +author: John Snow Labs +name: bert_sequence_classifier_wiki_paragraphs +date: 2024-09-01 +tags: [en, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-wiki-paragraphs` is a English model originally trained by `dennlinger`. + +## Predicted Entities + +`1`, `0` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_wiki_paragraphs_en_5.4.2_3.0_1725205143759.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_wiki_paragraphs_en_5.4.2_3.0_1725205143759.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_wiki_paragraphs","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_wiki_paragraphs","en") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_wiki_paragraphs| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +References + +- https://huggingface.co/dennlinger/bert-wiki-paragraphs +- https://arxiv.org/abs/2012.03619 +- https://arxiv.org/abs/1803.09337 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_sequence_classifier_wiki_paragraphs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_sequence_classifier_wiki_paragraphs_pipeline_en.md new file mode 100644 index 00000000000000..55ee82e087f002 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_sequence_classifier_wiki_paragraphs_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_sequence_classifier_wiki_paragraphs_pipeline pipeline BertForSequenceClassification from dennlinger +author: John Snow Labs +name: bert_sequence_classifier_wiki_paragraphs_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_wiki_paragraphs_pipeline` is a English model originally trained by dennlinger. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_wiki_paragraphs_pipeline_en_5.4.2_3.0_1725205167023.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_wiki_paragraphs_pipeline_en_5.4.2_3.0_1725205167023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sequence_classifier_wiki_paragraphs_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sequence_classifier_wiki_paragraphs_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_wiki_paragraphs_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/dennlinger/bert-wiki-paragraphs + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_solidity_re_entrancy_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_solidity_re_entrancy_en.md new file mode 100644 index 00000000000000..6a6991a115cc09 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_solidity_re_entrancy_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_solidity_re_entrancy RoBertaForSequenceClassification from Quangnguyen711 +author: John Snow Labs +name: bert_solidity_re_entrancy +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_solidity_re_entrancy` is a English model originally trained by Quangnguyen711. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_solidity_re_entrancy_en_5.5.0_3.0_1725212515388.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_solidity_re_entrancy_en_5.5.0_3.0_1725212515388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("bert_solidity_re_entrancy","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("bert_solidity_re_entrancy", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_solidity_re_entrancy| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/Quangnguyen711/bert-solidity-re-entrancy \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_solidity_re_entrancy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_solidity_re_entrancy_pipeline_en.md new file mode 100644 index 00000000000000..5b25ad945f6d01 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_solidity_re_entrancy_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_solidity_re_entrancy_pipeline pipeline RoBertaForSequenceClassification from Quangnguyen711 +author: John Snow Labs +name: bert_solidity_re_entrancy_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_solidity_re_entrancy_pipeline` is a English model originally trained by Quangnguyen711. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_solidity_re_entrancy_pipeline_en_5.5.0_3.0_1725212540785.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_solidity_re_entrancy_pipeline_en_5.5.0_3.0_1725212540785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_solidity_re_entrancy_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_solidity_re_entrancy_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_solidity_re_entrancy_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.4 MB| + +## References + +https://huggingface.co/Quangnguyen711/bert-solidity-re-entrancy + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_token_classifier_berturk_cased_keyword_discriminator_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-01-bert_token_classifier_berturk_cased_keyword_discriminator_pipeline_tr.md new file mode 100644 index 00000000000000..cedb4f3c699b48 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_token_classifier_berturk_cased_keyword_discriminator_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish bert_token_classifier_berturk_cased_keyword_discriminator_pipeline pipeline BertForTokenClassification from yanekyuk +author: John Snow Labs +name: bert_token_classifier_berturk_cased_keyword_discriminator_pipeline +date: 2024-09-01 +tags: [tr, open_source, pipeline, onnx] +task: Named Entity Recognition +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_token_classifier_berturk_cased_keyword_discriminator_pipeline` is a Turkish model originally trained by yanekyuk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_token_classifier_berturk_cased_keyword_discriminator_pipeline_tr_5.4.2_3.0_1725163781806.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_token_classifier_berturk_cased_keyword_discriminator_pipeline_tr_5.4.2_3.0_1725163781806.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_token_classifier_berturk_cased_keyword_discriminator_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_token_classifier_berturk_cased_keyword_discriminator_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_token_classifier_berturk_cased_keyword_discriminator_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|412.3 MB| + +## References + +https://huggingface.co/yanekyuk/berturk-cased-keyword-discriminator + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_token_classifier_loodos_sunlp_ner_turkish_tr.md b/docs/_posts/ahmedlone127/2024-09-01-bert_token_classifier_loodos_sunlp_ner_turkish_tr.md new file mode 100644 index 00000000000000..008a72cdb9e1cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bert_token_classifier_loodos_sunlp_ner_turkish_tr.md @@ -0,0 +1,100 @@ +--- +layout: model +title: Turkish BertForTokenClassification Cased model (from busecarik) +author: John Snow Labs +name: bert_token_classifier_loodos_sunlp_ner_turkish +date: 2024-09-01 +tags: [tr, open_source, bert, token_classification, ner, onnx] +task: Named Entity Recognition +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-loodos-sunlp-ner-turkish` is a Turkish model originally trained by `busecarik`. + +## Predicted Entities + +`ORGANIZATION`, `TVSHOW`, `MONEY`, `LOCATION`, `PRODUCT`, `TIME`, `PERSON` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_token_classifier_loodos_sunlp_ner_turkish_tr_5.4.2_3.0_1725163972953.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_token_classifier_loodos_sunlp_ner_turkish_tr_5.4.2_3.0_1725163972953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_loodos_sunlp_ner_turkish","tr") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, tokenClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_loodos_sunlp_ner_turkish","tr") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_token_classifier_loodos_sunlp_ner_turkish| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|tr| +|Size:|412.4 MB| + +## References + +References + +- https://huggingface.co/busecarik/bert-loodos-sunlp-ner-turkish +- https://github.com/SU-NLP/SUNLP-Twitter-NER-Dataset +- http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.484.pdf \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bertweet_large_sexism_detector_nlp_ltu_en.md b/docs/_posts/ahmedlone127/2024-09-01-bertweet_large_sexism_detector_nlp_ltu_en.md new file mode 100644 index 00000000000000..72de766d351983 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bertweet_large_sexism_detector_nlp_ltu_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bertweet_large_sexism_detector_nlp_ltu RoBertaForSequenceClassification from NLP-LTU +author: John Snow Labs +name: bertweet_large_sexism_detector_nlp_ltu +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertweet_large_sexism_detector_nlp_ltu` is a English model originally trained by NLP-LTU. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertweet_large_sexism_detector_nlp_ltu_en_5.4.2_3.0_1725168204438.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertweet_large_sexism_detector_nlp_ltu_en_5.4.2_3.0_1725168204438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("bertweet_large_sexism_detector_nlp_ltu","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("bertweet_large_sexism_detector_nlp_ltu", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertweet_large_sexism_detector_nlp_ltu| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NLP-LTU/bertweet-large-sexism-detector \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_all_nli_triplet_trasul_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_all_nli_triplet_trasul_en.md new file mode 100644 index 00000000000000..a4eb4a8aad34eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_all_nli_triplet_trasul_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_all_nli_triplet_trasul BGEEmbeddings from trasul +author: John Snow Labs +name: bge_base_all_nli_triplet_trasul +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_all_nli_triplet_trasul` is a English model originally trained by trasul. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_all_nli_triplet_trasul_en_5.4.2_3.0_1725198335585.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_all_nli_triplet_trasul_en_5.4.2_3.0_1725198335585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_all_nli_triplet_trasul","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_all_nli_triplet_trasul","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_all_nli_triplet_trasul| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|377.8 MB| + +## References + +https://huggingface.co/trasul/bge-base-all-nli-triplet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_all_nli_triplet_trasul_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_all_nli_triplet_trasul_pipeline_en.md new file mode 100644 index 00000000000000..ad92b582a6756b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_all_nli_triplet_trasul_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_all_nli_triplet_trasul_pipeline pipeline BGEEmbeddings from trasul +author: John Snow Labs +name: bge_base_all_nli_triplet_trasul_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_all_nli_triplet_trasul_pipeline` is a English model originally trained by trasul. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_all_nli_triplet_trasul_pipeline_en_5.4.2_3.0_1725198368082.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_all_nli_triplet_trasul_pipeline_en_5.4.2_3.0_1725198368082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_all_nli_triplet_trasul_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_all_nli_triplet_trasul_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_all_nli_triplet_trasul_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|377.8 MB| + +## References + +https://huggingface.co/trasul/bge-base-all-nli-triplet + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_automobile_matryoshka_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_automobile_matryoshka_en.md new file mode 100644 index 00000000000000..5470b49b0ece7b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_automobile_matryoshka_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_automobile_matryoshka BGEEmbeddings from ValentinaKim +author: John Snow Labs +name: bge_base_automobile_matryoshka +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_automobile_matryoshka` is a English model originally trained by ValentinaKim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_automobile_matryoshka_en_5.5.0_3.0_1725228339810.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_automobile_matryoshka_en_5.5.0_3.0_1725228339810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_automobile_matryoshka","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_automobile_matryoshka","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_automobile_matryoshka| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|375.0 MB| + +## References + +https://huggingface.co/ValentinaKim/bge-base-automobile-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_automobile_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_automobile_matryoshka_pipeline_en.md new file mode 100644 index 00000000000000..93ef52d234f06d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_automobile_matryoshka_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_automobile_matryoshka_pipeline pipeline BGEEmbeddings from ValentinaKim +author: John Snow Labs +name: bge_base_automobile_matryoshka_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_automobile_matryoshka_pipeline` is a English model originally trained by ValentinaKim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_automobile_matryoshka_pipeline_en_5.5.0_3.0_1725228377534.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_automobile_matryoshka_pipeline_en_5.5.0_3.0_1725228377534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_automobile_matryoshka_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_automobile_matryoshka_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_automobile_matryoshka_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|375.0 MB| + +## References + +https://huggingface.co/ValentinaKim/bge-base-automobile-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_aws_case_studies_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_aws_case_studies_en.md new file mode 100644 index 00000000000000..53c8fd693e6df9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_aws_case_studies_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_aws_case_studies BGEEmbeddings from anishareddyalla +author: John Snow Labs +name: bge_base_aws_case_studies +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_aws_case_studies` is a English model originally trained by anishareddyalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_aws_case_studies_en_5.4.2_3.0_1725199199908.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_aws_case_studies_en_5.4.2_3.0_1725199199908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_aws_case_studies","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_aws_case_studies","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_aws_case_studies| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|390.3 MB| + +## References + +https://huggingface.co/anishareddyalla/bge-base-aws-case-studies \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_aws_case_studies_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_aws_case_studies_pipeline_en.md new file mode 100644 index 00000000000000..821be9a5642dab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_aws_case_studies_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_aws_case_studies_pipeline pipeline BGEEmbeddings from anishareddyalla +author: John Snow Labs +name: bge_base_aws_case_studies_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_aws_case_studies_pipeline` is a English model originally trained by anishareddyalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_aws_case_studies_pipeline_en_5.4.2_3.0_1725199226911.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_aws_case_studies_pipeline_en_5.4.2_3.0_1725199226911.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_aws_case_studies_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_aws_case_studies_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_aws_case_studies_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|390.3 MB| + +## References + +https://huggingface.co/anishareddyalla/bge-base-aws-case-studies + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_embedding_5_8_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_embedding_5_8_en.md new file mode 100644 index 00000000000000..8c98d313ae068f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_embedding_5_8_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_embedding_5_8 BGEEmbeddings from quangtqv +author: John Snow Labs +name: bge_base_embedding_5_8 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_embedding_5_8` is a English model originally trained by quangtqv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_embedding_5_8_en_5.4.2_3.0_1725199123449.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_embedding_5_8_en_5.4.2_3.0_1725199123449.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_embedding_5_8","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_embedding_5_8","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_embedding_5_8| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|386.9 MB| + +## References + +https://huggingface.co/quangtqv/bge_base_embedding_5_8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_embedding_5_8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_embedding_5_8_pipeline_en.md new file mode 100644 index 00000000000000..dcc210c7827f96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_embedding_5_8_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_embedding_5_8_pipeline pipeline BGEEmbeddings from quangtqv +author: John Snow Labs +name: bge_base_embedding_5_8_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_embedding_5_8_pipeline` is a English model originally trained by quangtqv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_embedding_5_8_pipeline_en_5.4.2_3.0_1725199152227.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_embedding_5_8_pipeline_en_5.4.2_3.0_1725199152227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_embedding_5_8_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_embedding_5_8_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_embedding_5_8_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|386.9 MB| + +## References + +https://huggingface.co/quangtqv/bge_base_embedding_5_8 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_embedding_6_8_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_embedding_6_8_en.md new file mode 100644 index 00000000000000..9e641f14434900 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_embedding_6_8_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_embedding_6_8 BGEEmbeddings from quangtqv +author: John Snow Labs +name: bge_base_embedding_6_8 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_embedding_6_8` is a English model originally trained by quangtqv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_embedding_6_8_en_5.4.2_3.0_1725198662883.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_embedding_6_8_en_5.4.2_3.0_1725198662883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_embedding_6_8","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_embedding_6_8","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_embedding_6_8| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|386.9 MB| + +## References + +https://huggingface.co/quangtqv/bge_base_embedding_6_8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_embedding_6_8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_embedding_6_8_pipeline_en.md new file mode 100644 index 00000000000000..c4f5d9d64da7f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_embedding_6_8_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_embedding_6_8_pipeline pipeline BGEEmbeddings from quangtqv +author: John Snow Labs +name: bge_base_embedding_6_8_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_embedding_6_8_pipeline` is a English model originally trained by quangtqv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_embedding_6_8_pipeline_en_5.4.2_3.0_1725198693310.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_embedding_6_8_pipeline_en_5.4.2_3.0_1725198693310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_embedding_6_8_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_embedding_6_8_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_embedding_6_8_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|386.9 MB| + +## References + +https://huggingface.co/quangtqv/bge_base_embedding_6_8 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_bioembed768_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_bioembed768_en.md new file mode 100644 index 00000000000000..83b7c2f9584ab3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_bioembed768_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_english_bioembed768 BGEEmbeddings from pavanmantha +author: John Snow Labs +name: bge_base_english_bioembed768 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_bioembed768` is a English model originally trained by pavanmantha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_bioembed768_en_5.5.0_3.0_1725228333819.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_bioembed768_en_5.5.0_3.0_1725228333819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_english_bioembed768","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_english_bioembed768","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_bioembed768| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|389.3 MB| + +## References + +https://huggingface.co/pavanmantha/bge-base-en-bioembed768 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_bioembed768_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_bioembed768_pipeline_en.md new file mode 100644 index 00000000000000..2626f04e98786e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_bioembed768_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_english_bioembed768_pipeline pipeline BGEEmbeddings from pavanmantha +author: John Snow Labs +name: bge_base_english_bioembed768_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_bioembed768_pipeline` is a English model originally trained by pavanmantha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_bioembed768_pipeline_en_5.5.0_3.0_1725228376655.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_bioembed768_pipeline_en_5.5.0_3.0_1725228376655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_english_bioembed768_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_english_bioembed768_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_bioembed768_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|389.3 MB| + +## References + +https://huggingface.co/pavanmantha/bge-base-en-bioembed768 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_bioembed_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_bioembed_en.md new file mode 100644 index 00000000000000..8a72b8f81ba94a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_bioembed_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_english_bioembed BGEEmbeddings from pavanmantha +author: John Snow Labs +name: bge_base_english_bioembed +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_bioembed` is a English model originally trained by pavanmantha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_bioembed_en_5.4.2_3.0_1725198852426.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_bioembed_en_5.4.2_3.0_1725198852426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_english_bioembed","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_english_bioembed","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_bioembed| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|389.2 MB| + +## References + +https://huggingface.co/pavanmantha/bge-base-en-bioembed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_bioembed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_bioembed_pipeline_en.md new file mode 100644 index 00000000000000..cec1512790d5fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_bioembed_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_english_bioembed_pipeline pipeline BGEEmbeddings from pavanmantha +author: John Snow Labs +name: bge_base_english_bioembed_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_bioembed_pipeline` is a English model originally trained by pavanmantha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_bioembed_pipeline_en_5.4.2_3.0_1725198880215.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_bioembed_pipeline_en_5.4.2_3.0_1725198880215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_english_bioembed_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_english_bioembed_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_bioembed_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|389.2 MB| + +## References + +https://huggingface.co/pavanmantha/bge-base-en-bioembed + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_honsec10k_embed_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_honsec10k_embed_en.md new file mode 100644 index 00000000000000..74f6175a7001b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_honsec10k_embed_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_english_honsec10k_embed BGEEmbeddings from pavanmantha +author: John Snow Labs +name: bge_base_english_honsec10k_embed +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_honsec10k_embed` is a English model originally trained by pavanmantha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_honsec10k_embed_en_5.5.0_3.0_1725229206346.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_honsec10k_embed_en_5.5.0_3.0_1725229206346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_english_honsec10k_embed","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_english_honsec10k_embed","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_honsec10k_embed| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.0 MB| + +## References + +https://huggingface.co/pavanmantha/bge-base-en-honsec10k-embed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_honsec10k_embed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_honsec10k_embed_pipeline_en.md new file mode 100644 index 00000000000000..897133e25fd214 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_honsec10k_embed_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_english_honsec10k_embed_pipeline pipeline BGEEmbeddings from pavanmantha +author: John Snow Labs +name: bge_base_english_honsec10k_embed_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_honsec10k_embed_pipeline` is a English model originally trained by pavanmantha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_honsec10k_embed_pipeline_en_5.5.0_3.0_1725229236080.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_honsec10k_embed_pipeline_en_5.5.0_3.0_1725229236080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_english_honsec10k_embed_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_english_honsec10k_embed_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_honsec10k_embed_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.0 MB| + +## References + +https://huggingface.co/pavanmantha/bge-base-en-honsec10k-embed + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_finetuned_ragds_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_finetuned_ragds_en.md new file mode 100644 index 00000000000000..5a47655ee7be51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_finetuned_ragds_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_english_v1_5_finetuned_ragds BGEEmbeddings from aritrasen +author: John Snow Labs +name: bge_base_english_v1_5_finetuned_ragds +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_finetuned_ragds` is a English model originally trained by aritrasen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_ragds_en_5.4.2_3.0_1725198474962.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_ragds_en_5.4.2_3.0_1725198474962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_finetuned_ragds","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_finetuned_ragds","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_finetuned_ragds| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|404.3 MB| + +## References + +https://huggingface.co/aritrasen/bge-base-en-v1.5-finetuned_ragds \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_finetuned_ragds_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_finetuned_ragds_pipeline_en.md new file mode 100644 index 00000000000000..d84cd0ff236c9a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_finetuned_ragds_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_english_v1_5_finetuned_ragds_pipeline pipeline BGEEmbeddings from aritrasen +author: John Snow Labs +name: bge_base_english_v1_5_finetuned_ragds_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_finetuned_ragds_pipeline` is a English model originally trained by aritrasen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_ragds_pipeline_en_5.4.2_3.0_1725198503162.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_ragds_pipeline_en_5.4.2_3.0_1725198503162.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_english_v1_5_finetuned_ragds_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_english_v1_5_finetuned_ragds_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_finetuned_ragds_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|404.3 MB| + +## References + +https://huggingface.co/aritrasen/bge-base-en-v1.5-finetuned_ragds + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_finetuned_ragds_v1_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_finetuned_ragds_v1_en.md new file mode 100644 index 00000000000000..cbe0a48e78525c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_finetuned_ragds_v1_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_english_v1_5_finetuned_ragds_v1 BGEEmbeddings from aritrasen +author: John Snow Labs +name: bge_base_english_v1_5_finetuned_ragds_v1 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_finetuned_ragds_v1` is a English model originally trained by aritrasen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_ragds_v1_en_5.4.2_3.0_1725198687846.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_ragds_v1_en_5.4.2_3.0_1725198687846.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_finetuned_ragds_v1","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_finetuned_ragds_v1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_finetuned_ragds_v1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|404.3 MB| + +## References + +https://huggingface.co/aritrasen/bge-base-en-v1.5-finetuned_ragds_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_finetuned_ragds_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_finetuned_ragds_v1_pipeline_en.md new file mode 100644 index 00000000000000..2473b46a8a3740 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_finetuned_ragds_v1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_english_v1_5_finetuned_ragds_v1_pipeline pipeline BGEEmbeddings from aritrasen +author: John Snow Labs +name: bge_base_english_v1_5_finetuned_ragds_v1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_finetuned_ragds_v1_pipeline` is a English model originally trained by aritrasen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_ragds_v1_pipeline_en_5.4.2_3.0_1725198710921.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_ragds_v1_pipeline_en_5.4.2_3.0_1725198710921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_english_v1_5_finetuned_ragds_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_english_v1_5_finetuned_ragds_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_finetuned_ragds_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|404.3 MB| + +## References + +https://huggingface.co/aritrasen/bge-base-en-v1.5-finetuned_ragds_v1 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_ft_ragds_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_ft_ragds_pipeline_en.md new file mode 100644 index 00000000000000..c13bed32a63adc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_ft_ragds_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_english_v1_5_ft_ragds_pipeline pipeline BGEEmbeddings from aritrasen +author: John Snow Labs +name: bge_base_english_v1_5_ft_ragds_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_ft_ragds_pipeline` is a English model originally trained by aritrasen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_ft_ragds_pipeline_en_5.4.2_3.0_1725199656608.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_ft_ragds_pipeline_en_5.4.2_3.0_1725199656608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_english_v1_5_ft_ragds_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_english_v1_5_ft_ragds_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_ft_ragds_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|404.3 MB| + +## References + +https://huggingface.co/aritrasen/bge-base-en-v1.5-ft_ragds + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_akashmaggon_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_akashmaggon_en.md new file mode 100644 index 00000000000000..81d2a38e0fdd6d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_akashmaggon_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_akashmaggon BGEEmbeddings from akashmaggon +author: John Snow Labs +name: bge_base_financial_matryoshka_akashmaggon +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_akashmaggon` is a English model originally trained by akashmaggon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_akashmaggon_en_5.5.0_3.0_1725228334702.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_akashmaggon_en_5.5.0_3.0_1725228334702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_akashmaggon","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_akashmaggon","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_akashmaggon| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.0 MB| + +## References + +https://huggingface.co/akashmaggon/bge-base-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_akashmaggon_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_akashmaggon_pipeline_en.md new file mode 100644 index 00000000000000..a1c1dd1b5b71cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_akashmaggon_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_akashmaggon_pipeline pipeline BGEEmbeddings from akashmaggon +author: John Snow Labs +name: bge_base_financial_matryoshka_akashmaggon_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_akashmaggon_pipeline` is a English model originally trained by akashmaggon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_akashmaggon_pipeline_en_5.5.0_3.0_1725228377670.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_akashmaggon_pipeline_en_5.5.0_3.0_1725228377670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_akashmaggon_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_akashmaggon_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_akashmaggon_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.0 MB| + +## References + +https://huggingface.co/akashmaggon/bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_asprenger_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_asprenger_en.md new file mode 100644 index 00000000000000..2d9aa9fbc030a3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_asprenger_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_asprenger BGEEmbeddings from asprenger +author: John Snow Labs +name: bge_base_financial_matryoshka_asprenger +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_asprenger` is a English model originally trained by asprenger. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_asprenger_en_5.4.2_3.0_1725199436203.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_asprenger_en_5.4.2_3.0_1725199436203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_asprenger","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_asprenger","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_asprenger| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.0 MB| + +## References + +https://huggingface.co/asprenger/bge-base-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_asprenger_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_asprenger_pipeline_en.md new file mode 100644 index 00000000000000..0c5dcd9a08a96d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_asprenger_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_asprenger_pipeline pipeline BGEEmbeddings from asprenger +author: John Snow Labs +name: bge_base_financial_matryoshka_asprenger_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_asprenger_pipeline` is a English model originally trained by asprenger. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_asprenger_pipeline_en_5.4.2_3.0_1725199464793.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_asprenger_pipeline_en_5.4.2_3.0_1725199464793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_asprenger_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_asprenger_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_asprenger_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.0 MB| + +## References + +https://huggingface.co/asprenger/bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_haophancs_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_haophancs_en.md new file mode 100644 index 00000000000000..44d210ecb81a13 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_haophancs_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_haophancs BGEEmbeddings from haophancs +author: John Snow Labs +name: bge_base_financial_matryoshka_haophancs +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_haophancs` is a English model originally trained by haophancs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_haophancs_en_5.5.0_3.0_1725228480133.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_haophancs_en_5.5.0_3.0_1725228480133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_haophancs","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_haophancs","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_haophancs| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/haophancs/bge-base-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_haophancs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_haophancs_pipeline_en.md new file mode 100644 index 00000000000000..0c7d3d4986b9e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_haophancs_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_haophancs_pipeline pipeline BGEEmbeddings from haophancs +author: John Snow Labs +name: bge_base_financial_matryoshka_haophancs_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_haophancs_pipeline` is a English model originally trained by haophancs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_haophancs_pipeline_en_5.5.0_3.0_1725228508794.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_haophancs_pipeline_en_5.5.0_3.0_1725228508794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_haophancs_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_haophancs_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_haophancs_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/haophancs/bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_liu_xiang_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_liu_xiang_en.md new file mode 100644 index 00000000000000..347a5aff83d06b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_liu_xiang_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_liu_xiang BGEEmbeddings from Liu-Xiang +author: John Snow Labs +name: bge_base_financial_matryoshka_liu_xiang +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_liu_xiang` is a English model originally trained by Liu-Xiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_liu_xiang_en_5.4.2_3.0_1725199292258.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_liu_xiang_en_5.4.2_3.0_1725199292258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_liu_xiang","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_liu_xiang","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_liu_xiang| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.0 MB| + +## References + +https://huggingface.co/Liu-Xiang/bge-base-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_liu_xiang_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_liu_xiang_pipeline_en.md new file mode 100644 index 00000000000000..69fdd7f7cb5c97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_liu_xiang_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_liu_xiang_pipeline pipeline BGEEmbeddings from Liu-Xiang +author: John Snow Labs +name: bge_base_financial_matryoshka_liu_xiang_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_liu_xiang_pipeline` is a English model originally trained by Liu-Xiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_liu_xiang_pipeline_en_5.4.2_3.0_1725199322144.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_liu_xiang_pipeline_en_5.4.2_3.0_1725199322144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_liu_xiang_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_liu_xiang_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_liu_xiang_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.0 MB| + +## References + +https://huggingface.co/Liu-Xiang/bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_moritzglnr_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_moritzglnr_en.md new file mode 100644 index 00000000000000..c12374349223af --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_moritzglnr_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_moritzglnr BGEEmbeddings from moritzglnr +author: John Snow Labs +name: bge_base_financial_matryoshka_moritzglnr +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_moritzglnr` is a English model originally trained by moritzglnr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_moritzglnr_en_5.5.0_3.0_1725229075921.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_moritzglnr_en_5.5.0_3.0_1725229075921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_moritzglnr","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_moritzglnr","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_moritzglnr| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/moritzglnr/bge-base-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_moritzglnr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_moritzglnr_pipeline_en.md new file mode 100644 index 00000000000000..8b92680f5ea39a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_moritzglnr_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_moritzglnr_pipeline pipeline BGEEmbeddings from moritzglnr +author: John Snow Labs +name: bge_base_financial_matryoshka_moritzglnr_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_moritzglnr_pipeline` is a English model originally trained by moritzglnr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_moritzglnr_pipeline_en_5.5.0_3.0_1725229104421.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_moritzglnr_pipeline_en_5.5.0_3.0_1725229104421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_moritzglnr_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_moritzglnr_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_moritzglnr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/moritzglnr/bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_0_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_0_en.md new file mode 100644 index 00000000000000..204199a8c786a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_0_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_test_0 BGEEmbeddings from NickyNicky +author: John Snow Labs +name: bge_base_financial_matryoshka_test_0 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_test_0` is a English model originally trained by NickyNicky. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_0_en_5.5.0_3.0_1725228884265.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_0_en_5.5.0_3.0_1725228884265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_test_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_test_0","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_test_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/NickyNicky/bge-base-financial-matryoshka_test_0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_0_pipeline_en.md new file mode 100644 index 00000000000000..351b0a026f4b8b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_test_0_pipeline pipeline BGEEmbeddings from NickyNicky +author: John Snow Labs +name: bge_base_financial_matryoshka_test_0_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_test_0_pipeline` is a English model originally trained by NickyNicky. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_0_pipeline_en_5.5.0_3.0_1725228912947.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_0_pipeline_en_5.5.0_3.0_1725228912947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_test_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_test_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_test_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/NickyNicky/bge-base-financial-matryoshka_test_0 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_1_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_1_en.md new file mode 100644 index 00000000000000..81f421e3cc59a3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_1_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_test_1 BGEEmbeddings from NickyNicky +author: John Snow Labs +name: bge_base_financial_matryoshka_test_1 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_test_1` is a English model originally trained by NickyNicky. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_1_en_5.5.0_3.0_1725229258005.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_1_en_5.5.0_3.0_1725229258005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_test_1","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_test_1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_test_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/NickyNicky/bge-base-financial-matryoshka_test_1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_1_pipeline_en.md new file mode 100644 index 00000000000000..cf69096b791494 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_test_1_pipeline pipeline BGEEmbeddings from NickyNicky +author: John Snow Labs +name: bge_base_financial_matryoshka_test_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_test_1_pipeline` is a English model originally trained by NickyNicky. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_1_pipeline_en_5.5.0_3.0_1725229286024.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_1_pipeline_en_5.5.0_3.0_1725229286024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_test_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_test_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_test_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/NickyNicky/bge-base-financial-matryoshka_test_1 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_3_pipeline_en.md new file mode 100644 index 00000000000000..abac0f8df9785f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_test_3_pipeline pipeline BGEEmbeddings from NickyNicky +author: John Snow Labs +name: bge_base_financial_matryoshka_test_3_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_test_3_pipeline` is a English model originally trained by NickyNicky. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_3_pipeline_en_5.5.0_3.0_1725228377563.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_3_pipeline_en_5.5.0_3.0_1725228377563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_test_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_test_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_test_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/NickyNicky/bge-base-financial-matryoshka_test_3 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_burmese_my.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_burmese_my.md new file mode 100644 index 00000000000000..11500b64bd5205 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_burmese_my.md @@ -0,0 +1,87 @@ +--- +layout: model +title: Burmese bge_base_financial_matryoshka_test_burmese BGEEmbeddings from IlhamEbdesk +author: John Snow Labs +name: bge_base_financial_matryoshka_test_burmese +date: 2024-09-01 +tags: [my, open_source, onnx, embeddings, bge] +task: Embeddings +language: my +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_test_burmese` is a Burmese model originally trained by IlhamEbdesk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_burmese_my_5.4.2_3.0_1725198471863.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_burmese_my_5.4.2_3.0_1725198471863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_test_burmese","my") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_test_burmese","my") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_test_burmese| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|my| +|Size:|375.9 MB| + +## References + +https://huggingface.co/IlhamEbdesk/bge-base-financial-matryoshka_test_my \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_burmese_pipeline_my.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_burmese_pipeline_my.md new file mode 100644 index 00000000000000..673a957cc75724 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_burmese_pipeline_my.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Burmese bge_base_financial_matryoshka_test_burmese_pipeline pipeline BGEEmbeddings from IlhamEbdesk +author: John Snow Labs +name: bge_base_financial_matryoshka_test_burmese_pipeline +date: 2024-09-01 +tags: [my, open_source, pipeline, onnx] +task: Embeddings +language: my +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_test_burmese_pipeline` is a Burmese model originally trained by IlhamEbdesk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_burmese_pipeline_my_5.4.2_3.0_1725198515678.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_burmese_pipeline_my_5.4.2_3.0_1725198515678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_test_burmese_pipeline", lang = "my") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_test_burmese_pipeline", lang = "my") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_test_burmese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|my| +|Size:|375.9 MB| + +## References + +https://huggingface.co/IlhamEbdesk/bge-base-financial-matryoshka_test_my + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_v1_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_v1_en.md new file mode 100644 index 00000000000000..d60c3e1a2fe6f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_v1_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_v1 BGEEmbeddings from gauravsirola +author: John Snow Labs +name: bge_base_financial_matryoshka_v1 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_v1` is a English model originally trained by gauravsirola. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_v1_en_5.4.2_3.0_1725198629702.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_v1_en_5.4.2_3.0_1725198629702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_v1","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_v1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_v1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/gauravsirola/bge-base-financial-matryoshka-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_v1_pipeline_en.md new file mode 100644 index 00000000000000..cb540005296d41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_v1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_v1_pipeline pipeline BGEEmbeddings from gauravsirola +author: John Snow Labs +name: bge_base_financial_matryoshka_v1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_v1_pipeline` is a English model originally trained by gauravsirola. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_v1_pipeline_en_5.4.2_3.0_1725198658470.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_v1_pipeline_en_5.4.2_3.0_1725198658470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/gauravsirola/bge-base-financial-matryoshka-v1 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_nvidia_matryoshka_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_nvidia_matryoshka_en.md new file mode 100644 index 00000000000000..b88ee133efdbc0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_nvidia_matryoshka_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_nvidia_matryoshka BGEEmbeddings from rbhatia46 +author: John Snow Labs +name: bge_base_financial_nvidia_matryoshka +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_nvidia_matryoshka` is a English model originally trained by rbhatia46. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_nvidia_matryoshka_en_5.5.0_3.0_1725228934418.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_nvidia_matryoshka_en_5.5.0_3.0_1725228934418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_nvidia_matryoshka","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_nvidia_matryoshka","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_nvidia_matryoshka| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/rbhatia46/bge-base-financial-nvidia-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_nvidia_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_nvidia_matryoshka_pipeline_en.md new file mode 100644 index 00000000000000..b7211b8d0995c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_nvidia_matryoshka_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_nvidia_matryoshka_pipeline pipeline BGEEmbeddings from rbhatia46 +author: John Snow Labs +name: bge_base_financial_nvidia_matryoshka_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_nvidia_matryoshka_pipeline` is a English model originally trained by rbhatia46. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_nvidia_matryoshka_pipeline_en_5.5.0_3.0_1725228966522.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_nvidia_matryoshka_pipeline_en_5.5.0_3.0_1725228966522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_nvidia_matryoshka_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_nvidia_matryoshka_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_nvidia_matryoshka_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/rbhatia46/bge-base-financial-nvidia-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_horizon_europe_matryoshka_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_horizon_europe_matryoshka_en.md new file mode 100644 index 00000000000000..54dfa0c8025d9d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_horizon_europe_matryoshka_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_horizon_europe_matryoshka BGEEmbeddings from daniellgoncalves +author: John Snow Labs +name: bge_base_horizon_europe_matryoshka +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_horizon_europe_matryoshka` is a English model originally trained by daniellgoncalves. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_horizon_europe_matryoshka_en_5.4.2_3.0_1725199272744.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_horizon_europe_matryoshka_en_5.4.2_3.0_1725199272744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_horizon_europe_matryoshka","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_horizon_europe_matryoshka","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_horizon_europe_matryoshka| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|377.9 MB| + +## References + +https://huggingface.co/daniellgoncalves/bge-base-horizon-europe-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_horizon_europe_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_horizon_europe_matryoshka_pipeline_en.md new file mode 100644 index 00000000000000..c7a447bcec84cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_horizon_europe_matryoshka_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_horizon_europe_matryoshka_pipeline pipeline BGEEmbeddings from daniellgoncalves +author: John Snow Labs +name: bge_base_horizon_europe_matryoshka_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_horizon_europe_matryoshka_pipeline` is a English model originally trained by daniellgoncalves. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_horizon_europe_matryoshka_pipeline_en_5.4.2_3.0_1725199305304.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_horizon_europe_matryoshka_pipeline_en_5.4.2_3.0_1725199305304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_horizon_europe_matryoshka_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_horizon_europe_matryoshka_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_horizon_europe_matryoshka_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|377.9 MB| + +## References + +https://huggingface.co/daniellgoncalves/bge-base-horizon-europe-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_mbpp_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_mbpp_en.md new file mode 100644 index 00000000000000..a2795683e00658 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_mbpp_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_mbpp BGEEmbeddings from Nutanix +author: John Snow Labs +name: bge_base_mbpp +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_mbpp` is a English model originally trained by Nutanix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_mbpp_en_5.4.2_3.0_1725198781684.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_mbpp_en_5.4.2_3.0_1725198781684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_mbpp","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_mbpp","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_mbpp| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|376.4 MB| + +## References + +https://huggingface.co/Nutanix/bge-base-mbpp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_mbpp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_mbpp_pipeline_en.md new file mode 100644 index 00000000000000..32dbd60a8e90a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_mbpp_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_mbpp_pipeline pipeline BGEEmbeddings from Nutanix +author: John Snow Labs +name: bge_base_mbpp_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_mbpp_pipeline` is a English model originally trained by Nutanix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_mbpp_pipeline_en_5.4.2_3.0_1725198815766.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_mbpp_pipeline_en_5.4.2_3.0_1725198815766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_mbpp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_mbpp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_mbpp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|376.4 MB| + +## References + +https://huggingface.co/Nutanix/bge-base-mbpp + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_patentmatch_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_patentmatch_en.md new file mode 100644 index 00000000000000..d6ad1ac576be70 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_patentmatch_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_patentmatch BGEEmbeddings from bhlim +author: John Snow Labs +name: bge_base_patentmatch +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_patentmatch` is a English model originally trained by bhlim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_patentmatch_en_5.5.0_3.0_1725228754175.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_patentmatch_en_5.5.0_3.0_1725228754175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_patentmatch","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_patentmatch","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_patentmatch| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|391.3 MB| + +## References + +https://huggingface.co/bhlim/bge-base-patentmatch \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_patentmatch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_patentmatch_pipeline_en.md new file mode 100644 index 00000000000000..2556065b230409 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_patentmatch_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_patentmatch_pipeline pipeline BGEEmbeddings from bhlim +author: John Snow Labs +name: bge_base_patentmatch_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_patentmatch_pipeline` is a English model originally trained by bhlim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_patentmatch_pipeline_en_5.5.0_3.0_1725228781150.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_patentmatch_pipeline_en_5.5.0_3.0_1725228781150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_patentmatch_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_patentmatch_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_patentmatch_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|391.3 MB| + +## References + +https://huggingface.co/bhlim/bge-base-patentmatch + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_scidocs_dataset_10k_2k_e1_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_scidocs_dataset_10k_2k_e1_en.md new file mode 100644 index 00000000000000..a7f1678e66f9a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_scidocs_dataset_10k_2k_e1_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_scidocs_dataset_10k_2k_e1 BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_scidocs_dataset_10k_2k_e1 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_scidocs_dataset_10k_2k_e1` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_scidocs_dataset_10k_2k_e1_en_5.5.0_3.0_1725229369405.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_scidocs_dataset_10k_2k_e1_en_5.5.0_3.0_1725229369405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_scidocs_dataset_10k_2k_e1","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_scidocs_dataset_10k_2k_e1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_scidocs_dataset_10k_2k_e1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-scidocs-dataset-10k-2k-e1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_scidocs_dataset_10k_2k_e1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_scidocs_dataset_10k_2k_e1_pipeline_en.md new file mode 100644 index 00000000000000..b4ab5eb0972be5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_scidocs_dataset_10k_2k_e1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_scidocs_dataset_10k_2k_e1_pipeline pipeline BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_scidocs_dataset_10k_2k_e1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_scidocs_dataset_10k_2k_e1_pipeline` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_scidocs_dataset_10k_2k_e1_pipeline_en_5.5.0_3.0_1725229394839.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_scidocs_dataset_10k_2k_e1_pipeline_en_5.5.0_3.0_1725229394839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_scidocs_dataset_10k_2k_e1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_scidocs_dataset_10k_2k_e1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_scidocs_dataset_10k_2k_e1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-scidocs-dataset-10k-2k-e1 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_securiti_dataset_1_v18_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_securiti_dataset_1_v18_en.md new file mode 100644 index 00000000000000..4a1a99be538c8a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_securiti_dataset_1_v18_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v18 BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v18 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v18` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v18_en_5.4.2_3.0_1725199338126.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v18_en_5.4.2_3.0_1725199338126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v18","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v18","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v18| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|384.3 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v18 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_securiti_dataset_1_v18_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_securiti_dataset_1_v18_pipeline_en.md new file mode 100644 index 00000000000000..d596d42fdee84c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_securiti_dataset_1_v18_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v18_pipeline pipeline BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v18_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v18_pipeline` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v18_pipeline_en_5.4.2_3.0_1725199367956.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v18_pipeline_en_5.4.2_3.0_1725199367956.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_securiti_dataset_1_v18_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_securiti_dataset_1_v18_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v18_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|384.3 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v18 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_securiti_dataset_3_v23_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_securiti_dataset_3_v23_en.md new file mode 100644 index 00000000000000..65152360bebb0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_securiti_dataset_3_v23_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_securiti_dataset_3_v23 BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_3_v23 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_3_v23` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_3_v23_en_5.4.2_3.0_1725199224936.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_3_v23_en_5.4.2_3.0_1725199224936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_3_v23","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_3_v23","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_3_v23| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|384.8 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-3-v23 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_securiti_dataset_3_v23_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_securiti_dataset_3_v23_pipeline_en.md new file mode 100644 index 00000000000000..71354816fb4031 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_securiti_dataset_3_v23_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_securiti_dataset_3_v23_pipeline pipeline BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_3_v23_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_3_v23_pipeline` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_3_v23_pipeline_en_5.4.2_3.0_1725199257652.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_3_v23_pipeline_en_5.4.2_3.0_1725199257652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_securiti_dataset_3_v23_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_securiti_dataset_3_v23_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_3_v23_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|384.8 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-3-v23 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_swahili_matryoshka_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_swahili_matryoshka_en.md new file mode 100644 index 00000000000000..03422697b1e957 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_swahili_matryoshka_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_swahili_matryoshka BGEEmbeddings from sartifyllc +author: John Snow Labs +name: bge_base_swahili_matryoshka +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_swahili_matryoshka` is a English model originally trained by sartifyllc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_swahili_matryoshka_en_5.5.0_3.0_1725229088533.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_swahili_matryoshka_en_5.5.0_3.0_1725229088533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_swahili_matryoshka","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_swahili_matryoshka","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_swahili_matryoshka| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|397.1 MB| + +## References + +https://huggingface.co/sartifyllc/bge-base-swahili-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_swahili_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_swahili_matryoshka_pipeline_en.md new file mode 100644 index 00000000000000..50424f3f6d96f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_swahili_matryoshka_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_swahili_matryoshka_pipeline pipeline BGEEmbeddings from sartifyllc +author: John Snow Labs +name: bge_base_swahili_matryoshka_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_swahili_matryoshka_pipeline` is a English model originally trained by sartifyllc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_swahili_matryoshka_pipeline_en_5.5.0_3.0_1725229113325.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_swahili_matryoshka_pipeline_en_5.5.0_3.0_1725229113325.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_swahili_matryoshka_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_swahili_matryoshka_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_swahili_matryoshka_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.1 MB| + +## References + +https://huggingface.co/sartifyllc/bge-base-swahili-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_bislama_encoder_20_8_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_bislama_encoder_20_8_en.md new file mode 100644 index 00000000000000..ea312d66b3ae99 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_bislama_encoder_20_8_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_bislama_encoder_20_8 BGEEmbeddings from quangtqv +author: John Snow Labs +name: bge_bislama_encoder_20_8 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_bislama_encoder_20_8` is a English model originally trained by quangtqv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_bislama_encoder_20_8_en_5.5.0_3.0_1725228333831.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_bislama_encoder_20_8_en_5.5.0_3.0_1725228333831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_bislama_encoder_20_8","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_bislama_encoder_20_8","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_bislama_encoder_20_8| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|389.5 MB| + +## References + +https://huggingface.co/quangtqv/bge_bi_encoder_20_8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_large_chinese_v1_5_ft_v4_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_large_chinese_v1_5_ft_v4_en.md new file mode 100644 index 00000000000000..8dd71cecaedcf4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_large_chinese_v1_5_ft_v4_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_large_chinese_v1_5_ft_v4 BGEEmbeddings from stevenluo +author: John Snow Labs +name: bge_large_chinese_v1_5_ft_v4 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_chinese_v1_5_ft_v4` is a English model originally trained by stevenluo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_chinese_v1_5_ft_v4_en_5.4.2_3.0_1725198728223.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_chinese_v1_5_ft_v4_en_5.4.2_3.0_1725198728223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_large_chinese_v1_5_ft_v4","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_large_chinese_v1_5_ft_v4","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_chinese_v1_5_ft_v4| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/stevenluo/bge-large-zh-v1.5-ft-v4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_large_chinese_v1_5_ft_v4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_large_chinese_v1_5_ft_v4_pipeline_en.md new file mode 100644 index 00000000000000..b1d91a9a9a4d27 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_large_chinese_v1_5_ft_v4_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_large_chinese_v1_5_ft_v4_pipeline pipeline BGEEmbeddings from stevenluo +author: John Snow Labs +name: bge_large_chinese_v1_5_ft_v4_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_chinese_v1_5_ft_v4_pipeline` is a English model originally trained by stevenluo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_chinese_v1_5_ft_v4_pipeline_en_5.4.2_3.0_1725198804167.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_chinese_v1_5_ft_v4_pipeline_en_5.4.2_3.0_1725198804167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_large_chinese_v1_5_ft_v4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_large_chinese_v1_5_ft_v4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_chinese_v1_5_ft_v4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/stevenluo/bge-large-zh-v1.5-ft-v4 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_mnli_anli_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_mnli_anli_en.md new file mode 100644 index 00000000000000..908ccf79669b44 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_mnli_anli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bge_large_english_mnli_anli BertForZeroShotClassification from mjwong +author: John Snow Labs +name: bge_large_english_mnli_anli +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_english_mnli_anli` is a English model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_english_mnli_anli_en_5.4.2_3.0_1725208278809.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_english_mnli_anli_en_5.4.2_3.0_1725208278809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("bge_large_english_mnli_anli","en") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("bge_large_english_mnli_anli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_english_mnli_anli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/mjwong/bge-large-en-mnli-anli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_mnli_anli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_mnli_anli_pipeline_en.md new file mode 100644 index 00000000000000..1c810e6d558018 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_mnli_anli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bge_large_english_mnli_anli_pipeline pipeline BertForZeroShotClassification from mjwong +author: John Snow Labs +name: bge_large_english_mnli_anli_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_english_mnli_anli_pipeline` is a English model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_english_mnli_anli_pipeline_en_5.4.2_3.0_1725208351567.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_english_mnli_anli_pipeline_en_5.4.2_3.0_1725208351567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_large_english_mnli_anli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_large_english_mnli_anli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_english_mnli_anli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/mjwong/bge-large-en-mnli-anli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_v1_5_cosentloss_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_v1_5_cosentloss_en.md new file mode 100644 index 00000000000000..1b1c750420562b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_v1_5_cosentloss_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_large_english_v1_5_cosentloss BGEEmbeddings from Areeb-02 +author: John Snow Labs +name: bge_large_english_v1_5_cosentloss +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_english_v1_5_cosentloss` is a English model originally trained by Areeb-02. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_cosentloss_en_5.4.2_3.0_1725198444092.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_cosentloss_en_5.4.2_3.0_1725198444092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_large_english_v1_5_cosentloss","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_large_english_v1_5_cosentloss","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_english_v1_5_cosentloss| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Areeb-02/bge-large-en-v1.5-CosentLoss \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_v1_5_cosentloss_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_v1_5_cosentloss_pipeline_en.md new file mode 100644 index 00000000000000..e7ad23920b7ede --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_v1_5_cosentloss_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_large_english_v1_5_cosentloss_pipeline pipeline BGEEmbeddings from Areeb-02 +author: John Snow Labs +name: bge_large_english_v1_5_cosentloss_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_english_v1_5_cosentloss_pipeline` is a English model originally trained by Areeb-02. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_cosentloss_pipeline_en_5.4.2_3.0_1725198524178.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_cosentloss_pipeline_en_5.4.2_3.0_1725198524178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_large_english_v1_5_cosentloss_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_large_english_v1_5_cosentloss_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_english_v1_5_cosentloss_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Areeb-02/bge-large-en-v1.5-CosentLoss + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_v1_5_hpc_gpt_fine_tuned_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_v1_5_hpc_gpt_fine_tuned_en.md new file mode 100644 index 00000000000000..4abaedd3cce834 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_v1_5_hpc_gpt_fine_tuned_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_large_english_v1_5_hpc_gpt_fine_tuned BGEEmbeddings from izayashiro +author: John Snow Labs +name: bge_large_english_v1_5_hpc_gpt_fine_tuned +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_english_v1_5_hpc_gpt_fine_tuned` is a English model originally trained by izayashiro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_hpc_gpt_fine_tuned_en_5.5.0_3.0_1725229470850.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_hpc_gpt_fine_tuned_en_5.5.0_3.0_1725229470850.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_large_english_v1_5_hpc_gpt_fine_tuned","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_large_english_v1_5_hpc_gpt_fine_tuned","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_english_v1_5_hpc_gpt_fine_tuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/izayashiro/bge-large-en-v1.5-hpc-gpt-fine-tuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_v1_5_hpc_gpt_fine_tuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_v1_5_hpc_gpt_fine_tuned_pipeline_en.md new file mode 100644 index 00000000000000..4342bffa55af71 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_large_english_v1_5_hpc_gpt_fine_tuned_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_large_english_v1_5_hpc_gpt_fine_tuned_pipeline pipeline BGEEmbeddings from izayashiro +author: John Snow Labs +name: bge_large_english_v1_5_hpc_gpt_fine_tuned_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_english_v1_5_hpc_gpt_fine_tuned_pipeline` is a English model originally trained by izayashiro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_hpc_gpt_fine_tuned_pipeline_en_5.5.0_3.0_1725229548175.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_hpc_gpt_fine_tuned_pipeline_en_5.5.0_3.0_1725229548175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_large_english_v1_5_hpc_gpt_fine_tuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_large_english_v1_5_hpc_gpt_fine_tuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_english_v1_5_hpc_gpt_fine_tuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/izayashiro/bge-large-en-v1.5-hpc-gpt-fine-tuned + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_large_finetuned_400_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_large_finetuned_400_en.md new file mode 100644 index 00000000000000..7b01c3afb66d2b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_large_finetuned_400_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_large_finetuned_400 BGEEmbeddings from Nishit28 +author: John Snow Labs +name: bge_large_finetuned_400 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_finetuned_400` is a English model originally trained by Nishit28. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_finetuned_400_en_5.4.2_3.0_1725199556252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_finetuned_400_en_5.4.2_3.0_1725199556252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_large_finetuned_400","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_large_finetuned_400","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_finetuned_400| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Nishit28/bge-large-finetuned-400 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_large_finetuned_400_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_large_finetuned_400_pipeline_en.md new file mode 100644 index 00000000000000..f87d9cc730b38f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_large_finetuned_400_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_large_finetuned_400_pipeline pipeline BGEEmbeddings from Nishit28 +author: John Snow Labs +name: bge_large_finetuned_400_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_finetuned_400_pipeline` is a English model originally trained by Nishit28. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_finetuned_400_pipeline_en_5.4.2_3.0_1725199637639.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_finetuned_400_pipeline_en_5.4.2_3.0_1725199637639.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_large_finetuned_400_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_large_finetuned_400_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_finetuned_400_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Nishit28/bge-large-finetuned-400 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_small_bioasq_1epochs_batch32_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_small_bioasq_1epochs_batch32_en.md new file mode 100644 index 00000000000000..6d1f0b904f6b6e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_small_bioasq_1epochs_batch32_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_small_bioasq_1epochs_batch32 BGEEmbeddings from juanpablomesa +author: John Snow Labs +name: bge_small_bioasq_1epochs_batch32 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_bioasq_1epochs_batch32` is a English model originally trained by juanpablomesa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epochs_batch32_en_5.5.0_3.0_1725228819311.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epochs_batch32_en_5.5.0_3.0_1725228819311.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_small_bioasq_1epochs_batch32","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_small_bioasq_1epochs_batch32","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_bioasq_1epochs_batch32| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|115.7 MB| + +## References + +https://huggingface.co/juanpablomesa/bge-small-bioasq-1epochs-batch32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_small_bioasq_1epochs_batch32_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_small_bioasq_1epochs_batch32_pipeline_en.md new file mode 100644 index 00000000000000..1cf829f4573da2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_small_bioasq_1epochs_batch32_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_small_bioasq_1epochs_batch32_pipeline pipeline BGEEmbeddings from juanpablomesa +author: John Snow Labs +name: bge_small_bioasq_1epochs_batch32_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_bioasq_1epochs_batch32_pipeline` is a English model originally trained by juanpablomesa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epochs_batch32_pipeline_en_5.5.0_3.0_1725228828915.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epochs_batch32_pipeline_en_5.5.0_3.0_1725228828915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_small_bioasq_1epochs_batch32_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_small_bioasq_1epochs_batch32_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_bioasq_1epochs_batch32_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|115.7 MB| + +## References + +https://huggingface.co/juanpablomesa/bge-small-bioasq-1epochs-batch32 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_dcpr_tuned_sanyamjain0315_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_dcpr_tuned_sanyamjain0315_en.md new file mode 100644 index 00000000000000..264b9e95ae9566 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_dcpr_tuned_sanyamjain0315_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_small_english_dcpr_tuned_sanyamjain0315 BGEEmbeddings from sanyamjain0315 +author: John Snow Labs +name: bge_small_english_dcpr_tuned_sanyamjain0315 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_dcpr_tuned_sanyamjain0315` is a English model originally trained by sanyamjain0315. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_dcpr_tuned_sanyamjain0315_en_5.4.2_3.0_1725199109670.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_dcpr_tuned_sanyamjain0315_en_5.4.2_3.0_1725199109670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_small_english_dcpr_tuned_sanyamjain0315","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_small_english_dcpr_tuned_sanyamjain0315","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_dcpr_tuned_sanyamjain0315| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|115.2 MB| + +## References + +https://huggingface.co/sanyamjain0315/bge-small-en-dcpr-tuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_dcpr_tuned_sanyamjain0315_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_dcpr_tuned_sanyamjain0315_pipeline_en.md new file mode 100644 index 00000000000000..7c1914197f6250 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_dcpr_tuned_sanyamjain0315_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_small_english_dcpr_tuned_sanyamjain0315_pipeline pipeline BGEEmbeddings from sanyamjain0315 +author: John Snow Labs +name: bge_small_english_dcpr_tuned_sanyamjain0315_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_dcpr_tuned_sanyamjain0315_pipeline` is a English model originally trained by sanyamjain0315. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_dcpr_tuned_sanyamjain0315_pipeline_en_5.4.2_3.0_1725199118367.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_dcpr_tuned_sanyamjain0315_pipeline_en_5.4.2_3.0_1725199118367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_small_english_dcpr_tuned_sanyamjain0315_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_small_english_dcpr_tuned_sanyamjain0315_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_dcpr_tuned_sanyamjain0315_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|115.2 MB| + +## References + +https://huggingface.co/sanyamjain0315/bge-small-en-dcpr-tuned + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_multiplrrankingloss_tax_dataset_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_multiplrrankingloss_tax_dataset_en.md new file mode 100644 index 00000000000000..5d44095a468696 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_multiplrrankingloss_tax_dataset_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_small_english_multiplrrankingloss_tax_dataset BGEEmbeddings from Areeb-02 +author: John Snow Labs +name: bge_small_english_multiplrrankingloss_tax_dataset +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_multiplrrankingloss_tax_dataset` is a English model originally trained by Areeb-02. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_multiplrrankingloss_tax_dataset_en_5.5.0_3.0_1725229370204.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_multiplrrankingloss_tax_dataset_en_5.5.0_3.0_1725229370204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_small_english_multiplrrankingloss_tax_dataset","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_small_english_multiplrrankingloss_tax_dataset","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_multiplrrankingloss_tax_dataset| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|111.7 MB| + +## References + +https://huggingface.co/Areeb-02/bge-small-en-MultiplrRankingLoss-Tax-dataset \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_multiplrrankingloss_tax_dataset_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_multiplrrankingloss_tax_dataset_pipeline_en.md new file mode 100644 index 00000000000000..0a53c38d367d8d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_multiplrrankingloss_tax_dataset_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_small_english_multiplrrankingloss_tax_dataset_pipeline pipeline BGEEmbeddings from Areeb-02 +author: John Snow Labs +name: bge_small_english_multiplrrankingloss_tax_dataset_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_multiplrrankingloss_tax_dataset_pipeline` is a English model originally trained by Areeb-02. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_multiplrrankingloss_tax_dataset_pipeline_en_5.5.0_3.0_1725229385646.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_multiplrrankingloss_tax_dataset_pipeline_en_5.5.0_3.0_1725229385646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_small_english_multiplrrankingloss_tax_dataset_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_small_english_multiplrrankingloss_tax_dataset_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_multiplrrankingloss_tax_dataset_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|111.7 MB| + +## References + +https://huggingface.co/Areeb-02/bge-small-en-MultiplrRankingLoss-Tax-dataset + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_ol_science_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_ol_science_en.md new file mode 100644 index 00000000000000..d01cccb1ce637f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_ol_science_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_small_english_ol_science BGEEmbeddings from Ganidu +author: John Snow Labs +name: bge_small_english_ol_science +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_ol_science` is a English model originally trained by Ganidu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_ol_science_en_5.5.0_3.0_1725229309041.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_ol_science_en_5.5.0_3.0_1725229309041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_small_english_ol_science","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_small_english_ol_science","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_ol_science| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|115.7 MB| + +## References + +https://huggingface.co/Ganidu/bge-small-en-ol-science \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_ol_science_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_ol_science_pipeline_en.md new file mode 100644 index 00000000000000..c9ccaed16cd085 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_ol_science_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_small_english_ol_science_pipeline pipeline BGEEmbeddings from Ganidu +author: John Snow Labs +name: bge_small_english_ol_science_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_ol_science_pipeline` is a English model originally trained by Ganidu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_ol_science_pipeline_en_5.5.0_3.0_1725229318440.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_ol_science_pipeline_en_5.5.0_3.0_1725229318440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_small_english_ol_science_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_small_english_ol_science_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_ol_science_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|115.7 MB| + +## References + +https://huggingface.co/Ganidu/bge-small-en-ol-science + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_v1_5_ft_orc_0806_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_v1_5_ft_orc_0806_en.md new file mode 100644 index 00000000000000..0104f81ea39108 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_v1_5_ft_orc_0806_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_small_english_v1_5_ft_orc_0806 BGEEmbeddings from magnifi +author: John Snow Labs +name: bge_small_english_v1_5_ft_orc_0806 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_ft_orc_0806` is a English model originally trained by magnifi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_ft_orc_0806_en_5.4.2_3.0_1725199633915.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_ft_orc_0806_en_5.4.2_3.0_1725199633915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_ft_orc_0806","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_ft_orc_0806","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_v1_5_ft_orc_0806| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|110.2 MB| + +## References + +https://huggingface.co/magnifi/bge-small-en-v1.5-ft-orc-0806 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_v1_5_ft_orc_0806_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_v1_5_ft_orc_0806_pipeline_en.md new file mode 100644 index 00000000000000..2f9e5be1838ed7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_small_english_v1_5_ft_orc_0806_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_small_english_v1_5_ft_orc_0806_pipeline pipeline BGEEmbeddings from magnifi +author: John Snow Labs +name: bge_small_english_v1_5_ft_orc_0806_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_ft_orc_0806_pipeline` is a English model originally trained by magnifi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_ft_orc_0806_pipeline_en_5.4.2_3.0_1725199648738.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_ft_orc_0806_pipeline_en_5.4.2_3.0_1725199648738.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_small_english_v1_5_ft_orc_0806_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_small_english_v1_5_ft_orc_0806_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_v1_5_ft_orc_0806_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|110.2 MB| + +## References + +https://huggingface.co/magnifi/bge-small-en-v1.5-ft-orc-0806 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_small_financial_matryoshka_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_small_financial_matryoshka_en.md new file mode 100644 index 00000000000000..b58a10f4928e50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_small_financial_matryoshka_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_small_financial_matryoshka BGEEmbeddings from haophancs +author: John Snow Labs +name: bge_small_financial_matryoshka +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_financial_matryoshka` is a English model originally trained by haophancs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_financial_matryoshka_en_5.5.0_3.0_1725229359253.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_financial_matryoshka_en_5.5.0_3.0_1725229359253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_small_financial_matryoshka","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_small_financial_matryoshka","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_financial_matryoshka| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|114.9 MB| + +## References + +https://huggingface.co/haophancs/bge-small-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_small_financial_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_small_financial_matryoshka_pipeline_en.md new file mode 100644 index 00000000000000..954e202b03c8c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bge_small_financial_matryoshka_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_small_financial_matryoshka_pipeline pipeline BGEEmbeddings from haophancs +author: John Snow Labs +name: bge_small_financial_matryoshka_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_financial_matryoshka_pipeline` is a English model originally trained by haophancs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_financial_matryoshka_pipeline_en_5.5.0_3.0_1725229369188.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_financial_matryoshka_pipeline_en_5.5.0_3.0_1725229369188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_small_financial_matryoshka_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_small_financial_matryoshka_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_financial_matryoshka_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|115.0 MB| + +## References + +https://huggingface.co/haophancs/bge-small-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bilingualchildemo_en.md b/docs/_posts/ahmedlone127/2024-09-01-bilingualchildemo_en.md new file mode 100644 index 00000000000000..5170e5d312a52e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bilingualchildemo_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bilingualchildemo XlmRoBertaForSequenceClassification from nanaaaa +author: John Snow Labs +name: bilingualchildemo +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bilingualchildemo` is a English model originally trained by nanaaaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bilingualchildemo_en_5.4.2_3.0_1725169769601.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bilingualchildemo_en_5.4.2_3.0_1725169769601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("bilingualchildemo","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("bilingualchildemo", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bilingualchildemo| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|826.4 MB| + +## References + +https://huggingface.co/nanaaaa/BilingualChildEmo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bionlp13cg_clinicalbert_ner_en.md b/docs/_posts/ahmedlone127/2024-09-01-bionlp13cg_clinicalbert_ner_en.md new file mode 100644 index 00000000000000..607e461b995324 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bionlp13cg_clinicalbert_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bionlp13cg_clinicalbert_ner DistilBertForTokenClassification from judithrosell +author: John Snow Labs +name: bionlp13cg_clinicalbert_ner +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bionlp13cg_clinicalbert_ner` is a English model originally trained by judithrosell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bionlp13cg_clinicalbert_ner_en_5.4.2_3.0_1725160600304.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bionlp13cg_clinicalbert_ner_en_5.4.2_3.0_1725160600304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("bionlp13cg_clinicalbert_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("bionlp13cg_clinicalbert_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bionlp13cg_clinicalbert_ner| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|505.4 MB| + +## References + +https://huggingface.co/judithrosell/BioNLP13CG_ClinicalBERT_NER \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bionlp13cg_clinicalbert_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bionlp13cg_clinicalbert_ner_pipeline_en.md new file mode 100644 index 00000000000000..4b4c50bcbd96d5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bionlp13cg_clinicalbert_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bionlp13cg_clinicalbert_ner_pipeline pipeline DistilBertForTokenClassification from judithrosell +author: John Snow Labs +name: bionlp13cg_clinicalbert_ner_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bionlp13cg_clinicalbert_ner_pipeline` is a English model originally trained by judithrosell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bionlp13cg_clinicalbert_ner_pipeline_en_5.4.2_3.0_1725160630672.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bionlp13cg_clinicalbert_ner_pipeline_en_5.4.2_3.0_1725160630672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bionlp13cg_clinicalbert_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bionlp13cg_clinicalbert_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bionlp13cg_clinicalbert_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|505.5 MB| + +## References + +https://huggingface.co/judithrosell/BioNLP13CG_ClinicalBERT_NER + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bislama_all_bs192_hardneg_finetuned_webnlg2017_en.md b/docs/_posts/ahmedlone127/2024-09-01-bislama_all_bs192_hardneg_finetuned_webnlg2017_en.md new file mode 100644 index 00000000000000..fa6ddcb1aecc94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bislama_all_bs192_hardneg_finetuned_webnlg2017_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bislama_all_bs192_hardneg_finetuned_webnlg2017 MPNetEmbeddings from teven +author: John Snow Labs +name: bislama_all_bs192_hardneg_finetuned_webnlg2017 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bislama_all_bs192_hardneg_finetuned_webnlg2017` is a English model originally trained by teven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bislama_all_bs192_hardneg_finetuned_webnlg2017_en_5.5.0_3.0_1725225048775.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bislama_all_bs192_hardneg_finetuned_webnlg2017_en_5.5.0_3.0_1725225048775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("bislama_all_bs192_hardneg_finetuned_webnlg2017","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("bislama_all_bs192_hardneg_finetuned_webnlg2017","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bislama_all_bs192_hardneg_finetuned_webnlg2017| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/teven/bi_all_bs192_hardneg_finetuned_WebNLG2017 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-bislama_all_bs192_hardneg_finetuned_webnlg2017_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bislama_all_bs192_hardneg_finetuned_webnlg2017_pipeline_en.md new file mode 100644 index 00000000000000..5259fe0caf30d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-bislama_all_bs192_hardneg_finetuned_webnlg2017_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bislama_all_bs192_hardneg_finetuned_webnlg2017_pipeline pipeline MPNetEmbeddings from teven +author: John Snow Labs +name: bislama_all_bs192_hardneg_finetuned_webnlg2017_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bislama_all_bs192_hardneg_finetuned_webnlg2017_pipeline` is a English model originally trained by teven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bislama_all_bs192_hardneg_finetuned_webnlg2017_pipeline_en_5.5.0_3.0_1725225070598.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bislama_all_bs192_hardneg_finetuned_webnlg2017_pipeline_en_5.5.0_3.0_1725225070598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bislama_all_bs192_hardneg_finetuned_webnlg2017_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bislama_all_bs192_hardneg_finetuned_webnlg2017_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bislama_all_bs192_hardneg_finetuned_webnlg2017_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/teven/bi_all_bs192_hardneg_finetuned_WebNLG2017 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-brand_classification_20240820_model_distilbert_0_9847_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-brand_classification_20240820_model_distilbert_0_9847_pipeline_en.md new file mode 100644 index 00000000000000..a77dd63ba14af0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-brand_classification_20240820_model_distilbert_0_9847_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English brand_classification_20240820_model_distilbert_0_9847_pipeline pipeline DistilBertForSequenceClassification from jointriple +author: John Snow Labs +name: brand_classification_20240820_model_distilbert_0_9847_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brand_classification_20240820_model_distilbert_0_9847_pipeline` is a English model originally trained by jointriple. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brand_classification_20240820_model_distilbert_0_9847_pipeline_en_5.5.0_3.0_1725213585227.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brand_classification_20240820_model_distilbert_0_9847_pipeline_en_5.5.0_3.0_1725213585227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("brand_classification_20240820_model_distilbert_0_9847_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("brand_classification_20240820_model_distilbert_0_9847_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|brand_classification_20240820_model_distilbert_0_9847_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|253.0 MB| + +## References + +https://huggingface.co/jointriple/brand_classification_20240820_model_distilbert_0_9847 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_conll_model_kheyh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_conll_model_kheyh_pipeline_en.md new file mode 100644 index 00000000000000..a486b59e81e5d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_conll_model_kheyh_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_conll_model_kheyh_pipeline pipeline DistilBertForTokenClassification from KHEYH +author: John Snow Labs +name: burmese_awesome_conll_model_kheyh_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_conll_model_kheyh_pipeline` is a English model originally trained by KHEYH. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_conll_model_kheyh_pipeline_en_5.4.2_3.0_1725161011295.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_conll_model_kheyh_pipeline_en_5.4.2_3.0_1725161011295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_conll_model_kheyh_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_conll_model_kheyh_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_conll_model_kheyh_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/KHEYH/my_awesome_conll_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_pec_model3_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_pec_model3_en.md new file mode 100644 index 00000000000000..7f5c1d28c212bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_pec_model3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_pec_model3 DistilBertForTokenClassification from PaulBin +author: John Snow Labs +name: burmese_awesome_pec_model3 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_pec_model3` is a English model originally trained by PaulBin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_pec_model3_en_5.4.2_3.0_1725171504358.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_pec_model3_en_5.4.2_3.0_1725171504358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_pec_model3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_pec_model3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_pec_model3| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/PaulBin/my_awesome_PEC_model3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_qa_model_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_qa_model_en.md new file mode 100644 index 00000000000000..29690af029cbe4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_qa_model_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English burmese_awesome_qa_model CamemBertForQuestionAnswering from manonkrk +author: John Snow Labs +name: burmese_awesome_qa_model +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, camembert] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model` is a English model originally trained by manonkrk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_en_5.4.2_3.0_1725161868917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_en_5.4.2_3.0_1725161868917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = CamemBertForQuestionAnswering.pretrained("burmese_awesome_qa_model","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = CamemBertForQuestionAnswering.pretrained("burmese_awesome_qa_model", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_qa_model| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|253.5 MB| + +## References + +https://huggingface.co/manonkrk/my_awesome_qa_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_gaviolation_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_gaviolation_en.md new file mode 100644 index 00000000000000..afb6818cfd3085 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_gaviolation_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_wnut_gaviolation DistilBertForTokenClassification from gonzalezrostani +author: John Snow Labs +name: burmese_awesome_wnut_gaviolation +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_gaviolation` is a English model originally trained by gonzalezrostani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_gaviolation_en_5.4.2_3.0_1725170955210.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_gaviolation_en_5.4.2_3.0_1725170955210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_gaviolation","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_gaviolation", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_gaviolation| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/gonzalezrostani/my_awesome_wnut_GAviolation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_gaviolation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_gaviolation_pipeline_en.md new file mode 100644 index 00000000000000..a61d3cdc1f0fc6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_gaviolation_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_wnut_gaviolation_pipeline pipeline DistilBertForTokenClassification from gonzalezrostani +author: John Snow Labs +name: burmese_awesome_wnut_gaviolation_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_gaviolation_pipeline` is a English model originally trained by gonzalezrostani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_gaviolation_pipeline_en_5.4.2_3.0_1725170968218.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_gaviolation_pipeline_en_5.4.2_3.0_1725170968218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_wnut_gaviolation_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_wnut_gaviolation_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_gaviolation_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/gonzalezrostani/my_awesome_wnut_GAviolation + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_jhn_gonzalezrostani_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_jhn_gonzalezrostani_en.md new file mode 100644 index 00000000000000..8aea35666d17d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_jhn_gonzalezrostani_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_wnut_jhn_gonzalezrostani DistilBertForTokenClassification from gonzalezrostani +author: John Snow Labs +name: burmese_awesome_wnut_jhn_gonzalezrostani +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_jhn_gonzalezrostani` is a English model originally trained by gonzalezrostani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_jhn_gonzalezrostani_en_5.4.2_3.0_1725171496194.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_jhn_gonzalezrostani_en_5.4.2_3.0_1725171496194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_jhn_gonzalezrostani","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_jhn_gonzalezrostani", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_jhn_gonzalezrostani| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/gonzalezrostani/my_awesome_wnut_JHn \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_jpr_abegweit_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_jpr_abegweit_en.md new file mode 100644 index 00000000000000..305750fa8754fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_jpr_abegweit_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_wnut_jpr_abegweit DistilBertForTokenClassification from abegweit +author: John Snow Labs +name: burmese_awesome_wnut_jpr_abegweit +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_jpr_abegweit` is a English model originally trained by abegweit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_jpr_abegweit_en_5.4.2_3.0_1725170617745.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_jpr_abegweit_en_5.4.2_3.0_1725170617745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_jpr_abegweit","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_jpr_abegweit", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_jpr_abegweit| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/abegweit/my_awesome_wnut_JPR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_jpr_abegweit_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_jpr_abegweit_pipeline_en.md new file mode 100644 index 00000000000000..4fd59ee58f8cf8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_jpr_abegweit_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_wnut_jpr_abegweit_pipeline pipeline DistilBertForTokenClassification from abegweit +author: John Snow Labs +name: burmese_awesome_wnut_jpr_abegweit_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_jpr_abegweit_pipeline` is a English model originally trained by abegweit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_jpr_abegweit_pipeline_en_5.4.2_3.0_1725170634998.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_jpr_abegweit_pipeline_en_5.4.2_3.0_1725170634998.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_wnut_jpr_abegweit_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_wnut_jpr_abegweit_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_jpr_abegweit_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/abegweit/my_awesome_wnut_JPR + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_ck_0099_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_ck_0099_en.md new file mode 100644 index 00000000000000..05c63e3dbc9bad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_ck_0099_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_wnut_model_ck_0099 DistilBertForTokenClassification from ck-0099 +author: John Snow Labs +name: burmese_awesome_wnut_model_ck_0099 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_ck_0099` is a English model originally trained by ck-0099. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_ck_0099_en_5.4.2_3.0_1725161031648.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_ck_0099_en_5.4.2_3.0_1725161031648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_ck_0099","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_ck_0099", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_model_ck_0099| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/ck-0099/my_awesome_wnut_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_kolegas_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_kolegas_pipeline_en.md new file mode 100644 index 00000000000000..5a0bbd61ea2e5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_kolegas_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_wnut_model_kolegas_pipeline pipeline DistilBertForTokenClassification from kolegas +author: John Snow Labs +name: burmese_awesome_wnut_model_kolegas_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_kolegas_pipeline` is a English model originally trained by kolegas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_kolegas_pipeline_en_5.4.2_3.0_1725172402420.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_kolegas_pipeline_en_5.4.2_3.0_1725172402420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_wnut_model_kolegas_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_kolegas_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_model_kolegas_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/kolegas/my_awesome_wnut_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_sujit27_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_sujit27_en.md new file mode 100644 index 00000000000000..75f267be062c3c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_sujit27_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_wnut_model_sujit27 DistilBertForTokenClassification from sujit27 +author: John Snow Labs +name: burmese_awesome_wnut_model_sujit27 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_sujit27` is a English model originally trained by sujit27. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sujit27_en_5.4.2_3.0_1725171148629.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sujit27_en_5.4.2_3.0_1725171148629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_sujit27","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_sujit27", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_model_sujit27| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/sujit27/my_awesome_wnut_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_wool_peach_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_wool_peach_pipeline_en.md new file mode 100644 index 00000000000000..f013052dd6058f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_wool_peach_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_wnut_model_wool_peach_pipeline pipeline DistilBertForTokenClassification from Wool-Peach +author: John Snow Labs +name: burmese_awesome_wnut_model_wool_peach_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_wool_peach_pipeline` is a English model originally trained by Wool-Peach. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_wool_peach_pipeline_en_5.4.2_3.0_1725171722361.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_wool_peach_pipeline_en_5.4.2_3.0_1725171722361.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_wnut_model_wool_peach_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_wool_peach_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_model_wool_peach_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/Wool-Peach/my_awesome_wnut_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_yolkem_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_yolkem_pipeline_en.md new file mode 100644 index 00000000000000..1af9b5c1a2f4d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_model_yolkem_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_wnut_model_yolkem_pipeline pipeline DistilBertForTokenClassification from Yolkem +author: John Snow Labs +name: burmese_awesome_wnut_model_yolkem_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_yolkem_pipeline` is a English model originally trained by Yolkem. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_yolkem_pipeline_en_5.4.2_3.0_1725170859454.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_yolkem_pipeline_en_5.4.2_3.0_1725170859454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_wnut_model_yolkem_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_yolkem_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_model_yolkem_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/Yolkem/my_awesome_wnut_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_saneither_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_saneither_en.md new file mode 100644 index 00000000000000..14cad517e4efce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_saneither_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_wnut_saneither DistilBertForTokenClassification from gonzalezrostani +author: John Snow Labs +name: burmese_awesome_wnut_saneither +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_saneither` is a English model originally trained by gonzalezrostani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_saneither_en_5.4.2_3.0_1725161079273.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_saneither_en_5.4.2_3.0_1725161079273.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_saneither","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_saneither", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_saneither| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/gonzalezrostani/my_awesome_wnut_SAneither \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_them_all_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_them_all_pipeline_en.md new file mode 100644 index 00000000000000..b66ad2aa4bb9e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_awesome_wnut_them_all_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_wnut_them_all_pipeline pipeline DistilBertForTokenClassification from gonzalezrostani +author: John Snow Labs +name: burmese_awesome_wnut_them_all_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_them_all_pipeline` is a English model originally trained by gonzalezrostani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_them_all_pipeline_en_5.4.2_3.0_1725171956793.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_them_all_pipeline_en_5.4.2_3.0_1725171956793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_wnut_them_all_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_wnut_them_all_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_them_all_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/gonzalezrostani/my_awesome_wnut_Them_all + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_model_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_model_en.md new file mode 100644 index 00000000000000..cd70ac51e9872c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_model_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English burmese_model RoBertaForSequenceClassification from dadashzadeh +author: John Snow Labs +name: burmese_model +date: 2024-09-01 +tags: [roberta, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_model` is a English model originally trained by dadashzadeh. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_model_en_5.4.2_3.0_1725170735821.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_model_en_5.4.2_3.0_1725170735821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("burmese_model","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("burmese_model","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_model| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +References + +https://huggingface.co/dadashzadeh/my_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_ner_model_amrita06_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_ner_model_amrita06_pipeline_en.md new file mode 100644 index 00000000000000..9dde3e41740c25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_ner_model_amrita06_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_ner_model_amrita06_pipeline pipeline DistilBertForTokenClassification from amrita06 +author: John Snow Labs +name: burmese_ner_model_amrita06_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_model_amrita06_pipeline` is a English model originally trained by amrita06. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_ner_model_amrita06_pipeline_en_5.4.2_3.0_1725170867595.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_model_amrita06_pipeline_en_5.4.2_3.0_1725170867595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_ner_model_amrita06_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_ner_model_amrita06_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_ner_model_amrita06_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/amrita06/my_ner_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_wnut_model_yehoshuadiller_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_wnut_model_yehoshuadiller_en.md new file mode 100644 index 00000000000000..f18e691e3de4b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_wnut_model_yehoshuadiller_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_wnut_model_yehoshuadiller DistilBertForTokenClassification from yehoshuadiller +author: John Snow Labs +name: burmese_wnut_model_yehoshuadiller +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_wnut_model_yehoshuadiller` is a English model originally trained by yehoshuadiller. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_wnut_model_yehoshuadiller_en_5.4.2_3.0_1725172664635.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_wnut_model_yehoshuadiller_en_5.4.2_3.0_1725172664635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_wnut_model_yehoshuadiller","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_wnut_model_yehoshuadiller", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_wnut_model_yehoshuadiller| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/yehoshuadiller/my_wnut_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_wnut_model_yehoshuadiller_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_wnut_model_yehoshuadiller_pipeline_en.md new file mode 100644 index 00000000000000..0db5a2597c44f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_wnut_model_yehoshuadiller_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_wnut_model_yehoshuadiller_pipeline pipeline DistilBertForTokenClassification from yehoshuadiller +author: John Snow Labs +name: burmese_wnut_model_yehoshuadiller_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_wnut_model_yehoshuadiller_pipeline` is a English model originally trained by yehoshuadiller. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_wnut_model_yehoshuadiller_pipeline_en_5.4.2_3.0_1725172677393.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_wnut_model_yehoshuadiller_pipeline_en_5.4.2_3.0_1725172677393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_wnut_model_yehoshuadiller_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_wnut_model_yehoshuadiller_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_wnut_model_yehoshuadiller_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/yehoshuadiller/my_wnut_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_ws_extraction_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_ws_extraction_model_pipeline_en.md new file mode 100644 index 00000000000000..25c6ed7c537983 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_ws_extraction_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_ws_extraction_model_pipeline pipeline DistilBertForTokenClassification from manimaranpa07 +author: John Snow Labs +name: burmese_ws_extraction_model_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ws_extraction_model_pipeline` is a English model originally trained by manimaranpa07. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_ws_extraction_model_pipeline_en_5.4.2_3.0_1725171062642.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ws_extraction_model_pipeline_en_5.4.2_3.0_1725171062642.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_ws_extraction_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_ws_extraction_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_ws_extraction_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/manimaranpa07/my_Ws_extraction_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-camembert_base_token_classifier_wikiner_en.md b/docs/_posts/ahmedlone127/2024-09-01-camembert_base_token_classifier_wikiner_en.md new file mode 100644 index 00000000000000..703bf20a509713 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-camembert_base_token_classifier_wikiner_en.md @@ -0,0 +1,145 @@ +--- +layout: model +title: CamemBERT Token Classification Base - French WikiNER (camembert_base_token_classifier_wikiner) +author: John Snow Labs +name: camembert_base_token_classifier_wikiner +date: 2024-09-01 +tags: [open_source, camembert, token_classification, wikiner, ner, fr, french, en, openvino] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: openvino +annotator: CamemBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +CamemBertForTokenClassification can load CamemBERT Models with a token classification head on top (a linear layer on top of the hidden-states output) e.g. for Named-Entity-Recognition (NER) tasks. + +camembert_base_token_classifier_wikiner is a fine-tuned CamemBERT model that is ready to be used for Token Classification task such as Named Entity Recognition and it achieves state-of-the-art performance. + +We used TFCamembertForTokenClassification to train this model and used CamemBertForTokenClassification annotator in Spark NLP 🚀 for prediction at scale! This model has been trained to recognize four types of entities: +O, LOC, PER, MISC, and ORG. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_base_token_classifier_wikiner_en_5.4.2_3.0_1725216665652.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_base_token_classifier_wikiner_en_5.4.2_3.0_1725216665652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols(['document'])\ + .setOutputCol('token') + +tokenClassifier = CamemBertForTokenClassification.pretrained("camembert_base_token_classifier_wikiner", "en")\ + .setInputCols(["document", "token"])\ + .setOutputCol("ner")\ + .setCaseSensitive(True)\ + .setMaxSentenceLength(512) + +# since output column is IOB/IOB2 style, NerConverter can extract entities +ner_converter = NerConverter()\ + .setInputCols(['document', 'token', 'ner'])\ + .setOutputCol('entities') + +pipeline = Pipeline(stages=[ + document_assembler, + tokenizer, + tokenClassifier, + ner_converter +]) + +example = spark.createDataFrame([['I really liked that movie!']]).toDF("text") +result = pipeline.fit(example).transform(example) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = CamemBertForTokenClassification.pretrained("camembert_base_token_classifier_wikiner", "en") + .setInputCols("document", "token") + .setOutputCol("ner") + .setCaseSensitive(true) + .setMaxSentenceLength(512) + +// since output column is IOB/IOB2 style, NerConverter can extract entities +val ner_converter = NerConverter() + .setInputCols("document", "token", "ner") + .setOutputCol("entities") + +val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, tokenClassifier, ner_converter)) + +val example = Seq("I really liked that movie!").toDS.toDF("text") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.ner.camembert.base").predict("""I really liked that movie!""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_base_token_classifier_wikiner| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[token, document]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|411.6 MB| +|Case sensitive:|true| +|Max sentence length:|512| + +## References + +References + +[https://huggingface.co/datasets/Jean-Baptiste/wikiner_fr](https://huggingface.co/datasets/Jean-Baptiste/wikiner_fr) + +## Benchmarking + +```bash + +root: "{" +eval_loss ": 0.0396629199385643, " +eval_precision ": 0.9283267457180501, " +eval_recall ": 0.9337809780447939, " +eval_f1 ": 0.9310458739841875, " +eval_accuracy ": 0.9896610647939648, " +eval_runtime ": 204.7064, " +eval_samples_per_second ": 65.508, " +eval_steps_per_second ": 4.099, " +epoch ": 3.0}" +``` \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-camembert_bio_generalized_medkit_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-camembert_bio_generalized_medkit_pipeline_en.md new file mode 100644 index 00000000000000..31f11814b99c7b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-camembert_bio_generalized_medkit_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English camembert_bio_generalized_medkit_pipeline pipeline CamemBertForTokenClassification from medkit +author: John Snow Labs +name: camembert_bio_generalized_medkit_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_bio_generalized_medkit_pipeline` is a English model originally trained by medkit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_bio_generalized_medkit_pipeline_en_5.4.2_3.0_1725175831467.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_bio_generalized_medkit_pipeline_en_5.4.2_3.0_1725175831467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("camembert_bio_generalized_medkit_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("camembert_bio_generalized_medkit_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_bio_generalized_medkit_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.9 MB| + +## References + +https://huggingface.co/medkit/CamemBert-Bio-Generalized + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-camembert_bio_generalized_thibeb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-camembert_bio_generalized_thibeb_pipeline_en.md new file mode 100644 index 00000000000000..30db19468dfea4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-camembert_bio_generalized_thibeb_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English camembert_bio_generalized_thibeb_pipeline pipeline CamemBertForTokenClassification from Thibeb +author: John Snow Labs +name: camembert_bio_generalized_thibeb_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_bio_generalized_thibeb_pipeline` is a English model originally trained by Thibeb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_bio_generalized_thibeb_pipeline_en_5.4.2_3.0_1725175193945.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_bio_generalized_thibeb_pipeline_en_5.4.2_3.0_1725175193945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("camembert_bio_generalized_thibeb_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("camembert_bio_generalized_thibeb_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_bio_generalized_thibeb_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|413.0 MB| + +## References + +https://huggingface.co/Thibeb/CamemBert_bio_generalized + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-camembert_crossencoder_classification_large_mmarco_en.md b/docs/_posts/ahmedlone127/2024-09-01-camembert_crossencoder_classification_large_mmarco_en.md new file mode 100644 index 00000000000000..5669e2995f353a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-camembert_crossencoder_classification_large_mmarco_en.md @@ -0,0 +1,95 @@ +--- +layout: model +title: French CamemBertForSequenceClassification (from antoinelouis) +author: John Snow Labs +name: camembert_crossencoder_classification_large_mmarco +date: 2024-09-01 +tags: [sequence_classification, camembert, openvino, en, open_source] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: openvino +annotator: CamemBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +“ + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_crossencoder_classification_large_mmarco_en_5.5.0_3.0_1725208124975.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_crossencoder_classification_large_mmarco_en_5.5.0_3.0_1725208124975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() .setInputCol("text") .setOutputCol("document") + +tokenizer = Tokenizer() .setInputCols("document") .setOutputCol("token") + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("camembert_crossencoder_classification_large_mmarco","fr") .setInputCols(["document","token"]) .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("camembert_crossencoder_classification_large_mmarco","fr") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_crossencoder_classification_large_mmarco| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|411.0 MB| +|Case sensitive:|false| +|Max sentence length:|512| \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-caramelo_smile_2_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-01-caramelo_smile_2_pipeline_pt.md new file mode 100644 index 00000000000000..fdad5a30475ef5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-caramelo_smile_2_pipeline_pt.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Portuguese caramelo_smile_2_pipeline pipeline RoBertaForSequenceClassification from Adilmar +author: John Snow Labs +name: caramelo_smile_2_pipeline +date: 2024-09-01 +tags: [pt, open_source, pipeline, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`caramelo_smile_2_pipeline` is a Portuguese model originally trained by Adilmar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/caramelo_smile_2_pipeline_pt_5.5.0_3.0_1725212168763.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/caramelo_smile_2_pipeline_pt_5.5.0_3.0_1725212168763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("caramelo_smile_2_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("caramelo_smile_2_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|caramelo_smile_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|468.3 MB| + +## References + +https://huggingface.co/Adilmar/caramelo-smile-2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-caramelo_smile_2_pt.md b/docs/_posts/ahmedlone127/2024-09-01-caramelo_smile_2_pt.md new file mode 100644 index 00000000000000..acf36c5ce7ba96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-caramelo_smile_2_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese caramelo_smile_2 RoBertaForSequenceClassification from Adilmar +author: John Snow Labs +name: caramelo_smile_2 +date: 2024-09-01 +tags: [pt, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`caramelo_smile_2` is a Portuguese model originally trained by Adilmar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/caramelo_smile_2_pt_5.5.0_3.0_1725212138602.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/caramelo_smile_2_pt_5.5.0_3.0_1725212138602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("caramelo_smile_2","pt") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("caramelo_smile_2", "pt") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|caramelo_smile_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|468.3 MB| + +## References + +https://huggingface.co/Adilmar/caramelo-smile-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-cat_sayula_popoluca_french_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-cat_sayula_popoluca_french_3_pipeline_en.md new file mode 100644 index 00000000000000..26ff2a5077d1a0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-cat_sayula_popoluca_french_3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cat_sayula_popoluca_french_3_pipeline pipeline CamemBertForTokenClassification from homersimpson +author: John Snow Labs +name: cat_sayula_popoluca_french_3_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cat_sayula_popoluca_french_3_pipeline` is a English model originally trained by homersimpson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_french_3_pipeline_en_5.4.2_3.0_1725175530078.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_french_3_pipeline_en_5.4.2_3.0_1725175530078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cat_sayula_popoluca_french_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cat_sayula_popoluca_french_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cat_sayula_popoluca_french_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|393.1 MB| + +## References + +https://huggingface.co/homersimpson/cat-pos-fr-3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-categorization_model_abhishek107_en.md b/docs/_posts/ahmedlone127/2024-09-01-categorization_model_abhishek107_en.md new file mode 100644 index 00000000000000..f296ac7510eeab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-categorization_model_abhishek107_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English categorization_model_abhishek107 DistilBertForSequenceClassification from Abhishek107 +author: John Snow Labs +name: categorization_model_abhishek107 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`categorization_model_abhishek107` is a English model originally trained by Abhishek107. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/categorization_model_abhishek107_en_5.5.0_3.0_1725214080140.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/categorization_model_abhishek107_en_5.5.0_3.0_1725214080140.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("categorization_model_abhishek107","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("categorization_model_abhishek107", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|categorization_model_abhishek107| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Abhishek107/categorization_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-categorization_model_abhishek107_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-categorization_model_abhishek107_pipeline_en.md new file mode 100644 index 00000000000000..bcf7cf941da40c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-categorization_model_abhishek107_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English categorization_model_abhishek107_pipeline pipeline DistilBertForSequenceClassification from Abhishek107 +author: John Snow Labs +name: categorization_model_abhishek107_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`categorization_model_abhishek107_pipeline` is a English model originally trained by Abhishek107. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/categorization_model_abhishek107_pipeline_en_5.5.0_3.0_1725214099151.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/categorization_model_abhishek107_pipeline_en_5.5.0_3.0_1725214099151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("categorization_model_abhishek107_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("categorization_model_abhishek107_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|categorization_model_abhishek107_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Abhishek107/categorization_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-category_cleaning_imagefolder_en.md b/docs/_posts/ahmedlone127/2024-09-01-category_cleaning_imagefolder_en.md new file mode 100644 index 00000000000000..f8f334560ba544 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-category_cleaning_imagefolder_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English category_cleaning_imagefolder CLIPForZeroShotClassification from kpalczewski-displate +author: John Snow Labs +name: category_cleaning_imagefolder +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`category_cleaning_imagefolder` is a English model originally trained by kpalczewski-displate. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/category_cleaning_imagefolder_en_5.5.0_3.0_1725225826053.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/category_cleaning_imagefolder_en_5.5.0_3.0_1725225826053.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("category_cleaning_imagefolder","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("category_cleaning_imagefolder","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|category_cleaning_imagefolder| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/kpalczewski-displate/category_cleaning_imagefolder \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-category_cleaning_imagefolder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-category_cleaning_imagefolder_pipeline_en.md new file mode 100644 index 00000000000000..4b931ded9ee618 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-category_cleaning_imagefolder_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English category_cleaning_imagefolder_pipeline pipeline CLIPForZeroShotClassification from kpalczewski-displate +author: John Snow Labs +name: category_cleaning_imagefolder_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`category_cleaning_imagefolder_pipeline` is a English model originally trained by kpalczewski-displate. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/category_cleaning_imagefolder_pipeline_en_5.5.0_3.0_1725225857245.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/category_cleaning_imagefolder_pipeline_en_5.5.0_3.0_1725225857245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("category_cleaning_imagefolder_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("category_cleaning_imagefolder_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|category_cleaning_imagefolder_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/kpalczewski-displate/category_cleaning_imagefolder + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-charles_dickens_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-charles_dickens_classifier_pipeline_en.md new file mode 100644 index 00000000000000..c6540cd22d4761 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-charles_dickens_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English charles_dickens_classifier_pipeline pipeline DistilBertForSequenceClassification from GuillermoTBB +author: John Snow Labs +name: charles_dickens_classifier_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`charles_dickens_classifier_pipeline` is a English model originally trained by GuillermoTBB. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/charles_dickens_classifier_pipeline_en_5.5.0_3.0_1725214217551.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/charles_dickens_classifier_pipeline_en_5.5.0_3.0_1725214217551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("charles_dickens_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("charles_dickens_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|charles_dickens_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/GuillermoTBB/charles-dickens-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-chat_category_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-01-chat_category_classifier_en.md new file mode 100644 index 00000000000000..7023128cebe828 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-chat_category_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English chat_category_classifier DistilBertForSequenceClassification from Mominalix +author: John Snow Labs +name: chat_category_classifier +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chat_category_classifier` is a English model originally trained by Mominalix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chat_category_classifier_en_5.5.0_3.0_1725213563250.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chat_category_classifier_en_5.5.0_3.0_1725213563250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("chat_category_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("chat_category_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chat_category_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Mominalix/chat_category_classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-chat_category_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-chat_category_classifier_pipeline_en.md new file mode 100644 index 00000000000000..205d34a4242408 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-chat_category_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English chat_category_classifier_pipeline pipeline DistilBertForSequenceClassification from Mominalix +author: John Snow Labs +name: chat_category_classifier_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chat_category_classifier_pipeline` is a English model originally trained by Mominalix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chat_category_classifier_pipeline_en_5.5.0_3.0_1725213576914.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chat_category_classifier_pipeline_en_5.5.0_3.0_1725213576914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("chat_category_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("chat_category_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chat_category_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Mominalix/chat_category_classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-citation_intent_classification_roberta_en.md b/docs/_posts/ahmedlone127/2024-09-01-citation_intent_classification_roberta_en.md new file mode 100644 index 00000000000000..c4ee0774380c42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-citation_intent_classification_roberta_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English citation_intent_classification_roberta RoBertaForSequenceClassification from ltuzova +author: John Snow Labs +name: citation_intent_classification_roberta +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`citation_intent_classification_roberta` is a English model originally trained by ltuzova. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/citation_intent_classification_roberta_en_5.5.0_3.0_1725211862673.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/citation_intent_classification_roberta_en_5.5.0_3.0_1725211862673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("citation_intent_classification_roberta","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("citation_intent_classification_roberta", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|citation_intent_classification_roberta| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|435.8 MB| + +## References + +https://huggingface.co/ltuzova/citation_intent_classification_roberta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-citation_intent_classification_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-citation_intent_classification_roberta_pipeline_en.md new file mode 100644 index 00000000000000..d70e6fea39ba9e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-citation_intent_classification_roberta_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English citation_intent_classification_roberta_pipeline pipeline RoBertaForSequenceClassification from ltuzova +author: John Snow Labs +name: citation_intent_classification_roberta_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`citation_intent_classification_roberta_pipeline` is a English model originally trained by ltuzova. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/citation_intent_classification_roberta_pipeline_en_5.5.0_3.0_1725211892319.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/citation_intent_classification_roberta_pipeline_en_5.5.0_3.0_1725211892319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("citation_intent_classification_roberta_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("citation_intent_classification_roberta_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|citation_intent_classification_roberta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|435.8 MB| + +## References + +https://huggingface.co/ltuzova/citation_intent_classification_roberta + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-classifier__generated_data_only__observationsdetection_albert_en.md b/docs/_posts/ahmedlone127/2024-09-01-classifier__generated_data_only__observationsdetection_albert_en.md new file mode 100644 index 00000000000000..85e1f734d91647 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-classifier__generated_data_only__observationsdetection_albert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English classifier__generated_data_only__observationsdetection_albert AlbertForSequenceClassification from yevhenkost +author: John Snow Labs +name: classifier__generated_data_only__observationsdetection_albert +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classifier__generated_data_only__observationsdetection_albert` is a English model originally trained by yevhenkost. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classifier__generated_data_only__observationsdetection_albert_en_5.4.2_3.0_1725188312286.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classifier__generated_data_only__observationsdetection_albert_en_5.4.2_3.0_1725188312286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("classifier__generated_data_only__observationsdetection_albert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("classifier__generated_data_only__observationsdetection_albert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|classifier__generated_data_only__observationsdetection_albert| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/yevhenkost/classifier__generated_data_only__observationsdetection_albert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-classifier__generated_data_only__observationsdetection_albert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-classifier__generated_data_only__observationsdetection_albert_pipeline_en.md new file mode 100644 index 00000000000000..385f53f7b67303 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-classifier__generated_data_only__observationsdetection_albert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English classifier__generated_data_only__observationsdetection_albert_pipeline pipeline AlbertForSequenceClassification from yevhenkost +author: John Snow Labs +name: classifier__generated_data_only__observationsdetection_albert_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classifier__generated_data_only__observationsdetection_albert_pipeline` is a English model originally trained by yevhenkost. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classifier__generated_data_only__observationsdetection_albert_pipeline_en_5.4.2_3.0_1725188314704.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classifier__generated_data_only__observationsdetection_albert_pipeline_en_5.4.2_3.0_1725188314704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("classifier__generated_data_only__observationsdetection_albert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("classifier__generated_data_only__observationsdetection_albert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|classifier__generated_data_only__observationsdetection_albert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/yevhenkost/classifier__generated_data_only__observationsdetection_albert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-climate_fact_checker_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-climate_fact_checker_pipeline_en.md new file mode 100644 index 00000000000000..1145ccc3010e4f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-climate_fact_checker_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English climate_fact_checker_pipeline pipeline DistilBertForSequenceClassification from fzanartu +author: John Snow Labs +name: climate_fact_checker_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`climate_fact_checker_pipeline` is a English model originally trained by fzanartu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/climate_fact_checker_pipeline_en_5.5.0_3.0_1725213874176.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/climate_fact_checker_pipeline_en_5.5.0_3.0_1725213874176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("climate_fact_checker_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("climate_fact_checker_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|climate_fact_checker_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/fzanartu/climate-fact-checker + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clinical_sentence_transformers_mpnet_base_v2_en.md b/docs/_posts/ahmedlone127/2024-09-01-clinical_sentence_transformers_mpnet_base_v2_en.md new file mode 100644 index 00000000000000..03080bb6ed1ba1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clinical_sentence_transformers_mpnet_base_v2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English clinical_sentence_transformers_mpnet_base_v2 MPNetEmbeddings from Shobhank-iiitdwd +author: John Snow Labs +name: clinical_sentence_transformers_mpnet_base_v2 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinical_sentence_transformers_mpnet_base_v2` is a English model originally trained by Shobhank-iiitdwd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinical_sentence_transformers_mpnet_base_v2_en_5.5.0_3.0_1725224996324.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinical_sentence_transformers_mpnet_base_v2_en_5.5.0_3.0_1725224996324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("clinical_sentence_transformers_mpnet_base_v2","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("clinical_sentence_transformers_mpnet_base_v2","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clinical_sentence_transformers_mpnet_base_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/Shobhank-iiitdwd/Clinical_sentence_transformers_mpnet_base_v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clinical_sentence_transformers_mpnet_base_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clinical_sentence_transformers_mpnet_base_v2_pipeline_en.md new file mode 100644 index 00000000000000..25c8472360dd25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clinical_sentence_transformers_mpnet_base_v2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clinical_sentence_transformers_mpnet_base_v2_pipeline pipeline MPNetEmbeddings from Shobhank-iiitdwd +author: John Snow Labs +name: clinical_sentence_transformers_mpnet_base_v2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinical_sentence_transformers_mpnet_base_v2_pipeline` is a English model originally trained by Shobhank-iiitdwd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinical_sentence_transformers_mpnet_base_v2_pipeline_en_5.5.0_3.0_1725225018571.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinical_sentence_transformers_mpnet_base_v2_pipeline_en_5.5.0_3.0_1725225018571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clinical_sentence_transformers_mpnet_base_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clinical_sentence_transformers_mpnet_base_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clinical_sentence_transformers_mpnet_base_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/Shobhank-iiitdwd/Clinical_sentence_transformers_mpnet_base_v2 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clinicalbertprqab_280_992_czech_en.md b/docs/_posts/ahmedlone127/2024-09-01-clinicalbertprqab_280_992_czech_en.md new file mode 100644 index 00000000000000..5e1a5b8cfaaaaf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clinicalbertprqab_280_992_czech_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English clinicalbertprqab_280_992_czech BertForQuestionAnswering from lanzv +author: John Snow Labs +name: clinicalbertprqab_280_992_czech +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbertprqab_280_992_czech` is a English model originally trained by lanzv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbertprqab_280_992_czech_en_5.5.0_3.0_1725215701196.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbertprqab_280_992_czech_en_5.5.0_3.0_1725215701196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("clinicalbertprqab_280_992_czech","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("clinicalbertprqab_280_992_czech", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clinicalbertprqab_280_992_czech| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/lanzv/ClinicalBERTPRQAB_280_992_CS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clinicalbertprqab_280_992_czech_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clinicalbertprqab_280_992_czech_pipeline_en.md new file mode 100644 index 00000000000000..6f1652353ccd8b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clinicalbertprqab_280_992_czech_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clinicalbertprqab_280_992_czech_pipeline pipeline BertForQuestionAnswering from lanzv +author: John Snow Labs +name: clinicalbertprqab_280_992_czech_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbertprqab_280_992_czech_pipeline` is a English model originally trained by lanzv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbertprqab_280_992_czech_pipeline_en_5.5.0_3.0_1725215736365.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbertprqab_280_992_czech_pipeline_en_5.5.0_3.0_1725215736365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clinicalbertprqab_280_992_czech_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clinicalbertprqab_280_992_czech_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clinicalbertprqab_280_992_czech_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/lanzv/ClinicalBERTPRQAB_280_992_CS + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_base_patch16_supervised_mulitilingual_1920_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_base_patch16_supervised_mulitilingual_1920_en.md new file mode 100644 index 00000000000000..8d73b1098e6f16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_base_patch16_supervised_mulitilingual_1920_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_base_patch16_supervised_mulitilingual_1920 CLIPForZeroShotClassification from gowitheflowlab +author: John Snow Labs +name: clip_base_patch16_supervised_mulitilingual_1920 +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_base_patch16_supervised_mulitilingual_1920` is a English model originally trained by gowitheflowlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_1920_en_5.5.0_3.0_1725226691863.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_1920_en_5.5.0_3.0_1725226691863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_base_patch16_supervised_mulitilingual_1920","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_base_patch16_supervised_mulitilingual_1920","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_base_patch16_supervised_mulitilingual_1920| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|509.7 MB| + +## References + +https://huggingface.co/gowitheflowlab/clip-base-patch16-supervised-mulitilingual-1920 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_base_patch16_supervised_mulitilingual_1920_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_base_patch16_supervised_mulitilingual_1920_pipeline_en.md new file mode 100644 index 00000000000000..b5d9c3037ec178 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_base_patch16_supervised_mulitilingual_1920_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_base_patch16_supervised_mulitilingual_1920_pipeline pipeline CLIPForZeroShotClassification from gowitheflowlab +author: John Snow Labs +name: clip_base_patch16_supervised_mulitilingual_1920_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_base_patch16_supervised_mulitilingual_1920_pipeline` is a English model originally trained by gowitheflowlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_1920_pipeline_en_5.5.0_3.0_1725226741670.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_1920_pipeline_en_5.5.0_3.0_1725226741670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_base_patch16_supervised_mulitilingual_1920_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_base_patch16_supervised_mulitilingual_1920_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_base_patch16_supervised_mulitilingual_1920_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|509.7 MB| + +## References + +https://huggingface.co/gowitheflowlab/clip-base-patch16-supervised-mulitilingual-1920 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_base_patch16_supervised_mulitilingual_nli_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_base_patch16_supervised_mulitilingual_nli_en.md new file mode 100644 index 00000000000000..98fd04ccd4b2d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_base_patch16_supervised_mulitilingual_nli_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_base_patch16_supervised_mulitilingual_nli CLIPForZeroShotClassification from gowitheflowlab +author: John Snow Labs +name: clip_base_patch16_supervised_mulitilingual_nli +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_base_patch16_supervised_mulitilingual_nli` is a English model originally trained by gowitheflowlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_nli_en_5.5.0_3.0_1725227396766.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_nli_en_5.5.0_3.0_1725227396766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_base_patch16_supervised_mulitilingual_nli","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_base_patch16_supervised_mulitilingual_nli","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_base_patch16_supervised_mulitilingual_nli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|509.7 MB| + +## References + +https://huggingface.co/gowitheflowlab/clip-base-patch16-supervised-mulitilingual-nli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_base_patch16_supervised_mulitilingual_nli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_base_patch16_supervised_mulitilingual_nli_pipeline_en.md new file mode 100644 index 00000000000000..03a76ad8e127cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_base_patch16_supervised_mulitilingual_nli_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_base_patch16_supervised_mulitilingual_nli_pipeline pipeline CLIPForZeroShotClassification from gowitheflowlab +author: John Snow Labs +name: clip_base_patch16_supervised_mulitilingual_nli_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_base_patch16_supervised_mulitilingual_nli_pipeline` is a English model originally trained by gowitheflowlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_nli_pipeline_en_5.5.0_3.0_1725227446575.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_nli_pipeline_en_5.5.0_3.0_1725227446575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_base_patch16_supervised_mulitilingual_nli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_base_patch16_supervised_mulitilingual_nli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_base_patch16_supervised_mulitilingual_nli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|509.7 MB| + +## References + +https://huggingface.co/gowitheflowlab/clip-base-patch16-supervised-mulitilingual-nli + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_general_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_general_en.md new file mode 100644 index 00000000000000..4d2946cfecea2e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_general_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_general CLIPForZeroShotClassification from vinluvie +author: John Snow Labs +name: clip_general +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_general` is a English model originally trained by vinluvie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_general_en_5.4.2_3.0_1725159487359.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_general_en_5.4.2_3.0_1725159487359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_general","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_general","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_general| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/vinluvie/clip-general \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_hugging_face_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_hugging_face_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..fda5d006d68c4c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_hugging_face_finetuned_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_hugging_face_finetuned_pipeline pipeline CLIPForZeroShotClassification from BilelDJ +author: John Snow Labs +name: clip_hugging_face_finetuned_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_hugging_face_finetuned_pipeline` is a English model originally trained by BilelDJ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_hugging_face_finetuned_pipeline_en_5.4.2_3.0_1725159404360.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_hugging_face_finetuned_pipeline_en_5.4.2_3.0_1725159404360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_hugging_face_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_hugging_face_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_hugging_face_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/BilelDJ/clip-hugging-face-finetuned + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_rsicd_v2_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_rsicd_v2_en.md new file mode 100644 index 00000000000000..813b3865a7be5a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_rsicd_v2_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_rsicd_v2 CLIPForZeroShotClassification from flax-community +author: John Snow Labs +name: clip_rsicd_v2 +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_rsicd_v2` is a English model originally trained by flax-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_rsicd_v2_en_5.5.0_3.0_1725226467914.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_rsicd_v2_en_5.5.0_3.0_1725226467914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_rsicd_v2","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_rsicd_v2","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_rsicd_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/flax-community/clip-rsicd-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_rsicd_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_rsicd_v2_pipeline_en.md new file mode 100644 index 00000000000000..cc7b3c20d38847 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_rsicd_v2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_rsicd_v2_pipeline pipeline CLIPForZeroShotClassification from flax-community +author: John Snow Labs +name: clip_rsicd_v2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_rsicd_v2_pipeline` is a English model originally trained by flax-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_rsicd_v2_pipeline_en_5.5.0_3.0_1725226503841.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_rsicd_v2_pipeline_en_5.5.0_3.0_1725226503841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_rsicd_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_rsicd_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_rsicd_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/flax-community/clip-rsicd-v2 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_sup_multi_symmetric_400_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_sup_multi_symmetric_400_en.md new file mode 100644 index 00000000000000..b45d9eaec47596 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_sup_multi_symmetric_400_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_sup_multi_symmetric_400 CLIPForZeroShotClassification from gowitheflowlab +author: John Snow Labs +name: clip_sup_multi_symmetric_400 +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_sup_multi_symmetric_400` is a English model originally trained by gowitheflowlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_sup_multi_symmetric_400_en_5.5.0_3.0_1725226695762.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_sup_multi_symmetric_400_en_5.5.0_3.0_1725226695762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_sup_multi_symmetric_400","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_sup_multi_symmetric_400","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_sup_multi_symmetric_400| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|509.7 MB| + +## References + +https://huggingface.co/gowitheflowlab/clip-sup-multi-symmetric-400 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_sup_multi_symmetric_400_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_sup_multi_symmetric_400_pipeline_en.md new file mode 100644 index 00000000000000..0fbb2c2724d449 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_sup_multi_symmetric_400_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_sup_multi_symmetric_400_pipeline pipeline CLIPForZeroShotClassification from gowitheflowlab +author: John Snow Labs +name: clip_sup_multi_symmetric_400_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_sup_multi_symmetric_400_pipeline` is a English model originally trained by gowitheflowlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_sup_multi_symmetric_400_pipeline_en_5.5.0_3.0_1725226749523.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_sup_multi_symmetric_400_pipeline_en_5.5.0_3.0_1725226749523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_sup_multi_symmetric_400_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_sup_multi_symmetric_400_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_sup_multi_symmetric_400_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|509.8 MB| + +## References + +https://huggingface.co/gowitheflowlab/clip-sup-multi-symmetric-400 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_b_32_laion2b_s34b_b79k_rroset_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_b_32_laion2b_s34b_b79k_rroset_en.md new file mode 100644 index 00000000000000..aa24d78300476d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_b_32_laion2b_s34b_b79k_rroset_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_b_32_laion2b_s34b_b79k_rroset CLIPForZeroShotClassification from rroset +author: John Snow Labs +name: clip_vit_b_32_laion2b_s34b_b79k_rroset +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_b_32_laion2b_s34b_b79k_rroset` is a English model originally trained by rroset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_b_32_laion2b_s34b_b79k_rroset_en_5.5.0_3.0_1725227375636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_b_32_laion2b_s34b_b79k_rroset_en_5.5.0_3.0_1725227375636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_b_32_laion2b_s34b_b79k_rroset","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_b_32_laion2b_s34b_b79k_rroset","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_b_32_laion2b_s34b_b79k_rroset| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|567.6 MB| + +## References + +https://huggingface.co/rroset/CLIP-ViT-B-32-laion2B-s34B-b79K \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_adasdimchom_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_adasdimchom_en.md new file mode 100644 index 00000000000000..0a60502ab1e863 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_adasdimchom_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_base_patch32_adasdimchom CLIPForZeroShotClassification from adasdimchom +author: John Snow Labs +name: clip_vit_base_patch32_adasdimchom +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_adasdimchom` is a English model originally trained by adasdimchom. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_adasdimchom_en_5.5.0_3.0_1725227448471.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_adasdimchom_en_5.5.0_3.0_1725227448471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_adasdimchom","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_adasdimchom","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_adasdimchom| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/adasdimchom/clip-vit-base-patch32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_adasdimchom_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_adasdimchom_pipeline_en.md new file mode 100644 index 00000000000000..a460f20c64a15a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_adasdimchom_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_vit_base_patch32_adasdimchom_pipeline pipeline CLIPForZeroShotClassification from adasdimchom +author: John Snow Labs +name: clip_vit_base_patch32_adasdimchom_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_adasdimchom_pipeline` is a English model originally trained by adasdimchom. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_adasdimchom_pipeline_en_5.5.0_3.0_1725227549912.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_adasdimchom_pipeline_en_5.5.0_3.0_1725227549912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_vit_base_patch32_adasdimchom_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_vit_base_patch32_adasdimchom_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_adasdimchom_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/adasdimchom/clip-vit-base-patch32 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_demo_omarques_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_demo_omarques_en.md new file mode 100644 index 00000000000000..73b3406b4215b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_demo_omarques_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_base_patch32_demo_omarques CLIPForZeroShotClassification from omarques +author: John Snow Labs +name: clip_vit_base_patch32_demo_omarques +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_demo_omarques` is a English model originally trained by omarques. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_omarques_en_5.5.0_3.0_1725227613223.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_omarques_en_5.5.0_3.0_1725227613223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo_omarques","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo_omarques","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_demo_omarques| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/omarques/clip-vit-base-patch32-demo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_demo_omarques_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_demo_omarques_pipeline_en.md new file mode 100644 index 00000000000000..8b839d2e3d392d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_demo_omarques_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_vit_base_patch32_demo_omarques_pipeline pipeline CLIPForZeroShotClassification from omarques +author: John Snow Labs +name: clip_vit_base_patch32_demo_omarques_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_demo_omarques_pipeline` is a English model originally trained by omarques. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_omarques_pipeline_en_5.5.0_3.0_1725227709047.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_omarques_pipeline_en_5.5.0_3.0_1725227709047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_vit_base_patch32_demo_omarques_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_vit_base_patch32_demo_omarques_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_demo_omarques_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/omarques/clip-vit-base-patch32-demo + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_demo_pizapalooza_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_demo_pizapalooza_en.md new file mode 100644 index 00000000000000..71afacbbb277f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_demo_pizapalooza_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_base_patch32_demo_pizapalooza CLIPForZeroShotClassification from pizapalooza +author: John Snow Labs +name: clip_vit_base_patch32_demo_pizapalooza +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_demo_pizapalooza` is a English model originally trained by pizapalooza. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_pizapalooza_en_5.5.0_3.0_1725226371632.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_pizapalooza_en_5.5.0_3.0_1725226371632.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo_pizapalooza","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo_pizapalooza","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_demo_pizapalooza| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/pizapalooza/clip-vit-base-patch32-demo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_demo_pizapalooza_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_demo_pizapalooza_pipeline_en.md new file mode 100644 index 00000000000000..c4ac21bf6a0d21 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_demo_pizapalooza_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_vit_base_patch32_demo_pizapalooza_pipeline pipeline CLIPForZeroShotClassification from pizapalooza +author: John Snow Labs +name: clip_vit_base_patch32_demo_pizapalooza_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_demo_pizapalooza_pipeline` is a English model originally trained by pizapalooza. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_pizapalooza_pipeline_en_5.5.0_3.0_1725226469030.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_pizapalooza_pipeline_en_5.5.0_3.0_1725226469030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_vit_base_patch32_demo_pizapalooza_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_vit_base_patch32_demo_pizapalooza_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_demo_pizapalooza_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/pizapalooza/clip-vit-base-patch32-demo + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_purr_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_purr_en.md new file mode 100644 index 00000000000000..8a7a24faee7207 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_purr_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_base_patch32_purr CLIPForZeroShotClassification from Sheryl815 +author: John Snow Labs +name: clip_vit_base_patch32_purr +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_purr` is a English model originally trained by Sheryl815. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_purr_en_5.5.0_3.0_1725227641864.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_purr_en_5.5.0_3.0_1725227641864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_purr","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_purr","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_purr| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/Sheryl815/clip-vit-base-patch32-purr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_purr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_purr_pipeline_en.md new file mode 100644 index 00000000000000..b5d5dec0ce5505 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_purr_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_vit_base_patch32_purr_pipeline pipeline CLIPForZeroShotClassification from Sheryl815 +author: John Snow Labs +name: clip_vit_base_patch32_purr_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_purr_pipeline` is a English model originally trained by Sheryl815. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_purr_pipeline_en_5.5.0_3.0_1725227737845.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_purr_pipeline_en_5.5.0_3.0_1725227737845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_vit_base_patch32_purr_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_vit_base_patch32_purr_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_purr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/Sheryl815/clip-vit-base-patch32-purr + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_saullu_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_saullu_en.md new file mode 100644 index 00000000000000..347756c6f555f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_saullu_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_base_patch32_saullu CLIPForZeroShotClassification from SaulLu +author: John Snow Labs +name: clip_vit_base_patch32_saullu +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_saullu` is a English model originally trained by SaulLu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_saullu_en_5.5.0_3.0_1725227597341.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_saullu_en_5.5.0_3.0_1725227597341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_saullu","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_saullu","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_saullu| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/SaulLu/clip-vit-base-patch32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_saullu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_saullu_pipeline_en.md new file mode 100644 index 00000000000000..d32e29a6939076 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_base_patch32_saullu_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_vit_base_patch32_saullu_pipeline pipeline CLIPForZeroShotClassification from SaulLu +author: John Snow Labs +name: clip_vit_base_patch32_saullu_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_saullu_pipeline` is a English model originally trained by SaulLu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_saullu_pipeline_en_5.5.0_3.0_1725227693127.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_saullu_pipeline_en_5.5.0_3.0_1725227693127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_vit_base_patch32_saullu_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_vit_base_patch32_saullu_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_saullu_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/SaulLu/clip-vit-base-patch32 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_large_patch14_336_romilshah16_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_large_patch14_336_romilshah16_en.md new file mode 100644 index 00000000000000..c0b772a3bcb091 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_large_patch14_336_romilshah16_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_large_patch14_336_romilshah16 CLIPForZeroShotClassification from romilshah16 +author: John Snow Labs +name: clip_vit_large_patch14_336_romilshah16 +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_336_romilshah16` is a English model originally trained by romilshah16. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_336_romilshah16_en_5.5.0_3.0_1725227661586.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_336_romilshah16_en_5.5.0_3.0_1725227661586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_336_romilshah16","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_336_romilshah16","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_large_patch14_336_romilshah16| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/romilshah16/clip-vit-large-patch14-336 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_large_patch14_336_romilshah16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_large_patch14_336_romilshah16_pipeline_en.md new file mode 100644 index 00000000000000..e508373a7c791b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_large_patch14_336_romilshah16_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_vit_large_patch14_336_romilshah16_pipeline pipeline CLIPForZeroShotClassification from romilshah16 +author: John Snow Labs +name: clip_vit_large_patch14_336_romilshah16_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_336_romilshah16_pipeline` is a English model originally trained by romilshah16. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_336_romilshah16_pipeline_en_5.5.0_3.0_1725227939260.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_336_romilshah16_pipeline_en_5.5.0_3.0_1725227939260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_vit_large_patch14_336_romilshah16_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_vit_large_patch14_336_romilshah16_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_large_patch14_336_romilshah16_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/romilshah16/clip-vit-large-patch14-336 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_tiny_random_patch14_336_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_tiny_random_patch14_336_en.md new file mode 100644 index 00000000000000..be620e138f9352 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_tiny_random_patch14_336_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_tiny_random_patch14_336 CLIPForZeroShotClassification from yujiepan +author: John Snow Labs +name: clip_vit_tiny_random_patch14_336 +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_tiny_random_patch14_336` is a English model originally trained by yujiepan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_tiny_random_patch14_336_en_5.5.0_3.0_1725227796332.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_tiny_random_patch14_336_en_5.5.0_3.0_1725227796332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_tiny_random_patch14_336","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_tiny_random_patch14_336","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_tiny_random_patch14_336| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|2.1 MB| + +## References + +https://huggingface.co/yujiepan/clip-vit-tiny-random-patch14-336 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clip_vit_tiny_random_patch14_336_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_tiny_random_patch14_336_pipeline_en.md new file mode 100644 index 00000000000000..97fb7a71722c8b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clip_vit_tiny_random_patch14_336_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_vit_tiny_random_patch14_336_pipeline pipeline CLIPForZeroShotClassification from yujiepan +author: John Snow Labs +name: clip_vit_tiny_random_patch14_336_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_tiny_random_patch14_336_pipeline` is a English model originally trained by yujiepan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_tiny_random_patch14_336_pipeline_en_5.5.0_3.0_1725227797118.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_tiny_random_patch14_336_pipeline_en_5.5.0_3.0_1725227797118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_vit_tiny_random_patch14_336_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_vit_tiny_random_patch14_336_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_tiny_random_patch14_336_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|2.1 MB| + +## References + +https://huggingface.co/yujiepan/clip-vit-tiny-random-patch14-336 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clipmd_en.md b/docs/_posts/ahmedlone127/2024-09-01-clipmd_en.md new file mode 100644 index 00000000000000..5a8d7953e28874 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clipmd_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clipmd CLIPForZeroShotClassification from Idan0405 +author: John Snow Labs +name: clipmd +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clipmd` is a English model originally trained by Idan0405. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clipmd_en_5.5.0_3.0_1725226500192.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clipmd_en_5.5.0_3.0_1725226500192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clipmd","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clipmd","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clipmd| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/Idan0405/ClipMD \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-clipmd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-clipmd_pipeline_en.md new file mode 100644 index 00000000000000..28ffc2e265d63f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-clipmd_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clipmd_pipeline pipeline CLIPForZeroShotClassification from Idan0405 +author: John Snow Labs +name: clipmd_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clipmd_pipeline` is a English model originally trained by Idan0405. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clipmd_pipeline_en_5.5.0_3.0_1725226536168.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clipmd_pipeline_en_5.5.0_3.0_1725226536168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clipmd_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clipmd_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clipmd_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/Idan0405/ClipMD + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-code_prompt_similarity_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-code_prompt_similarity_model_pipeline_en.md new file mode 100644 index 00000000000000..fd8d8e68bcff75 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-code_prompt_similarity_model_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English code_prompt_similarity_model_pipeline pipeline MPNetEmbeddings from davanstrien +author: John Snow Labs +name: code_prompt_similarity_model_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_prompt_similarity_model_pipeline` is a English model originally trained by davanstrien. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_prompt_similarity_model_pipeline_en_5.5.0_3.0_1725225059472.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_prompt_similarity_model_pipeline_en_5.5.0_3.0_1725225059472.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("code_prompt_similarity_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("code_prompt_similarity_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|code_prompt_similarity_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|380.8 MB| + +## References + +https://huggingface.co/davanstrien/code-prompt-similarity-model + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-code_segmentor_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-code_segmentor_distilbert_pipeline_en.md new file mode 100644 index 00000000000000..78e9a4f313afd2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-code_segmentor_distilbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English code_segmentor_distilbert_pipeline pipeline DistilBertForTokenClassification from LemiSt +author: John Snow Labs +name: code_segmentor_distilbert_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_segmentor_distilbert_pipeline` is a English model originally trained by LemiSt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_segmentor_distilbert_pipeline_en_5.4.2_3.0_1725160746871.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_segmentor_distilbert_pipeline_en_5.4.2_3.0_1725160746871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("code_segmentor_distilbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("code_segmentor_distilbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|code_segmentor_distilbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|505.5 MB| + +## References + +https://huggingface.co/LemiSt/code-segmentor-distilbert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-codebert_javascript_en.md b/docs/_posts/ahmedlone127/2024-09-01-codebert_javascript_en.md new file mode 100644 index 00000000000000..28798f6626490f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-codebert_javascript_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English codebert_javascript RoBertaEmbeddings from neulab +author: John Snow Labs +name: codebert_javascript +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`codebert_javascript` is a English model originally trained by neulab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/codebert_javascript_en_5.4.2_3.0_1725186546069.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/codebert_javascript_en_5.4.2_3.0_1725186546069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("codebert_javascript","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("codebert_javascript","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|codebert_javascript| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|466.0 MB| + +## References + +https://huggingface.co/neulab/codebert-javascript \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-codebert_portuguesebased_creoles_and_pidgins_en.md b/docs/_posts/ahmedlone127/2024-09-01-codebert_portuguesebased_creoles_and_pidgins_en.md new file mode 100644 index 00000000000000..56a7f94943c72a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-codebert_portuguesebased_creoles_and_pidgins_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English codebert_portuguesebased_creoles_and_pidgins RoBertaEmbeddings from neulab +author: John Snow Labs +name: codebert_portuguesebased_creoles_and_pidgins +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`codebert_portuguesebased_creoles_and_pidgins` is a English model originally trained by neulab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/codebert_portuguesebased_creoles_and_pidgins_en_5.4.2_3.0_1725165385225.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/codebert_portuguesebased_creoles_and_pidgins_en_5.4.2_3.0_1725165385225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("codebert_portuguesebased_creoles_and_pidgins","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("codebert_portuguesebased_creoles_and_pidgins","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|codebert_portuguesebased_creoles_and_pidgins| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|466.0 MB| + +## References + +https://huggingface.co/neulab/codebert-cpp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_en.md b/docs/_posts/ahmedlone127/2024-09-01-codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_en.md new file mode 100644 index 00000000000000..b07253a85ecd24 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins RoBertaEmbeddings from maximus12793 +author: John Snow Labs +name: codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins` is a English model originally trained by maximus12793. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_en_5.4.2_3.0_1725191818153.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_en_5.4.2_3.0_1725191818153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|312.1 MB| + +## References + +https://huggingface.co/maximus12793/CodeBERTa-small-v1-finetuned-cpp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_pipeline_en.md new file mode 100644 index 00000000000000..a0849d556a90e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_pipeline pipeline RoBertaEmbeddings from maximus12793 +author: John Snow Labs +name: codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_pipeline` is a English model originally trained by maximus12793. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_pipeline_en_5.4.2_3.0_1725191834726.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_pipeline_en_5.4.2_3.0_1725191834726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|codeberta_small_v1_finetuned_portuguesebased_creoles_and_pidgins_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|312.1 MB| + +## References + +https://huggingface.co/maximus12793/CodeBERTa-small-v1-finetuned-cpp + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-cold_light_pass_en.md b/docs/_posts/ahmedlone127/2024-09-01-cold_light_pass_en.md new file mode 100644 index 00000000000000..11cbbb1c195843 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-cold_light_pass_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English cold_light_pass CLIPForZeroShotClassification from Bingsu +author: John Snow Labs +name: cold_light_pass +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_light_pass` is a English model originally trained by Bingsu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_light_pass_en_5.5.0_3.0_1725226396302.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_light_pass_en_5.5.0_3.0_1725226396302.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("cold_light_pass","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("cold_light_pass","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_light_pass| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Bingsu/cold_light_pass \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-cold_light_pass_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-cold_light_pass_pipeline_en.md new file mode 100644 index 00000000000000..b1f53a3aad383c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-cold_light_pass_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English cold_light_pass_pipeline pipeline CLIPForZeroShotClassification from Bingsu +author: John Snow Labs +name: cold_light_pass_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_light_pass_pipeline` is a English model originally trained by Bingsu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_light_pass_pipeline_en_5.5.0_3.0_1725226638348.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_light_pass_pipeline_en_5.5.0_3.0_1725226638348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cold_light_pass_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cold_light_pass_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_light_pass_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Bingsu/cold_light_pass + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-comma_mdeberta_v3_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-comma_mdeberta_v3_base_en.md new file mode 100644 index 00000000000000..f9114531db4f34 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-comma_mdeberta_v3_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English comma_mdeberta_v3_base DeBertaForTokenClassification from aseifert +author: John Snow Labs +name: comma_mdeberta_v3_base +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`comma_mdeberta_v3_base` is a English model originally trained by aseifert. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/comma_mdeberta_v3_base_en_5.4.2_3.0_1725197741170.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/comma_mdeberta_v3_base_en_5.4.2_3.0_1725197741170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("comma_mdeberta_v3_base","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("comma_mdeberta_v3_base", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|comma_mdeberta_v3_base| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|811.5 MB| + +## References + +https://huggingface.co/aseifert/comma-mdeberta-v3-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-comma_mdeberta_v3_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-comma_mdeberta_v3_base_pipeline_en.md new file mode 100644 index 00000000000000..07df0a6875ee29 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-comma_mdeberta_v3_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English comma_mdeberta_v3_base_pipeline pipeline DeBertaForTokenClassification from aseifert +author: John Snow Labs +name: comma_mdeberta_v3_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`comma_mdeberta_v3_base_pipeline` is a English model originally trained by aseifert. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/comma_mdeberta_v3_base_pipeline_en_5.4.2_3.0_1725197881048.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/comma_mdeberta_v3_base_pipeline_en_5.4.2_3.0_1725197881048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("comma_mdeberta_v3_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("comma_mdeberta_v3_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|comma_mdeberta_v3_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|811.6 MB| + +## References + +https://huggingface.co/aseifert/comma-mdeberta-v3-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-command_ner_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-command_ner_distilbert_pipeline_en.md new file mode 100644 index 00000000000000..a05d51803d3b7e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-command_ner_distilbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English command_ner_distilbert_pipeline pipeline DistilBertForTokenClassification from HoaAn2003 +author: John Snow Labs +name: command_ner_distilbert_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`command_ner_distilbert_pipeline` is a English model originally trained by HoaAn2003. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/command_ner_distilbert_pipeline_en_5.4.2_3.0_1725172508599.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/command_ner_distilbert_pipeline_en_5.4.2_3.0_1725172508599.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("command_ner_distilbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("command_ner_distilbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|command_ner_distilbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/HoaAn2003/command_ner_distilbert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-contriever_mnli_en.md b/docs/_posts/ahmedlone127/2024-09-01-contriever_mnli_en.md new file mode 100644 index 00000000000000..ba19347cd5b840 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-contriever_mnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English contriever_mnli BertForZeroShotClassification from mjwong +author: John Snow Labs +name: contriever_mnli +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`contriever_mnli` is a English model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/contriever_mnli_en_5.4.2_3.0_1725201954286.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/contriever_mnli_en_5.4.2_3.0_1725201954286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("contriever_mnli","en") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("contriever_mnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|contriever_mnli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|407.5 MB| + +## References + +https://huggingface.co/mjwong/contriever-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-contriever_mnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-contriever_mnli_pipeline_en.md new file mode 100644 index 00000000000000..5a7e54411456f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-contriever_mnli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English contriever_mnli_pipeline pipeline BertForZeroShotClassification from mjwong +author: John Snow Labs +name: contriever_mnli_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`contriever_mnli_pipeline` is a English model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/contriever_mnli_pipeline_en_5.4.2_3.0_1725201976378.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/contriever_mnli_pipeline_en_5.4.2_3.0_1725201976378.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("contriever_mnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("contriever_mnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|contriever_mnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.5 MB| + +## References + +https://huggingface.co/mjwong/contriever-mnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_allnli_turkish_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_allnli_turkish_pipeline_tr.md new file mode 100644 index 00000000000000..ee89a08201f3f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_allnli_turkish_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish convbert_base_turkish_mc4_cased_allnli_turkish_pipeline pipeline BertForZeroShotClassification from emrecan +author: John Snow Labs +name: convbert_base_turkish_mc4_cased_allnli_turkish_pipeline +date: 2024-09-01 +tags: [tr, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_mc4_cased_allnli_turkish_pipeline` is a Turkish model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_allnli_turkish_pipeline_tr_5.4.2_3.0_1725207984343.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_allnli_turkish_pipeline_tr_5.4.2_3.0_1725207984343.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("convbert_base_turkish_mc4_cased_allnli_turkish_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("convbert_base_turkish_mc4_cased_allnli_turkish_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|convbert_base_turkish_mc4_cased_allnli_turkish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|400.1 MB| + +## References + +https://huggingface.co/emrecan/convbert-base-turkish-mc4-cased-allnli_tr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_allnli_turkish_tr.md b/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_allnli_turkish_tr.md new file mode 100644 index 00000000000000..62a7d9d8a6ccc7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_allnli_turkish_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish convbert_base_turkish_mc4_cased_allnli_turkish BertForZeroShotClassification from emrecan +author: John Snow Labs +name: convbert_base_turkish_mc4_cased_allnli_turkish +date: 2024-09-01 +tags: [tr, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_mc4_cased_allnli_turkish` is a Turkish model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_allnli_turkish_tr_5.4.2_3.0_1725207962631.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_allnli_turkish_tr_5.4.2_3.0_1725207962631.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("convbert_base_turkish_mc4_cased_allnli_turkish","tr") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("convbert_base_turkish_mc4_cased_allnli_turkish", "tr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|convbert_base_turkish_mc4_cased_allnli_turkish| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|400.1 MB| + +## References + +https://huggingface.co/emrecan/convbert-base-turkish-mc4-cased-allnli_tr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_multinli_turkish_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_multinli_turkish_pipeline_tr.md new file mode 100644 index 00000000000000..fea14036c3466d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_multinli_turkish_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish convbert_base_turkish_mc4_cased_multinli_turkish_pipeline pipeline BertForZeroShotClassification from emrecan +author: John Snow Labs +name: convbert_base_turkish_mc4_cased_multinli_turkish_pipeline +date: 2024-09-01 +tags: [tr, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_mc4_cased_multinli_turkish_pipeline` is a Turkish model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_multinli_turkish_pipeline_tr_5.4.2_3.0_1725208019522.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_multinli_turkish_pipeline_tr_5.4.2_3.0_1725208019522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("convbert_base_turkish_mc4_cased_multinli_turkish_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("convbert_base_turkish_mc4_cased_multinli_turkish_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|convbert_base_turkish_mc4_cased_multinli_turkish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|400.1 MB| + +## References + +https://huggingface.co/emrecan/convbert-base-turkish-mc4-cased-multinli_tr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_multinli_turkish_tr.md b/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_multinli_turkish_tr.md new file mode 100644 index 00000000000000..04e2da01317d52 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_multinli_turkish_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish convbert_base_turkish_mc4_cased_multinli_turkish BertForZeroShotClassification from emrecan +author: John Snow Labs +name: convbert_base_turkish_mc4_cased_multinli_turkish +date: 2024-09-01 +tags: [tr, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_mc4_cased_multinli_turkish` is a Turkish model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_multinli_turkish_tr_5.4.2_3.0_1725207998284.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_multinli_turkish_tr_5.4.2_3.0_1725207998284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("convbert_base_turkish_mc4_cased_multinli_turkish","tr") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("convbert_base_turkish_mc4_cased_multinli_turkish", "tr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|convbert_base_turkish_mc4_cased_multinli_turkish| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|400.1 MB| + +## References + +https://huggingface.co/emrecan/convbert-base-turkish-mc4-cased-multinli_tr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_snli_turkish_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_snli_turkish_pipeline_tr.md new file mode 100644 index 00000000000000..bcf5195a4439a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_snli_turkish_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish convbert_base_turkish_mc4_cased_snli_turkish_pipeline pipeline BertForZeroShotClassification from emrecan +author: John Snow Labs +name: convbert_base_turkish_mc4_cased_snli_turkish_pipeline +date: 2024-09-01 +tags: [tr, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_mc4_cased_snli_turkish_pipeline` is a Turkish model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_snli_turkish_pipeline_tr_5.4.2_3.0_1725201670691.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_snli_turkish_pipeline_tr_5.4.2_3.0_1725201670691.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("convbert_base_turkish_mc4_cased_snli_turkish_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("convbert_base_turkish_mc4_cased_snli_turkish_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|convbert_base_turkish_mc4_cased_snli_turkish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|400.1 MB| + +## References + +https://huggingface.co/emrecan/convbert-base-turkish-mc4-cased-snli_tr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_snli_turkish_tr.md b/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_snli_turkish_tr.md new file mode 100644 index 00000000000000..b88d12aec459e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-convbert_base_turkish_mc4_cased_snli_turkish_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish convbert_base_turkish_mc4_cased_snli_turkish BertForZeroShotClassification from emrecan +author: John Snow Labs +name: convbert_base_turkish_mc4_cased_snli_turkish +date: 2024-09-01 +tags: [tr, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: tr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_mc4_cased_snli_turkish` is a Turkish model originally trained by emrecan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_snli_turkish_tr_5.4.2_3.0_1725201643376.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_snli_turkish_tr_5.4.2_3.0_1725201643376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("convbert_base_turkish_mc4_cased_snli_turkish","tr") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("convbert_base_turkish_mc4_cased_snli_turkish", "tr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|convbert_base_turkish_mc4_cased_snli_turkish| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|400.1 MB| + +## References + +https://huggingface.co/emrecan/convbert-base-turkish-mc4-cased-snli_tr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-covid_trained_deberta_en.md b/docs/_posts/ahmedlone127/2024-09-01-covid_trained_deberta_en.md new file mode 100644 index 00000000000000..b6370232052a5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-covid_trained_deberta_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English covid_trained_deberta DeBertaEmbeddings from timoneda +author: John Snow Labs +name: covid_trained_deberta +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_trained_deberta` is a English model originally trained by timoneda. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_trained_deberta_en_5.5.0_3.0_1725230044723.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_trained_deberta_en_5.5.0_3.0_1725230044723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("covid_trained_deberta","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("covid_trained_deberta","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_trained_deberta| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/timoneda/covid-trained-deberta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-covid_trained_deberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-covid_trained_deberta_pipeline_en.md new file mode 100644 index 00000000000000..1c4cb78c4c87d5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-covid_trained_deberta_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English covid_trained_deberta_pipeline pipeline DeBertaEmbeddings from timoneda +author: John Snow Labs +name: covid_trained_deberta_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_trained_deberta_pipeline` is a English model originally trained by timoneda. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_trained_deberta_pipeline_en_5.5.0_3.0_1725230126639.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_trained_deberta_pipeline_en_5.5.0_3.0_1725230126639.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("covid_trained_deberta_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("covid_trained_deberta_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_trained_deberta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/timoneda/covid-trained-deberta + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-cpegen_prod_en.md b/docs/_posts/ahmedlone127/2024-09-01-cpegen_prod_en.md new file mode 100644 index 00000000000000..eb7c278766e981 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-cpegen_prod_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cpegen_prod DistilBertForTokenClassification from Neurona +author: John Snow Labs +name: cpegen_prod +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cpegen_prod` is a English model originally trained by Neurona. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cpegen_prod_en_5.4.2_3.0_1725172120362.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cpegen_prod_en_5.4.2_3.0_1725172120362.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("cpegen_prod","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("cpegen_prod", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cpegen_prod| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/Neurona/cpegen_prod \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-crossencoder_mminilmv2_l12_mmarcofr_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-01-crossencoder_mminilmv2_l12_mmarcofr_pipeline_fr.md new file mode 100644 index 00000000000000..03da25903b4260 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-crossencoder_mminilmv2_l12_mmarcofr_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French crossencoder_mminilmv2_l12_mmarcofr_pipeline pipeline XlmRoBertaForSequenceClassification from antoinelouis +author: John Snow Labs +name: crossencoder_mminilmv2_l12_mmarcofr_pipeline +date: 2024-09-01 +tags: [fr, open_source, pipeline, onnx] +task: Text Classification +language: fr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_mminilmv2_l12_mmarcofr_pipeline` is a French model originally trained by antoinelouis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_mminilmv2_l12_mmarcofr_pipeline_fr_5.4.2_3.0_1725189115481.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_mminilmv2_l12_mmarcofr_pipeline_fr_5.4.2_3.0_1725189115481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("crossencoder_mminilmv2_l12_mmarcofr_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("crossencoder_mminilmv2_l12_mmarcofr_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|crossencoder_mminilmv2_l12_mmarcofr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|356.8 MB| + +## References + +https://huggingface.co/antoinelouis/crossencoder-mMiniLMv2-L12-mmarcoFR + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-cso_ner_en.md b/docs/_posts/ahmedlone127/2024-09-01-cso_ner_en.md new file mode 100644 index 00000000000000..41687adab1d1e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-cso_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cso_ner DistilBertForTokenClassification from myselfronin +author: John Snow Labs +name: cso_ner +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cso_ner` is a English model originally trained by myselfronin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cso_ner_en_5.4.2_3.0_1725160771139.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cso_ner_en_5.4.2_3.0_1725160771139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("cso_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("cso_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cso_ner| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/myselfronin/cso_ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-cso_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-cso_ner_pipeline_en.md new file mode 100644 index 00000000000000..8d2ffd8c0731ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-cso_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cso_ner_pipeline pipeline DistilBertForTokenClassification from myselfronin +author: John Snow Labs +name: cso_ner_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cso_ner_pipeline` is a English model originally trained by myselfronin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cso_ner_pipeline_en_5.4.2_3.0_1725160784048.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cso_ner_pipeline_en_5.4.2_3.0_1725160784048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cso_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cso_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cso_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/myselfronin/cso_ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_1_2_en.md b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_1_2_en.md new file mode 100644 index 00000000000000..bafdc7fd9cc8ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_1_2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English ct_cos_mdeberta_idkmrc_1_2 DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_cos_mdeberta_idkmrc_1_2 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_mdeberta_idkmrc_1_2` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_mdeberta_idkmrc_1_2_en_5.5.0_3.0_1725221117346.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_mdeberta_idkmrc_1_2_en_5.5.0_3.0_1725221117346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_cos_mdeberta_idkmrc_1_2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_cos_mdeberta_idkmrc_1_2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_cos_mdeberta_idkmrc_1_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|869.3 MB| + +## References + +https://huggingface.co/intanm/ct-cos-mdeberta-idkmrc-1-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_1_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_1_2_pipeline_en.md new file mode 100644 index 00000000000000..d5c14959f7b230 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_1_2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ct_cos_mdeberta_idkmrc_1_2_pipeline pipeline DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_cos_mdeberta_idkmrc_1_2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_mdeberta_idkmrc_1_2_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_mdeberta_idkmrc_1_2_pipeline_en_5.5.0_3.0_1725221221029.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_mdeberta_idkmrc_1_2_pipeline_en_5.5.0_3.0_1725221221029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ct_cos_mdeberta_idkmrc_1_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ct_cos_mdeberta_idkmrc_1_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_cos_mdeberta_idkmrc_1_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|869.3 MB| + +## References + +https://huggingface.co/intanm/ct-cos-mdeberta-idkmrc-1-2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_1_en.md b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_1_en.md new file mode 100644 index 00000000000000..e21ef0c6ded8c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English ct_cos_mdeberta_idkmrc_1 DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_cos_mdeberta_idkmrc_1 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_mdeberta_idkmrc_1` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_mdeberta_idkmrc_1_en_5.5.0_3.0_1725220315148.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_mdeberta_idkmrc_1_en_5.5.0_3.0_1725220315148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_cos_mdeberta_idkmrc_1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_cos_mdeberta_idkmrc_1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_cos_mdeberta_idkmrc_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|867.7 MB| + +## References + +https://huggingface.co/intanm/ct-cos-mdeberta-idkmrc-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_1_pipeline_en.md new file mode 100644 index 00000000000000..ade286243e4e73 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ct_cos_mdeberta_idkmrc_1_pipeline pipeline DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_cos_mdeberta_idkmrc_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_mdeberta_idkmrc_1_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_mdeberta_idkmrc_1_pipeline_en_5.5.0_3.0_1725220420611.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_mdeberta_idkmrc_1_pipeline_en_5.5.0_3.0_1725220420611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ct_cos_mdeberta_idkmrc_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ct_cos_mdeberta_idkmrc_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_cos_mdeberta_idkmrc_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|867.7 MB| + +## References + +https://huggingface.co/intanm/ct-cos-mdeberta-idkmrc-1 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_en.md b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_en.md new file mode 100644 index 00000000000000..5fbfc33d374425 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English ct_cos_mdeberta_idkmrc DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_cos_mdeberta_idkmrc +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_mdeberta_idkmrc` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_mdeberta_idkmrc_en_5.5.0_3.0_1725220534739.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_mdeberta_idkmrc_en_5.5.0_3.0_1725220534739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_cos_mdeberta_idkmrc","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_cos_mdeberta_idkmrc", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_cos_mdeberta_idkmrc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|867.7 MB| + +## References + +https://huggingface.co/intanm/ct-cos-mdeberta-idkmrc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_pipeline_en.md new file mode 100644 index 00000000000000..7034369095b08e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_mdeberta_idkmrc_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ct_cos_mdeberta_idkmrc_pipeline pipeline DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_cos_mdeberta_idkmrc_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_mdeberta_idkmrc_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_mdeberta_idkmrc_pipeline_en_5.5.0_3.0_1725220639769.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_mdeberta_idkmrc_pipeline_en_5.5.0_3.0_1725220639769.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ct_cos_mdeberta_idkmrc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ct_cos_mdeberta_idkmrc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_cos_mdeberta_idkmrc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|867.7 MB| + +## References + +https://huggingface.co/intanm/ct-cos-mdeberta-idkmrc + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ct_cos_xlmr_20230920_1_en.md b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_xlmr_20230920_1_en.md new file mode 100644 index 00000000000000..9765c7587190a1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_xlmr_20230920_1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English ct_cos_xlmr_20230920_1 XlmRoBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_cos_xlmr_20230920_1 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_xlmr_20230920_1` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_20230920_1_en_5.5.0_3.0_1725234464822.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_20230920_1_en_5.5.0_3.0_1725234464822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_cos_xlmr_20230920_1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_cos_xlmr_20230920_1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_cos_xlmr_20230920_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|876.0 MB| + +## References + +https://huggingface.co/intanm/ct-cos-xlmr-20230920-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ct_cos_xlmr_20230920_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_xlmr_20230920_1_pipeline_en.md new file mode 100644 index 00000000000000..a97794e129b9de --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_xlmr_20230920_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ct_cos_xlmr_20230920_1_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_cos_xlmr_20230920_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_xlmr_20230920_1_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_20230920_1_pipeline_en_5.5.0_3.0_1725234544577.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_20230920_1_pipeline_en_5.5.0_3.0_1725234544577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ct_cos_xlmr_20230920_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ct_cos_xlmr_20230920_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_cos_xlmr_20230920_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|876.0 MB| + +## References + +https://huggingface.co/intanm/ct-cos-xlmr-20230920-1 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ct_cos_xlmr_idkmrc_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_xlmr_idkmrc_1_pipeline_en.md new file mode 100644 index 00000000000000..b069a8a23a1d9a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ct_cos_xlmr_idkmrc_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ct_cos_xlmr_idkmrc_1_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_cos_xlmr_idkmrc_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_xlmr_idkmrc_1_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_idkmrc_1_pipeline_en_5.4.2_3.0_1725173867999.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_idkmrc_1_pipeline_en_5.4.2_3.0_1725173867999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ct_cos_xlmr_idkmrc_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ct_cos_xlmr_idkmrc_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_cos_xlmr_idkmrc_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|834.0 MB| + +## References + +https://huggingface.co/intanm/ct-cos-xlmr-idkmrc-1 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ct_m2_bestloss_en.md b/docs/_posts/ahmedlone127/2024-09-01-ct_m2_bestloss_en.md new file mode 100644 index 00000000000000..b7736bb401680c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ct_m2_bestloss_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ct_m2_bestloss RoBertaEmbeddings from crisistransformers +author: John Snow Labs +name: ct_m2_bestloss +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_m2_bestloss` is a English model originally trained by crisistransformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_m2_bestloss_en_5.4.2_3.0_1725191386302.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_m2_bestloss_en_5.4.2_3.0_1725191386302.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("ct_m2_bestloss","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("ct_m2_bestloss","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_m2_bestloss| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|466.2 MB| + +## References + +https://huggingface.co/crisistransformers/CT-M2-BestLoss \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ct_mse_mdeberta_webis_en.md b/docs/_posts/ahmedlone127/2024-09-01-ct_mse_mdeberta_webis_en.md new file mode 100644 index 00000000000000..d7033ce2c8d01d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ct_mse_mdeberta_webis_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English ct_mse_mdeberta_webis DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_mse_mdeberta_webis +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_mse_mdeberta_webis` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_mse_mdeberta_webis_en_5.5.0_3.0_1725221797405.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_mse_mdeberta_webis_en_5.5.0_3.0_1725221797405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_mse_mdeberta_webis","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_mse_mdeberta_webis", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_mse_mdeberta_webis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|841.9 MB| + +## References + +https://huggingface.co/intanm/ct-mse-mdeberta-webis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ct_mse_mdeberta_webis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ct_mse_mdeberta_webis_pipeline_en.md new file mode 100644 index 00000000000000..8f044ff49fc807 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ct_mse_mdeberta_webis_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ct_mse_mdeberta_webis_pipeline pipeline DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_mse_mdeberta_webis_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_mse_mdeberta_webis_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_mse_mdeberta_webis_pipeline_en_5.5.0_3.0_1725221912540.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_mse_mdeberta_webis_pipeline_en_5.5.0_3.0_1725221912540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ct_mse_mdeberta_webis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ct_mse_mdeberta_webis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_mse_mdeberta_webis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|841.9 MB| + +## References + +https://huggingface.co/intanm/ct-mse-mdeberta-webis + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-dagpap24_deberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-dagpap24_deberta_base_en.md new file mode 100644 index 00000000000000..69ab3fc824cfc2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-dagpap24_deberta_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dagpap24_deberta_base DeBertaEmbeddings from swimmingcrab +author: John Snow Labs +name: dagpap24_deberta_base +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dagpap24_deberta_base` is a English model originally trained by swimmingcrab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dagpap24_deberta_base_en_5.5.0_3.0_1725229831875.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dagpap24_deberta_base_en_5.5.0_3.0_1725229831875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("dagpap24_deberta_base","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("dagpap24_deberta_base","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dagpap24_deberta_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|660.5 MB| + +## References + +https://huggingface.co/swimmingcrab/DAGPap24-deberta-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-dagpap24_deberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-dagpap24_deberta_base_pipeline_en.md new file mode 100644 index 00000000000000..9d7539a3550432 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-dagpap24_deberta_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dagpap24_deberta_base_pipeline pipeline DeBertaEmbeddings from swimmingcrab +author: John Snow Labs +name: dagpap24_deberta_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dagpap24_deberta_base_pipeline` is a English model originally trained by swimmingcrab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dagpap24_deberta_base_pipeline_en_5.5.0_3.0_1725229877500.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dagpap24_deberta_base_pipeline_en_5.5.0_3.0_1725229877500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dagpap24_deberta_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dagpap24_deberta_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dagpap24_deberta_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|660.5 MB| + +## References + +https://huggingface.co/swimmingcrab/DAGPap24-deberta-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-danskbert_da.md b/docs/_posts/ahmedlone127/2024-09-01-danskbert_da.md new file mode 100644 index 00000000000000..cad5359262e6bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-danskbert_da.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Danish danskbert RoBertaEmbeddings from vesteinn +author: John Snow Labs +name: danskbert +date: 2024-09-01 +tags: [da, open_source, onnx, embeddings, roberta] +task: Embeddings +language: da +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danskbert` is a Danish model originally trained by vesteinn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danskbert_da_5.4.2_3.0_1725191462157.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danskbert_da_5.4.2_3.0_1725191462157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("danskbert","da") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("danskbert","da") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|danskbert| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|da| +|Size:|297.8 MB| + +## References + +https://huggingface.co/vesteinn/DanskBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-db_fe_1_1_en.md b/docs/_posts/ahmedlone127/2024-09-01-db_fe_1_1_en.md new file mode 100644 index 00000000000000..1aaa39e474b905 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-db_fe_1_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English db_fe_1_1 DistilBertForSequenceClassification from exala +author: John Snow Labs +name: db_fe_1_1 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_fe_1_1` is a English model originally trained by exala. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_fe_1_1_en_5.5.0_3.0_1725213751291.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_fe_1_1_en_5.5.0_3.0_1725213751291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("db_fe_1_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("db_fe_1_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|db_fe_1_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.6 MB| + +## References + +https://huggingface.co/exala/db_fe_1.1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-db_fe_1_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-db_fe_1_1_pipeline_en.md new file mode 100644 index 00000000000000..3f8685b6b92313 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-db_fe_1_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English db_fe_1_1_pipeline pipeline DistilBertForSequenceClassification from exala +author: John Snow Labs +name: db_fe_1_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_fe_1_1_pipeline` is a English model originally trained by exala. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_fe_1_1_pipeline_en_5.5.0_3.0_1725213764955.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_fe_1_1_pipeline_en_5.5.0_3.0_1725213764955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("db_fe_1_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("db_fe_1_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|db_fe_1_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.6 MB| + +## References + +https://huggingface.co/exala/db_fe_1.1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-db_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-db_finetuned_ner_pipeline_en.md new file mode 100644 index 00000000000000..9892754ba35ce3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-db_finetuned_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English db_finetuned_ner_pipeline pipeline DistilBertForTokenClassification from Yash907 +author: John Snow Labs +name: db_finetuned_ner_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_finetuned_ner_pipeline` is a English model originally trained by Yash907. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_finetuned_ner_pipeline_en_5.4.2_3.0_1725170971510.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_finetuned_ner_pipeline_en_5.4.2_3.0_1725170971510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("db_finetuned_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("db_finetuned_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|db_finetuned_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/Yash907/db-finetuned-NER + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_amazon_reviews_v1_masapasa_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_amazon_reviews_v1_masapasa_en.md new file mode 100644 index 00000000000000..7d00ea5bf98d42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_amazon_reviews_v1_masapasa_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_amazon_reviews_v1_masapasa DeBertaForSequenceClassification from masapasa +author: John Snow Labs +name: deberta_amazon_reviews_v1_masapasa +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_amazon_reviews_v1_masapasa` is a English model originally trained by masapasa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v1_masapasa_en_5.5.0_3.0_1725222495774.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v1_masapasa_en_5.5.0_3.0_1725222495774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_amazon_reviews_v1_masapasa","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_amazon_reviews_v1_masapasa", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_amazon_reviews_v1_masapasa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|437.4 MB| + +## References + +https://huggingface.co/masapasa/deberta_amazon_reviews_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_amazon_reviews_v1_masapasa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_amazon_reviews_v1_masapasa_pipeline_en.md new file mode 100644 index 00000000000000..90dc81f6ddd644 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_amazon_reviews_v1_masapasa_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_amazon_reviews_v1_masapasa_pipeline pipeline DeBertaForSequenceClassification from masapasa +author: John Snow Labs +name: deberta_amazon_reviews_v1_masapasa_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_amazon_reviews_v1_masapasa_pipeline` is a English model originally trained by masapasa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v1_masapasa_pipeline_en_5.5.0_3.0_1725222630198.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v1_masapasa_pipeline_en_5.5.0_3.0_1725222630198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_amazon_reviews_v1_masapasa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_amazon_reviews_v1_masapasa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_amazon_reviews_v1_masapasa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|437.4 MB| + +## References + +https://huggingface.co/masapasa/deberta_amazon_reviews_v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_attr_score_final_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_attr_score_final_en.md new file mode 100644 index 00000000000000..b501ef0c267dbd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_attr_score_final_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_attr_score_final DeBertaForSequenceClassification from Josef0801 +author: John Snow Labs +name: deberta_attr_score_final +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_final` is a English model originally trained by Josef0801. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_attr_score_final_en_5.5.0_3.0_1725222606020.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_final_en_5.5.0_3.0_1725222606020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_attr_score_final","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_attr_score_final", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_attr_score_final| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|665.8 MB| + +## References + +https://huggingface.co/Josef0801/deberta_attr_score_final \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_attr_score_final_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_attr_score_final_pipeline_en.md new file mode 100644 index 00000000000000..4aafe618371438 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_attr_score_final_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_attr_score_final_pipeline pipeline DeBertaForSequenceClassification from Josef0801 +author: John Snow Labs +name: deberta_attr_score_final_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_final_pipeline` is a English model originally trained by Josef0801. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_attr_score_final_pipeline_en_5.5.0_3.0_1725222651916.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_final_pipeline_en_5.5.0_3.0_1725222651916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_attr_score_final_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_attr_score_final_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_attr_score_final_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|665.8 MB| + +## References + +https://huggingface.co/Josef0801/deberta_attr_score_final + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_base_fine_tune_mnli_half_v2_labels_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_base_fine_tune_mnli_half_v2_labels_en.md new file mode 100644 index 00000000000000..9e724c3b84fda7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_base_fine_tune_mnli_half_v2_labels_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_base_fine_tune_mnli_half_v2_labels DeBertaForSequenceClassification from grace-pro +author: John Snow Labs +name: deberta_base_fine_tune_mnli_half_v2_labels +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_base_fine_tune_mnli_half_v2_labels` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_base_fine_tune_mnli_half_v2_labels_en_5.5.0_3.0_1725224285019.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_base_fine_tune_mnli_half_v2_labels_en_5.5.0_3.0_1725224285019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_base_fine_tune_mnli_half_v2_labels","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_base_fine_tune_mnli_half_v2_labels", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_base_fine_tune_mnli_half_v2_labels| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|643.4 MB| + +## References + +https://huggingface.co/grace-pro/deberta_base_fine_tune_mnli_half_v2_labels \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_base_fine_tune_mnli_half_v2_labels_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_base_fine_tune_mnli_half_v2_labels_pipeline_en.md new file mode 100644 index 00000000000000..04cc5f1ea71dbc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_base_fine_tune_mnli_half_v2_labels_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_base_fine_tune_mnli_half_v2_labels_pipeline pipeline DeBertaForSequenceClassification from grace-pro +author: John Snow Labs +name: deberta_base_fine_tune_mnli_half_v2_labels_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_base_fine_tune_mnli_half_v2_labels_pipeline` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_base_fine_tune_mnli_half_v2_labels_pipeline_en_5.5.0_3.0_1725224332168.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_base_fine_tune_mnli_half_v2_labels_pipeline_en_5.5.0_3.0_1725224332168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_base_fine_tune_mnli_half_v2_labels_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_base_fine_tune_mnli_half_v2_labels_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_base_fine_tune_mnli_half_v2_labels_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|643.4 MB| + +## References + +https://huggingface.co/grace-pro/deberta_base_fine_tune_mnli_half_v2_labels + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_classifier_feedback_1024_pseudo_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_classifier_feedback_1024_pseudo_en.md new file mode 100644 index 00000000000000..7c1b35fcd7ab66 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_classifier_feedback_1024_pseudo_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_classifier_feedback_1024_pseudo DeBertaForTokenClassification from TTian +author: John Snow Labs +name: deberta_classifier_feedback_1024_pseudo +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_classifier_feedback_1024_pseudo` is a English model originally trained by TTian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_classifier_feedback_1024_pseudo_en_5.4.2_3.0_1725195909453.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_classifier_feedback_1024_pseudo_en_5.4.2_3.0_1725195909453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_classifier_feedback_1024_pseudo","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_classifier_feedback_1024_pseudo", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_classifier_feedback_1024_pseudo| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/TTian/deberta-classifier-feedback-1024-pseudo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_classifier_feedback_1024_pseudo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_classifier_feedback_1024_pseudo_pipeline_en.md new file mode 100644 index 00000000000000..85398fe19830b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_classifier_feedback_1024_pseudo_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_classifier_feedback_1024_pseudo_pipeline pipeline DeBertaForTokenClassification from TTian +author: John Snow Labs +name: deberta_classifier_feedback_1024_pseudo_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_classifier_feedback_1024_pseudo_pipeline` is a English model originally trained by TTian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_classifier_feedback_1024_pseudo_pipeline_en_5.4.2_3.0_1725195997339.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_classifier_feedback_1024_pseudo_pipeline_en_5.4.2_3.0_1725195997339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_classifier_feedback_1024_pseudo_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_classifier_feedback_1024_pseudo_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_classifier_feedback_1024_pseudo_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/TTian/deberta-classifier-feedback-1024-pseudo + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_cowese_base_es.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_cowese_base_es.md new file mode 100644 index 00000000000000..8cb66bbd594c88 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_cowese_base_es.md @@ -0,0 +1,100 @@ +--- +layout: model +title: Spanish Deberta Embeddings model (from plncmm) +author: John Snow Labs +name: deberta_embeddings_cowese_base +date: 2024-09-01 +tags: [deberta, open_source, deberta_embeddings, debertav2formaskedlm, es, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DebertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `mdeberta-cowese-base-es` is a Spanish model originally trained by `plncmm`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_cowese_base_es_5.5.0_3.0_1725230147079.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_cowese_base_es_5.5.0_3.0_1725230147079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_cowese_base","es") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") \ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings]) + +data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_cowese_base","es") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) + +val data = Seq("I love Spark NLP").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_cowese_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|es| +|Size:|1.0 GB| + +## References + +References + +https://huggingface.co/plncmm/mdeberta-cowese-base-es \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_cowese_base_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_cowese_base_pipeline_es.md new file mode 100644 index 00000000000000..2a95ccd130f35b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_cowese_base_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish deberta_embeddings_cowese_base_pipeline pipeline DeBertaEmbeddings from plncmm +author: John Snow Labs +name: deberta_embeddings_cowese_base_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_embeddings_cowese_base_pipeline` is a Castilian, Spanish model originally trained by plncmm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_cowese_base_pipeline_es_5.5.0_3.0_1725230204254.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_cowese_base_pipeline_es_5.5.0_3.0_1725230204254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_embeddings_cowese_base_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_embeddings_cowese_base_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_cowese_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|1.0 GB| + +## References + +https://huggingface.co/plncmm/mdeberta-cowese-base-es + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_docket_language_model_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_docket_language_model_en.md new file mode 100644 index 00000000000000..52e435c755e955 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_docket_language_model_en.md @@ -0,0 +1,100 @@ +--- +layout: model +title: English Deberta Embeddings model (from scales-okn) +author: John Snow Labs +name: deberta_embeddings_docket_language_model +date: 2024-09-01 +tags: [deberta, open_source, deberta_embeddings, debertav2formaskedlm, en, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DebertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `docket-language-model` is a English model originally trained by `scales-okn`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_docket_language_model_en_5.5.0_3.0_1725230429029.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_docket_language_model_en_5.5.0_3.0_1725230429029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_docket_language_model","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") \ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings]) + +data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_docket_language_model","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) + +val data = Seq("I love Spark NLP").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_docket_language_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|1.6 GB| + +## References + +References + +https://huggingface.co/scales-okn/docket-language-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_docket_language_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_docket_language_model_pipeline_en.md new file mode 100644 index 00000000000000..67ac3b6d7104fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_docket_language_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_embeddings_docket_language_model_pipeline pipeline DeBertaEmbeddings from scales-okn +author: John Snow Labs +name: deberta_embeddings_docket_language_model_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_embeddings_docket_language_model_pipeline` is a English model originally trained by scales-okn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_docket_language_model_pipeline_en_5.5.0_3.0_1725230514265.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_docket_language_model_pipeline_en_5.5.0_3.0_1725230514265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_embeddings_docket_language_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_embeddings_docket_language_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_docket_language_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/scales-okn/docket-language-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_wl_base_es.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_wl_base_es.md new file mode 100644 index 00000000000000..5025d10c6b62d0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_wl_base_es.md @@ -0,0 +1,100 @@ +--- +layout: model +title: Spanish Deberta Embeddings model (from plncmm) +author: John Snow Labs +name: deberta_embeddings_wl_base +date: 2024-09-01 +tags: [deberta, open_source, deberta_embeddings, debertav2formaskedlm, es, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DebertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `mdeberta-wl-base-es` is a Spanish model originally trained by `plncmm`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_wl_base_es_5.5.0_3.0_1725217105926.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_wl_base_es_5.5.0_3.0_1725217105926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_wl_base","es") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") \ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings]) + +data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_wl_base","es") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) + +val data = Seq("I love Spark NLP").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_wl_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|es| +|Size:|1.0 GB| + +## References + +References + +https://huggingface.co/plncmm/mdeberta-wl-base-es \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_wl_base_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_wl_base_pipeline_es.md new file mode 100644 index 00000000000000..f3fed8d5759100 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_embeddings_wl_base_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish deberta_embeddings_wl_base_pipeline pipeline DeBertaEmbeddings from plncmm +author: John Snow Labs +name: deberta_embeddings_wl_base_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_embeddings_wl_base_pipeline` is a Castilian, Spanish model originally trained by plncmm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_wl_base_pipeline_es_5.5.0_3.0_1725217163977.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_wl_base_pipeline_es_5.5.0_3.0_1725217163977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_embeddings_wl_base_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_embeddings_wl_base_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_wl_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|1.0 GB| + +## References + +https://huggingface.co/plncmm/mdeberta-wl-base-es + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_finewebedu_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_finewebedu_en.md new file mode 100644 index 00000000000000..7c5ae73235a98d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_finewebedu_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_finewebedu DeBertaEmbeddings from agentlans +author: John Snow Labs +name: deberta_finewebedu +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_finewebedu` is a English model originally trained by agentlans. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_finewebedu_en_5.5.0_3.0_1725217270040.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_finewebedu_en_5.5.0_3.0_1725217270040.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_finewebedu","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_finewebedu","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_finewebedu| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|265.9 MB| + +## References + +https://huggingface.co/agentlans/deberta-finewebedu \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_finewebedu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_finewebedu_pipeline_en.md new file mode 100644 index 00000000000000..90efdaa565fd01 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_finewebedu_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_finewebedu_pipeline pipeline DeBertaEmbeddings from agentlans +author: John Snow Labs +name: deberta_finewebedu_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_finewebedu_pipeline` is a English model originally trained by agentlans. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_finewebedu_pipeline_en_5.5.0_3.0_1725217284645.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_finewebedu_pipeline_en_5.5.0_3.0_1725217284645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_finewebedu_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_finewebedu_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_finewebedu_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|266.0 MB| + +## References + +https://huggingface.co/agentlans/deberta-finewebedu + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_med_22feb_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_med_22feb_en.md new file mode 100644 index 00000000000000..967411d637eab8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_med_22feb_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_med_22feb DeBertaForTokenClassification from codeaze +author: John Snow Labs +name: deberta_med_22feb +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_med_22feb` is a English model originally trained by codeaze. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_med_22feb_en_5.4.2_3.0_1725197082943.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_med_22feb_en_5.4.2_3.0_1725197082943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_med_22feb","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_med_22feb", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_med_22feb| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/codeaze/deberta_med_22feb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_med_22feb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_med_22feb_pipeline_en.md new file mode 100644 index 00000000000000..ed23cb709ed8c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_med_22feb_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_med_22feb_pipeline pipeline DeBertaForTokenClassification from codeaze +author: John Snow Labs +name: deberta_med_22feb_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_med_22feb_pipeline` is a English model originally trained by codeaze. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_med_22feb_pipeline_en_5.4.2_3.0_1725197195399.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_med_22feb_pipeline_en_5.4.2_3.0_1725197195399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_med_22feb_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_med_22feb_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_med_22feb_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/codeaze/deberta_med_22feb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_mlm_test_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_mlm_test_en.md new file mode 100644 index 00000000000000..fc5c53cb471fe2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_mlm_test_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_mlm_test DeBertaEmbeddings from domenicrosati +author: John Snow Labs +name: deberta_mlm_test +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_mlm_test` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_mlm_test_en_5.5.0_3.0_1725230850864.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_mlm_test_en_5.5.0_3.0_1725230850864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_mlm_test","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_mlm_test","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_mlm_test| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|265.4 MB| + +## References + +https://huggingface.co/domenicrosati/deberta-mlm-test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_mlm_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_mlm_test_pipeline_en.md new file mode 100644 index 00000000000000..6d8b9dcc1871c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_mlm_test_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_mlm_test_pipeline pipeline DeBertaEmbeddings from domenicrosati +author: John Snow Labs +name: deberta_mlm_test_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_mlm_test_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_mlm_test_pipeline_en_5.5.0_3.0_1725230866061.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_mlm_test_pipeline_en_5.5.0_3.0_1725230866061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_mlm_test_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_mlm_test_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_mlm_test_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|265.4 MB| + +## References + +https://huggingface.co/domenicrosati/deberta-mlm-test + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_paqott_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_paqott_en.md new file mode 100644 index 00000000000000..a096ce84f05e41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_paqott_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_paqott DeBertaForQuestionAnswering from MateuszW +author: John Snow Labs +name: deberta_paqott +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_paqott` is a English model originally trained by MateuszW. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_paqott_en_5.5.0_3.0_1725218681664.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_paqott_en_5.5.0_3.0_1725218681664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_paqott","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_paqott", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_paqott| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/MateuszW/deberta-paqott \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_paqott_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_paqott_pipeline_en.md new file mode 100644 index 00000000000000..f136a75dc66719 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_paqott_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_paqott_pipeline pipeline DeBertaForQuestionAnswering from MateuszW +author: John Snow Labs +name: deberta_paqott_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_paqott_pipeline` is a English model originally trained by MateuszW. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_paqott_pipeline_en_5.5.0_3.0_1725218765642.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_paqott_pipeline_en_5.5.0_3.0_1725218765642.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_paqott_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_paqott_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_paqott_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/MateuszW/deberta-paqott + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_pii_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_pii_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..8dd310a9d4490b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_pii_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_pii_finetuned_pipeline pipeline DeBertaForTokenClassification from 1-13-am +author: John Snow Labs +name: deberta_pii_finetuned_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_pii_finetuned_pipeline` is a English model originally trained by 1-13-am. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_pii_finetuned_pipeline_en_5.4.2_3.0_1725196249423.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_pii_finetuned_pipeline_en_5.4.2_3.0_1725196249423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_pii_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_pii_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_pii_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|630.6 MB| + +## References + +https://huggingface.co/1-13-am/deberta-pii-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_squadnewsqa_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_squadnewsqa_en.md new file mode 100644 index 00000000000000..cf36a33f40815e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_squadnewsqa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_squadnewsqa DeBertaForQuestionAnswering from sophiebottani +author: John Snow Labs +name: deberta_squadnewsqa +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_squadnewsqa` is a English model originally trained by sophiebottani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_squadnewsqa_en_5.5.0_3.0_1725218227366.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_squadnewsqa_en_5.5.0_3.0_1725218227366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_squadnewsqa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_squadnewsqa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_squadnewsqa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|670.6 MB| + +## References + +https://huggingface.co/sophiebottani/deberta_squadnewsqa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_squadnewsqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_squadnewsqa_pipeline_en.md new file mode 100644 index 00000000000000..7041ecfa06c85a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_squadnewsqa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_squadnewsqa_pipeline pipeline DeBertaForQuestionAnswering from sophiebottani +author: John Snow Labs +name: deberta_squadnewsqa_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_squadnewsqa_pipeline` is a English model originally trained by sophiebottani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_squadnewsqa_pipeline_en_5.5.0_3.0_1725218264593.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_squadnewsqa_pipeline_en_5.5.0_3.0_1725218264593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_squadnewsqa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_squadnewsqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_squadnewsqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|670.6 MB| + +## References + +https://huggingface.co/sophiebottani/deberta_squadnewsqa + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_base_japanese_finetuned_qae_ja.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_base_japanese_finetuned_qae_ja.md new file mode 100644 index 00000000000000..7e914dd2331ebb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_base_japanese_finetuned_qae_ja.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Japanese deberta_v2_base_japanese_finetuned_qae DeBertaForQuestionAnswering from Mizuiro-sakura +author: John Snow Labs +name: deberta_v2_base_japanese_finetuned_qae +date: 2024-09-01 +tags: [ja, open_source, onnx, question_answering, deberta] +task: Question Answering +language: ja +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_base_japanese_finetuned_qae` is a Japanese model originally trained by Mizuiro-sakura. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_base_japanese_finetuned_qae_ja_5.5.0_3.0_1725220727214.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_base_japanese_finetuned_qae_ja_5.5.0_3.0_1725220727214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v2_base_japanese_finetuned_qae","ja") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v2_base_japanese_finetuned_qae", "ja") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v2_base_japanese_finetuned_qae| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|ja| +|Size:|419.0 MB| + +## References + +https://huggingface.co/Mizuiro-sakura/deberta-v2-base-japanese-finetuned-QAe \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_base_japanese_finetuned_qae_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_base_japanese_finetuned_qae_pipeline_ja.md new file mode 100644 index 00000000000000..07643df51e9fd1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_base_japanese_finetuned_qae_pipeline_ja.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Japanese deberta_v2_base_japanese_finetuned_qae_pipeline pipeline DeBertaForQuestionAnswering from Mizuiro-sakura +author: John Snow Labs +name: deberta_v2_base_japanese_finetuned_qae_pipeline +date: 2024-09-01 +tags: [ja, open_source, pipeline, onnx] +task: Question Answering +language: ja +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_base_japanese_finetuned_qae_pipeline` is a Japanese model originally trained by Mizuiro-sakura. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_base_japanese_finetuned_qae_pipeline_ja_5.5.0_3.0_1725220749383.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_base_japanese_finetuned_qae_pipeline_ja_5.5.0_3.0_1725220749383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v2_base_japanese_finetuned_qae_pipeline", lang = "ja") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v2_base_japanese_finetuned_qae_pipeline", lang = "ja") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v2_base_japanese_finetuned_qae_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ja| +|Size:|419.0 MB| + +## References + +https://huggingface.co/Mizuiro-sakura/deberta-v2-base-japanese-finetuned-QAe + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_large_conll2003_inca_v1_retrained_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_large_conll2003_inca_v1_retrained_en.md new file mode 100644 index 00000000000000..d3c06421da0140 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_large_conll2003_inca_v1_retrained_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v2_large_conll2003_inca_v1_retrained DeBertaForTokenClassification from Yanis +author: John Snow Labs +name: deberta_v2_large_conll2003_inca_v1_retrained +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_large_conll2003_inca_v1_retrained` is a English model originally trained by Yanis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_large_conll2003_inca_v1_retrained_en_5.4.2_3.0_1725196033814.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_large_conll2003_inca_v1_retrained_en_5.4.2_3.0_1725196033814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v2_large_conll2003_inca_v1_retrained","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v2_large_conll2003_inca_v1_retrained", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v2_large_conll2003_inca_v1_retrained| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/Yanis/deberta-v2-large-conll2003-inca_v1_retrained \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_large_conll2003_inca_v1_retrained_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_large_conll2003_inca_v1_retrained_pipeline_en.md new file mode 100644 index 00000000000000..70cb4915f666ea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_large_conll2003_inca_v1_retrained_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v2_large_conll2003_inca_v1_retrained_pipeline pipeline DeBertaForTokenClassification from Yanis +author: John Snow Labs +name: deberta_v2_large_conll2003_inca_v1_retrained_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_large_conll2003_inca_v1_retrained_pipeline` is a English model originally trained by Yanis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_large_conll2003_inca_v1_retrained_pipeline_en_5.4.2_3.0_1725196125369.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_large_conll2003_inca_v1_retrained_pipeline_en_5.4.2_3.0_1725196125369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v2_large_conll2003_inca_v1_retrained_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v2_large_conll2003_inca_v1_retrained_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v2_large_conll2003_inca_v1_retrained_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/Yanis/deberta-v2-large-conll2003-inca_v1_retrained + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_large_japanese_finetuned_wrime_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_large_japanese_finetuned_wrime_en.md new file mode 100644 index 00000000000000..b5d125e1239b41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_large_japanese_finetuned_wrime_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v2_large_japanese_finetuned_wrime DeBertaForSequenceClassification from MuneK +author: John Snow Labs +name: deberta_v2_large_japanese_finetuned_wrime +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_large_japanese_finetuned_wrime` is a English model originally trained by MuneK. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_large_japanese_finetuned_wrime_en_5.5.0_3.0_1725210079097.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_large_japanese_finetuned_wrime_en_5.5.0_3.0_1725210079097.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v2_large_japanese_finetuned_wrime","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v2_large_japanese_finetuned_wrime", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v2_large_japanese_finetuned_wrime| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/MuneK/deberta-v2-large-japanese-finetuned-wrime \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_large_japanese_finetuned_wrime_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_large_japanese_finetuned_wrime_pipeline_en.md new file mode 100644 index 00000000000000..0c7ee91d4ba19b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v2_large_japanese_finetuned_wrime_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v2_large_japanese_finetuned_wrime_pipeline pipeline DeBertaForSequenceClassification from MuneK +author: John Snow Labs +name: deberta_v2_large_japanese_finetuned_wrime_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_large_japanese_finetuned_wrime_pipeline` is a English model originally trained by MuneK. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_large_japanese_finetuned_wrime_pipeline_en_5.5.0_3.0_1725210157309.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_large_japanese_finetuned_wrime_pipeline_en_5.5.0_3.0_1725210157309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v2_large_japanese_finetuned_wrime_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v2_large_japanese_finetuned_wrime_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v2_large_japanese_finetuned_wrime_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/MuneK/deberta-v2-large-japanese-finetuned-wrime + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_10xp3nirstbbflan_10xc4_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_10xp3nirstbbflan_10xc4_en.md new file mode 100644 index 00000000000000..df73ced69cdb49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_10xp3nirstbbflan_10xc4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_10xp3nirstbbflan_10xc4 DeBertaForSequenceClassification from taskydata +author: John Snow Labs +name: deberta_v3_base_10xp3nirstbbflan_10xc4 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_10xp3nirstbbflan_10xc4` is a English model originally trained by taskydata. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_10xp3nirstbbflan_10xc4_en_5.5.0_3.0_1725222979909.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_10xp3nirstbbflan_10xc4_en_5.5.0_3.0_1725222979909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_10xp3nirstbbflan_10xc4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_10xp3nirstbbflan_10xc4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_10xp3nirstbbflan_10xc4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|690.2 MB| + +## References + +https://huggingface.co/taskydata/deberta-v3-base_10xp3nirstbbflan_10xc4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_10xp3nirstbbflan_10xc4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_10xp3nirstbbflan_10xc4_pipeline_en.md new file mode 100644 index 00000000000000..1edcda7f1c9f2e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_10xp3nirstbbflan_10xc4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_10xp3nirstbbflan_10xc4_pipeline pipeline DeBertaForSequenceClassification from taskydata +author: John Snow Labs +name: deberta_v3_base_10xp3nirstbbflan_10xc4_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_10xp3nirstbbflan_10xc4_pipeline` is a English model originally trained by taskydata. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_10xp3nirstbbflan_10xc4_pipeline_en_5.5.0_3.0_1725223017558.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_10xp3nirstbbflan_10xc4_pipeline_en_5.5.0_3.0_1725223017558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_10xp3nirstbbflan_10xc4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_10xp3nirstbbflan_10xc4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_10xp3nirstbbflan_10xc4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|690.2 MB| + +## References + +https://huggingface.co/taskydata/deberta-v3-base_10xp3nirstbbflan_10xc4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_amazon_reviews_multi_fp16_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_amazon_reviews_multi_fp16_en.md new file mode 100644 index 00000000000000..5ae9856facadab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_amazon_reviews_multi_fp16_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_amazon_reviews_multi_fp16 DeBertaForSequenceClassification from thainq107 +author: John Snow Labs +name: deberta_v3_base_amazon_reviews_multi_fp16 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_amazon_reviews_multi_fp16` is a English model originally trained by thainq107. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_amazon_reviews_multi_fp16_en_5.5.0_3.0_1725222478130.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_amazon_reviews_multi_fp16_en_5.5.0_3.0_1725222478130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_amazon_reviews_multi_fp16","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_amazon_reviews_multi_fp16", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_amazon_reviews_multi_fp16| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|621.2 MB| + +## References + +https://huggingface.co/thainq107/deberta-v3-base-amazon-reviews-multi-fp16 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_amazon_reviews_multi_fp16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_amazon_reviews_multi_fp16_pipeline_en.md new file mode 100644 index 00000000000000..5485fe20231531 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_amazon_reviews_multi_fp16_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_amazon_reviews_multi_fp16_pipeline pipeline DeBertaForSequenceClassification from thainq107 +author: John Snow Labs +name: deberta_v3_base_amazon_reviews_multi_fp16_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_amazon_reviews_multi_fp16_pipeline` is a English model originally trained by thainq107. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_amazon_reviews_multi_fp16_pipeline_en_5.5.0_3.0_1725222539515.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_amazon_reviews_multi_fp16_pipeline_en_5.5.0_3.0_1725222539515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_amazon_reviews_multi_fp16_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_amazon_reviews_multi_fp16_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_amazon_reviews_multi_fp16_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|621.2 MB| + +## References + +https://huggingface.co/thainq107/deberta-v3-base-amazon-reviews-multi-fp16 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_company_names_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_company_names_pipeline_en.md new file mode 100644 index 00000000000000..9c6e156a9c5308 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_company_names_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_company_names_pipeline pipeline DeBertaForTokenClassification from nbroad +author: John Snow Labs +name: deberta_v3_base_company_names_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_company_names_pipeline` is a English model originally trained by nbroad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_company_names_pipeline_en_5.4.2_3.0_1725197591257.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_company_names_pipeline_en_5.4.2_3.0_1725197591257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_company_names_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_company_names_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_company_names_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|661.8 MB| + +## References + +https://huggingface.co/nbroad/deberta-v3-base-company-names + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_cotat_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_cotat_en.md new file mode 100644 index 00000000000000..042fbc685b0905 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_cotat_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_cotat DeBertaForSequenceClassification from DandinPower +author: John Snow Labs +name: deberta_v3_base_cotat +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_cotat` is a English model originally trained by DandinPower. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_cotat_en_5.4.2_3.0_1725184004482.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_cotat_en_5.4.2_3.0_1725184004482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_cotat","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_cotat", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_cotat| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|600.7 MB| + +## References + +https://huggingface.co/DandinPower/deberta-v3-base-cotat \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_custom_v2_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_custom_v2_en.md new file mode 100644 index 00000000000000..7212d0949d4797 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_custom_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_custom_v2 DeBertaForSequenceClassification from sami1616 +author: John Snow Labs +name: deberta_v3_base_custom_v2 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_custom_v2` is a English model originally trained by sami1616. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_custom_v2_en_5.5.0_3.0_1725209492248.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_custom_v2_en_5.5.0_3.0_1725209492248.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_custom_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_custom_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_custom_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|589.6 MB| + +## References + +https://huggingface.co/sami1616/deberta-v3-base-custom-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_custom_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_custom_v2_pipeline_en.md new file mode 100644 index 00000000000000..f4cac0b2afeb76 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_custom_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_custom_v2_pipeline pipeline DeBertaForSequenceClassification from sami1616 +author: John Snow Labs +name: deberta_v3_base_custom_v2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_custom_v2_pipeline` is a English model originally trained by sami1616. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_custom_v2_pipeline_en_5.5.0_3.0_1725209540388.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_custom_v2_pipeline_en_5.5.0_3.0_1725209540388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_custom_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_custom_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_custom_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|589.7 MB| + +## References + +https://huggingface.co/sami1616/deberta-v3-base-custom-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_financial_question_classification_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_financial_question_classification_en.md new file mode 100644 index 00000000000000..c6f18c751dc784 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_financial_question_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_financial_question_classification DeBertaForSequenceClassification from nogae +author: John Snow Labs +name: deberta_v3_base_financial_question_classification +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_financial_question_classification` is a English model originally trained by nogae. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_financial_question_classification_en_5.5.0_3.0_1725222263368.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_financial_question_classification_en_5.5.0_3.0_1725222263368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_financial_question_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_financial_question_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_financial_question_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|688.9 MB| + +## References + +https://huggingface.co/nogae/deberta-v3-base-financial-question-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_financial_question_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_financial_question_classification_pipeline_en.md new file mode 100644 index 00000000000000..c90f9d28f18ba1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_financial_question_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_financial_question_classification_pipeline pipeline DeBertaForSequenceClassification from nogae +author: John Snow Labs +name: deberta_v3_base_financial_question_classification_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_financial_question_classification_pipeline` is a English model originally trained by nogae. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_financial_question_classification_pipeline_en_5.5.0_3.0_1725222300594.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_financial_question_classification_pipeline_en_5.5.0_3.0_1725222300594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_financial_question_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_financial_question_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_financial_question_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|688.9 MB| + +## References + +https://huggingface.co/nogae/deberta-v3-base-financial-question-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_fine_tuned_food_ner_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_fine_tuned_food_ner_en.md new file mode 100644 index 00000000000000..dfc2fdb9a73d0e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_fine_tuned_food_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_fine_tuned_food_ner DeBertaForTokenClassification from davanstrien +author: John Snow Labs +name: deberta_v3_base_fine_tuned_food_ner +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_fine_tuned_food_ner` is a English model originally trained by davanstrien. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_fine_tuned_food_ner_en_5.5.0_3.0_1725233016829.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_fine_tuned_food_ner_en_5.5.0_3.0_1725233016829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_fine_tuned_food_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_fine_tuned_food_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_fine_tuned_food_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|576.5 MB| + +## References + +https://huggingface.co/davanstrien/deberta-v3-base_fine_tuned_food_ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_fine_tuned_food_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_fine_tuned_food_ner_pipeline_en.md new file mode 100644 index 00000000000000..65d7e2665277fa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_fine_tuned_food_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_fine_tuned_food_ner_pipeline pipeline DeBertaForTokenClassification from davanstrien +author: John Snow Labs +name: deberta_v3_base_fine_tuned_food_ner_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_fine_tuned_food_ner_pipeline` is a English model originally trained by davanstrien. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_fine_tuned_food_ner_pipeline_en_5.5.0_3.0_1725233073036.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_fine_tuned_food_ner_pipeline_en_5.5.0_3.0_1725233073036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_fine_tuned_food_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_fine_tuned_food_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_fine_tuned_food_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|576.5 MB| + +## References + +https://huggingface.co/davanstrien/deberta-v3-base_fine_tuned_food_ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_finetuned_squadv2_en.md new file mode 100644 index 00000000000000..72d3f62b1eca08 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_finetuned_squadv2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_base_finetuned_squadv2 DeBertaForQuestionAnswering from mrm8488 +author: John Snow Labs +name: deberta_v3_base_finetuned_squadv2 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_squadv2` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_squadv2_en_5.5.0_3.0_1725218678315.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_squadv2_en_5.5.0_3.0_1725218678315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_finetuned_squadv2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_finetuned_squadv2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_finetuned_squadv2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|644.5 MB| + +## References + +https://huggingface.co/mrm8488/deberta-v3-base-finetuned-squadv2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_finetuned_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_finetuned_squadv2_pipeline_en.md new file mode 100644 index 00000000000000..1843cfa1d93ec1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_finetuned_squadv2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_base_finetuned_squadv2_pipeline pipeline DeBertaForQuestionAnswering from mrm8488 +author: John Snow Labs +name: deberta_v3_base_finetuned_squadv2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_squadv2_pipeline` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_squadv2_pipeline_en_5.5.0_3.0_1725218730125.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_squadv2_pipeline_en_5.5.0_3.0_1725218730125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_finetuned_squadv2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_finetuned_squadv2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_finetuned_squadv2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|644.5 MB| + +## References + +https://huggingface.co/mrm8488/deberta-v3-base-finetuned-squadv2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_finetuned_sst2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_finetuned_sst2_pipeline_en.md new file mode 100644 index 00000000000000..f0da26b3c37143 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_finetuned_sst2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_finetuned_sst2_pipeline pipeline DeBertaForSequenceClassification from vroomhf +author: John Snow Labs +name: deberta_v3_base_finetuned_sst2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_sst2_pipeline` is a English model originally trained by vroomhf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_sst2_pipeline_en_5.4.2_3.0_1725182025238.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_sst2_pipeline_en_5.4.2_3.0_1725182025238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_finetuned_sst2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_finetuned_sst2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_finetuned_sst2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|586.4 MB| + +## References + +https://huggingface.co/vroomhf/deberta-v3-base-finetuned-sst2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_injection_deepset_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_injection_deepset_en.md new file mode 100644 index 00000000000000..bdfec373273664 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_injection_deepset_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_injection_deepset DeBertaForSequenceClassification from deepset +author: John Snow Labs +name: deberta_v3_base_injection_deepset +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_injection_deepset` is a English model originally trained by deepset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_injection_deepset_en_5.5.0_3.0_1725209160531.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_injection_deepset_en_5.5.0_3.0_1725209160531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_injection_deepset","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_injection_deepset", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_injection_deepset| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|578.9 MB| + +## References + +https://huggingface.co/deepset/deberta-v3-base-injection \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_injection_deepset_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_injection_deepset_pipeline_en.md new file mode 100644 index 00000000000000..f361544285d7b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_injection_deepset_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_injection_deepset_pipeline pipeline DeBertaForSequenceClassification from deepset +author: John Snow Labs +name: deberta_v3_base_injection_deepset_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_injection_deepset_pipeline` is a English model originally trained by deepset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_injection_deepset_pipeline_en_5.5.0_3.0_1725209208947.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_injection_deepset_pipeline_en_5.5.0_3.0_1725209208947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_injection_deepset_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_injection_deepset_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_injection_deepset_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|578.9 MB| + +## References + +https://huggingface.co/deepset/deberta-v3-base-injection + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_mrqa_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_mrqa_en.md new file mode 100644 index 00000000000000..d6af8e16c5f2cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_mrqa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_base_mrqa DeBertaForQuestionAnswering from VMware +author: John Snow Labs +name: deberta_v3_base_mrqa +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_mrqa` is a English model originally trained by VMware. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mrqa_en_5.5.0_3.0_1725218760387.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mrqa_en_5.5.0_3.0_1725218760387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_mrqa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_mrqa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_mrqa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|688.1 MB| + +## References + +https://huggingface.co/VMware/deberta-v3-base-mrqa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_mrqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_mrqa_pipeline_en.md new file mode 100644 index 00000000000000..dec1ebd4c32bd6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_mrqa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_base_mrqa_pipeline pipeline DeBertaForQuestionAnswering from VMware +author: John Snow Labs +name: deberta_v3_base_mrqa_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_mrqa_pipeline` is a English model originally trained by VMware. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mrqa_pipeline_en_5.5.0_3.0_1725218797522.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mrqa_pipeline_en_5.5.0_3.0_1725218797522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_mrqa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_mrqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_mrqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|688.1 MB| + +## References + +https://huggingface.co/VMware/deberta-v3-base-mrqa + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_ner_a_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_ner_a_en.md new file mode 100644 index 00000000000000..13f5426a033453 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_ner_a_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_ner_a DeBertaForTokenClassification from alexeyak +author: John Snow Labs +name: deberta_v3_base_ner_a +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_ner_a` is a English model originally trained by alexeyak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_ner_a_en_5.5.0_3.0_1725233215057.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_ner_a_en_5.5.0_3.0_1725233215057.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_ner_a","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_ner_a", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_ner_a| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|656.9 MB| + +## References + +https://huggingface.co/alexeyak/deberta-v3-base-ner-A \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_ner_a_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_ner_a_pipeline_en.md new file mode 100644 index 00000000000000..fedd1e385dcd01 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_ner_a_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_ner_a_pipeline pipeline DeBertaForTokenClassification from alexeyak +author: John Snow Labs +name: deberta_v3_base_ner_a_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_ner_a_pipeline` is a English model originally trained by alexeyak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_ner_a_pipeline_en_5.5.0_3.0_1725233257807.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_ner_a_pipeline_en_5.5.0_3.0_1725233257807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_ner_a_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_ner_a_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_ner_a_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|656.9 MB| + +## References + +https://huggingface.co/alexeyak/deberta-v3-base-ner-A + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_nli_mixer_binary_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_nli_mixer_binary_en.md new file mode 100644 index 00000000000000..e959d3cfa0eae0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_nli_mixer_binary_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_nli_mixer_binary DeBertaForSequenceClassification from ragarwal +author: John Snow Labs +name: deberta_v3_base_nli_mixer_binary +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_nli_mixer_binary` is a English model originally trained by ragarwal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_nli_mixer_binary_en_5.4.2_3.0_1725181605991.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_nli_mixer_binary_en_5.4.2_3.0_1725181605991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_nli_mixer_binary","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_nli_mixer_binary", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_nli_mixer_binary| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|687.5 MB| + +## References + +https://huggingface.co/ragarwal/deberta-v3-base-nli-mixer-binary \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_on5_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_on5_en.md new file mode 100644 index 00000000000000..1dcec9992eb784 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_on5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_on5 DeBertaForTokenClassification from lambdavi +author: John Snow Labs +name: deberta_v3_base_on5 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_on5` is a English model originally trained by lambdavi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_on5_en_5.5.0_3.0_1725233231309.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_on5_en_5.5.0_3.0_1725233231309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_on5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_on5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_on5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|601.7 MB| + +## References + +https://huggingface.co/lambdavi/deberta-v3-base_on5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_on5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_on5_pipeline_en.md new file mode 100644 index 00000000000000..fa65268ffcaa10 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_on5_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_on5_pipeline pipeline DeBertaForTokenClassification from lambdavi +author: John Snow Labs +name: deberta_v3_base_on5_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_on5_pipeline` is a English model originally trained by lambdavi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_on5_pipeline_en_5.5.0_3.0_1725233299673.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_on5_pipeline_en_5.5.0_3.0_1725233299673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_on5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_on5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_on5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|601.7 MB| + +## References + +https://huggingface.co/lambdavi/deberta-v3-base_on5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_open_ner_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_open_ner_en.md new file mode 100644 index 00000000000000..565ba47374eeb7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_open_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_open_ner DeBertaForTokenClassification from yongsun-yoon +author: John Snow Labs +name: deberta_v3_base_open_ner +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_open_ner` is a English model originally trained by yongsun-yoon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_open_ner_en_5.5.0_3.0_1725232694634.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_open_ner_en_5.5.0_3.0_1725232694634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_open_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_open_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_open_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|676.3 MB| + +## References + +https://huggingface.co/yongsun-yoon/deberta-v3-base-open-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_open_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_open_ner_pipeline_en.md new file mode 100644 index 00000000000000..88e70d31251d9a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_open_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_open_ner_pipeline pipeline DeBertaForTokenClassification from yongsun-yoon +author: John Snow Labs +name: deberta_v3_base_open_ner_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_open_ner_pipeline` is a English model originally trained by yongsun-yoon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_open_ner_pipeline_en_5.5.0_3.0_1725232734904.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_open_ner_pipeline_en_5.5.0_3.0_1725232734904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_open_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_open_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_open_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|676.3 MB| + +## References + +https://huggingface.co/yongsun-yoon/deberta-v3-base-open-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_optimus_v0_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_optimus_v0_en.md new file mode 100644 index 00000000000000..6dc063d2b002ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_optimus_v0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_optimus_v0 DeBertaForSequenceClassification from vibraniumdome +author: John Snow Labs +name: deberta_v3_base_optimus_v0 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_optimus_v0` is a English model originally trained by vibraniumdome. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_optimus_v0_en_5.4.2_3.0_1725183359685.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_optimus_v0_en_5.4.2_3.0_1725183359685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_optimus_v0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_optimus_v0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_optimus_v0| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|590.7 MB| + +## References + +https://huggingface.co/vibraniumdome/deberta-v3-base-optimus-v0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v1_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v1_en.md new file mode 100644 index 00000000000000..66628e4637bd8f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_orgs_v1 DeBertaForTokenClassification from nbroad +author: John Snow Labs +name: deberta_v3_base_orgs_v1 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_orgs_v1` is a English model originally trained by nbroad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_orgs_v1_en_5.4.2_3.0_1725195722897.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_orgs_v1_en_5.4.2_3.0_1725195722897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_orgs_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_orgs_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_orgs_v1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|661.6 MB| + +## References + +https://huggingface.co/nbroad/deberta-v3-base-orgs-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v1_pipeline_en.md new file mode 100644 index 00000000000000..51ae908d775682 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_orgs_v1_pipeline pipeline DeBertaForTokenClassification from nbroad +author: John Snow Labs +name: deberta_v3_base_orgs_v1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_orgs_v1_pipeline` is a English model originally trained by nbroad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_orgs_v1_pipeline_en_5.4.2_3.0_1725195761968.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_orgs_v1_pipeline_en_5.4.2_3.0_1725195761968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_orgs_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_orgs_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_orgs_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|661.6 MB| + +## References + +https://huggingface.co/nbroad/deberta-v3-base-orgs-v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v2_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v2_en.md new file mode 100644 index 00000000000000..df2056371201ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_orgs_v2 DeBertaForTokenClassification from nbroad +author: John Snow Labs +name: deberta_v3_base_orgs_v2 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_orgs_v2` is a English model originally trained by nbroad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_orgs_v2_en_5.4.2_3.0_1725197055037.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_orgs_v2_en_5.4.2_3.0_1725197055037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_orgs_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_orgs_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_orgs_v2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|661.6 MB| + +## References + +https://huggingface.co/nbroad/deberta-v3-base-orgs-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v2_pipeline_en.md new file mode 100644 index 00000000000000..670b3cf07a138f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_orgs_v2_pipeline pipeline DeBertaForTokenClassification from nbroad +author: John Snow Labs +name: deberta_v3_base_orgs_v2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_orgs_v2_pipeline` is a English model originally trained by nbroad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_orgs_v2_pipeline_en_5.4.2_3.0_1725197094033.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_orgs_v2_pipeline_en_5.4.2_3.0_1725197094033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_orgs_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_orgs_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_orgs_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|661.6 MB| + +## References + +https://huggingface.co/nbroad/deberta-v3-base-orgs-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v3_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v3_en.md new file mode 100644 index 00000000000000..bbe0293dc43d74 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_orgs_v3 DeBertaForTokenClassification from nbroad +author: John Snow Labs +name: deberta_v3_base_orgs_v3 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_orgs_v3` is a English model originally trained by nbroad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_orgs_v3_en_5.5.0_3.0_1725233015188.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_orgs_v3_en_5.5.0_3.0_1725233015188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_orgs_v3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_orgs_v3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_orgs_v3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|661.1 MB| + +## References + +https://huggingface.co/nbroad/deberta-v3-base-orgs-v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v3_pipeline_en.md new file mode 100644 index 00000000000000..ab56b248b10f81 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_orgs_v3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_orgs_v3_pipeline pipeline DeBertaForTokenClassification from nbroad +author: John Snow Labs +name: deberta_v3_base_orgs_v3_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_orgs_v3_pipeline` is a English model originally trained by nbroad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_orgs_v3_pipeline_en_5.5.0_3.0_1725233058939.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_orgs_v3_pipeline_en_5.5.0_3.0_1725233058939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_orgs_v3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_orgs_v3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_orgs_v3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|661.1 MB| + +## References + +https://huggingface.co/nbroad/deberta-v3-base-orgs-v3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_qa_english_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_qa_english_en.md new file mode 100644 index 00000000000000..975f6e3cb09326 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_qa_english_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_base_qa_english DeBertaForQuestionAnswering from LLukas22 +author: John Snow Labs +name: deberta_v3_base_qa_english +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_qa_english` is a English model originally trained by LLukas22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_qa_english_en_5.5.0_3.0_1725219075677.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_qa_english_en_5.5.0_3.0_1725219075677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_qa_english","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_qa_english", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_qa_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|677.4 MB| + +## References + +https://huggingface.co/LLukas22/deberta-v3-base-qa-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_qa_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_qa_english_pipeline_en.md new file mode 100644 index 00000000000000..d0028370c3ba29 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_qa_english_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_base_qa_english_pipeline pipeline DeBertaForQuestionAnswering from LLukas22 +author: John Snow Labs +name: deberta_v3_base_qa_english_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_qa_english_pipeline` is a English model originally trained by LLukas22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_qa_english_pipeline_en_5.5.0_3.0_1725219120110.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_qa_english_pipeline_en_5.5.0_3.0_1725219120110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_qa_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_qa_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_qa_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|677.4 MB| + +## References + +https://huggingface.co/LLukas22/deberta-v3-base-qa-en + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_qqp_cliang1453_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_qqp_cliang1453_en.md new file mode 100644 index 00000000000000..77501bf9f3800c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_qqp_cliang1453_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_qqp_cliang1453 DeBertaForSequenceClassification from cliang1453 +author: John Snow Labs +name: deberta_v3_base_qqp_cliang1453 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_qqp_cliang1453` is a English model originally trained by cliang1453. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_qqp_cliang1453_en_5.5.0_3.0_1725208720939.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_qqp_cliang1453_en_5.5.0_3.0_1725208720939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_qqp_cliang1453","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_qqp_cliang1453", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_qqp_cliang1453| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|648.9 MB| + +## References + +https://huggingface.co/cliang1453/deberta-v3-base-qqp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_qqp_cliang1453_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_qqp_cliang1453_pipeline_en.md new file mode 100644 index 00000000000000..f49b78a5487da3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_qqp_cliang1453_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_qqp_cliang1453_pipeline pipeline DeBertaForSequenceClassification from cliang1453 +author: John Snow Labs +name: deberta_v3_base_qqp_cliang1453_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_qqp_cliang1453_pipeline` is a English model originally trained by cliang1453. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_qqp_cliang1453_pipeline_en_5.5.0_3.0_1725208770990.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_qqp_cliang1453_pipeline_en_5.5.0_3.0_1725208770990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_qqp_cliang1453_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_qqp_cliang1453_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_qqp_cliang1453_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|648.9 MB| + +## References + +https://huggingface.co/cliang1453/deberta-v3-base-qqp + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_reward_model_0102_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_reward_model_0102_en.md new file mode 100644 index 00000000000000..8c2e53105fd929 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_reward_model_0102_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_reward_model_0102 DeBertaForSequenceClassification from decem +author: John Snow Labs +name: deberta_v3_base_reward_model_0102 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_reward_model_0102` is a English model originally trained by decem. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_reward_model_0102_en_5.5.0_3.0_1725222797001.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_reward_model_0102_en_5.5.0_3.0_1725222797001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_reward_model_0102","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_reward_model_0102", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_reward_model_0102| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|644.5 MB| + +## References + +https://huggingface.co/decem/deberta-v3-base-reward-model-0102 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_reward_model_0102_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_reward_model_0102_pipeline_en.md new file mode 100644 index 00000000000000..dddf65e53afd25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_reward_model_0102_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_reward_model_0102_pipeline pipeline DeBertaForSequenceClassification from decem +author: John Snow Labs +name: deberta_v3_base_reward_model_0102_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_reward_model_0102_pipeline` is a English model originally trained by decem. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_reward_model_0102_pipeline_en_5.5.0_3.0_1725222852656.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_reward_model_0102_pipeline_en_5.5.0_3.0_1725222852656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_reward_model_0102_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_reward_model_0102_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_reward_model_0102_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|644.5 MB| + +## References + +https://huggingface.co/decem/deberta-v3-base-reward-model-0102 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_rotten_tomatoes_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_rotten_tomatoes_en.md new file mode 100644 index 00000000000000..b3c7484d5d9f97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_rotten_tomatoes_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_rotten_tomatoes DeBertaForSequenceClassification from marcelomoreno26 +author: John Snow Labs +name: deberta_v3_base_rotten_tomatoes +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_rotten_tomatoes` is a English model originally trained by marcelomoreno26. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_rotten_tomatoes_en_5.5.0_3.0_1725224053349.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_rotten_tomatoes_en_5.5.0_3.0_1725224053349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_rotten_tomatoes","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_rotten_tomatoes", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_rotten_tomatoes| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|577.5 MB| + +## References + +https://huggingface.co/marcelomoreno26/deberta-v3-base-rotten-tomatoes \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_rotten_tomatoes_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_rotten_tomatoes_pipeline_en.md new file mode 100644 index 00000000000000..e8c28f968a7abc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_rotten_tomatoes_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_rotten_tomatoes_pipeline pipeline DeBertaForSequenceClassification from marcelomoreno26 +author: John Snow Labs +name: deberta_v3_base_rotten_tomatoes_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_rotten_tomatoes_pipeline` is a English model originally trained by marcelomoreno26. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_rotten_tomatoes_pipeline_en_5.5.0_3.0_1725224133395.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_rotten_tomatoes_pipeline_en_5.5.0_3.0_1725224133395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_rotten_tomatoes_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_rotten_tomatoes_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_rotten_tomatoes_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|577.5 MB| + +## References + +https://huggingface.co/marcelomoreno26/deberta-v3-base-rotten-tomatoes + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_squad2_navteca_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_squad2_navteca_en.md new file mode 100644 index 00000000000000..205df8b074ec1b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_squad2_navteca_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_base_squad2_navteca DeBertaForQuestionAnswering from navteca +author: John Snow Labs +name: deberta_v3_base_squad2_navteca +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_squad2_navteca` is a English model originally trained by navteca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_navteca_en_5.5.0_3.0_1725219485532.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_navteca_en_5.5.0_3.0_1725219485532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_squad2_navteca","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_squad2_navteca", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_squad2_navteca| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|651.0 MB| + +## References + +https://huggingface.co/navteca/deberta-v3-base-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_squad2_navteca_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_squad2_navteca_pipeline_en.md new file mode 100644 index 00000000000000..94c5faa351609f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_squad2_navteca_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_base_squad2_navteca_pipeline pipeline DeBertaForQuestionAnswering from navteca +author: John Snow Labs +name: deberta_v3_base_squad2_navteca_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_squad2_navteca_pipeline` is a English model originally trained by navteca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_navteca_pipeline_en_5.5.0_3.0_1725219531092.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_navteca_pipeline_en_5.5.0_3.0_1725219531092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_squad2_navteca_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_squad2_navteca_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_squad2_navteca_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|651.1 MB| + +## References + +https://huggingface.co/navteca/deberta-v3-base-squad2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_survey_combined_rater_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_survey_combined_rater_en.md new file mode 100644 index 00000000000000..63414d50a02fa9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_survey_combined_rater_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_survey_combined_rater DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_base_survey_combined_rater +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_survey_combined_rater` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_survey_combined_rater_en_5.5.0_3.0_1725223132329.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_survey_combined_rater_en_5.5.0_3.0_1725223132329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_survey_combined_rater","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_survey_combined_rater", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_survey_combined_rater| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|611.3 MB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-base-survey-combined-rater \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_survey_combined_rater_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_survey_combined_rater_pipeline_en.md new file mode 100644 index 00000000000000..1a4c103d9def08 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_survey_combined_rater_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_survey_combined_rater_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_base_survey_combined_rater_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_survey_combined_rater_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_survey_combined_rater_pipeline_en_5.5.0_3.0_1725223181077.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_survey_combined_rater_pipeline_en_5.5.0_3.0_1725223181077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_survey_combined_rater_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_survey_combined_rater_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_survey_combined_rater_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|611.4 MB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-base-survey-combined-rater + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_en.md new file mode 100644 index 00000000000000..b8ac3237bd6b38 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_en_5.5.0_3.0_1725223454435.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_en_5.5.0_3.0_1725223454435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|610.1 MB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-base-survey-new_fact_main_passage-rater \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_pipeline_en.md new file mode 100644 index 00000000000000..b0a8e9024ca723 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_pipeline_en_5.5.0_3.0_1725223508919.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_pipeline_en_5.5.0_3.0_1725223508919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_survey_nepal_bhasa_fact_main_passage_rater_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|610.1 MB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-base-survey-new_fact_main_passage-rater + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_dnli_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_dnli_en.md new file mode 100644 index 00000000000000..93ba1b721e3f43 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_dnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_dnli DeBertaForSequenceClassification from zayn1111 +author: John Snow Labs +name: deberta_v3_dnli +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_dnli` is a English model originally trained by zayn1111. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_dnli_en_5.4.2_3.0_1725182956839.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_dnli_en_5.4.2_3.0_1725182956839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_dnli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_dnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_dnli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/zayn1111/deberta-v3-dnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_16_1_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_16_1_en.md new file mode 100644 index 00000000000000..210d7ee996fc4b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_16_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large__sst2__train_16_1 DeBertaForSequenceClassification from SetFit +author: John Snow Labs +name: deberta_v3_large__sst2__train_16_1 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_16_1` is a English model originally trained by SetFit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_1_en_5.5.0_3.0_1725209069283.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_1_en_5.5.0_3.0_1725209069283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_16_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_16_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large__sst2__train_16_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/SetFit/deberta-v3-large__sst2__train-16-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_16_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_16_1_pipeline_en.md new file mode 100644 index 00000000000000..5f80e2c110f9e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_16_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large__sst2__train_16_1_pipeline pipeline DeBertaForSequenceClassification from SetFit +author: John Snow Labs +name: deberta_v3_large__sst2__train_16_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_16_1_pipeline` is a English model originally trained by SetFit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_1_pipeline_en_5.5.0_3.0_1725209198373.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_1_pipeline_en_5.5.0_3.0_1725209198373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large__sst2__train_16_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large__sst2__train_16_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large__sst2__train_16_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/SetFit/deberta-v3-large__sst2__train-16-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_16_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_16_5_pipeline_en.md new file mode 100644 index 00000000000000..1908a51c2d9103 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_16_5_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large__sst2__train_16_5_pipeline pipeline DeBertaForSequenceClassification from SetFit +author: John Snow Labs +name: deberta_v3_large__sst2__train_16_5_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_16_5_pipeline` is a English model originally trained by SetFit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_5_pipeline_en_5.4.2_3.0_1725183644287.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_5_pipeline_en_5.4.2_3.0_1725183644287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large__sst2__train_16_5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large__sst2__train_16_5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large__sst2__train_16_5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/SetFit/deberta-v3-large__sst2__train-16-5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_32_1_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_32_1_en.md new file mode 100644 index 00000000000000..4c99c6bb70f2d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_32_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large__sst2__train_32_1 DeBertaForSequenceClassification from SetFit +author: John Snow Labs +name: deberta_v3_large__sst2__train_32_1 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_32_1` is a English model originally trained by SetFit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_32_1_en_5.4.2_3.0_1725182807310.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_32_1_en_5.4.2_3.0_1725182807310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_32_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_32_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large__sst2__train_32_1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/SetFit/deberta-v3-large__sst2__train-32-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_32_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_32_1_pipeline_en.md new file mode 100644 index 00000000000000..17360526379c41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_32_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large__sst2__train_32_1_pipeline pipeline DeBertaForSequenceClassification from SetFit +author: John Snow Labs +name: deberta_v3_large__sst2__train_32_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_32_1_pipeline` is a English model originally trained by SetFit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_32_1_pipeline_en_5.4.2_3.0_1725182933813.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_32_1_pipeline_en_5.4.2_3.0_1725182933813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large__sst2__train_32_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large__sst2__train_32_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large__sst2__train_32_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/SetFit/deberta-v3-large__sst2__train-32-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_8_1_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_8_1_en.md new file mode 100644 index 00000000000000..b88e6b3217518a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_8_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large__sst2__train_8_1 DeBertaForSequenceClassification from SetFit +author: John Snow Labs +name: deberta_v3_large__sst2__train_8_1 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_8_1` is a English model originally trained by SetFit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_1_en_5.5.0_3.0_1725210683978.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_1_en_5.5.0_3.0_1725210683978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_8_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_8_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large__sst2__train_8_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/SetFit/deberta-v3-large__sst2__train-8-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_8_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_8_1_pipeline_en.md new file mode 100644 index 00000000000000..2ae79efe81ab04 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large__sst2__train_8_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large__sst2__train_8_1_pipeline pipeline DeBertaForSequenceClassification from SetFit +author: John Snow Labs +name: deberta_v3_large__sst2__train_8_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_8_1_pipeline` is a English model originally trained by SetFit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_1_pipeline_en_5.5.0_3.0_1725210819076.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_1_pipeline_en_5.5.0_3.0_1725210819076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large__sst2__train_8_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large__sst2__train_8_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large__sst2__train_8_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/SetFit/deberta-v3-large__sst2__train-8-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_boolq_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_boolq_en.md new file mode 100644 index 00000000000000..ec90c96425dcf6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_boolq_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_boolq DeBertaForSequenceClassification from nfliu +author: John Snow Labs +name: deberta_v3_large_boolq +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_boolq` is a English model originally trained by nfliu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_boolq_en_5.5.0_3.0_1725209546853.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_boolq_en_5.5.0_3.0_1725209546853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_boolq","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_boolq", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_boolq| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/nfliu/deberta-v3-large_boolq \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_boolq_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_boolq_pipeline_en.md new file mode 100644 index 00000000000000..9954d8f7f0cc83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_boolq_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_boolq_pipeline pipeline DeBertaForSequenceClassification from nfliu +author: John Snow Labs +name: deberta_v3_large_boolq_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_boolq_pipeline` is a English model originally trained by nfliu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_boolq_pipeline_en_5.5.0_3.0_1725209679026.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_boolq_pipeline_en_5.5.0_3.0_1725209679026.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_boolq_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_boolq_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_boolq_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/nfliu/deberta-v3-large_boolq + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_btc_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_btc_en.md new file mode 100644 index 00000000000000..eed001a285d397 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_btc_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_btc DeBertaForTokenClassification from tner +author: John Snow Labs +name: deberta_v3_large_btc +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_btc` is a English model originally trained by tner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_btc_en_5.5.0_3.0_1725233793655.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_btc_en_5.5.0_3.0_1725233793655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_btc","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_btc", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_btc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/tner/deberta-v3-large-btc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_btc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_btc_pipeline_en.md new file mode 100644 index 00000000000000..fd77a91d6f5c0e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_btc_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_btc_pipeline pipeline DeBertaForTokenClassification from tner +author: John Snow Labs +name: deberta_v3_large_btc_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_btc_pipeline` is a English model originally trained by tner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_btc_pipeline_en_5.5.0_3.0_1725233915388.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_btc_pipeline_en_5.5.0_3.0_1725233915388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_btc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_btc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_btc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/tner/deberta-v3-large-btc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_com2_atomic_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_com2_atomic_en.md new file mode 100644 index 00000000000000..f79006c6b1be9f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_com2_atomic_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_com2_atomic DeBertaEmbeddings from tqfang229 +author: John Snow Labs +name: deberta_v3_large_com2_atomic +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_com2_atomic` is a English model originally trained by tqfang229. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_com2_atomic_en_5.5.0_3.0_1725230231932.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_com2_atomic_en_5.5.0_3.0_1725230231932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large_com2_atomic","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large_com2_atomic","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_com2_atomic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/tqfang229/deberta-v3-large-com2-atomic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_com2_atomic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_com2_atomic_pipeline_en.md new file mode 100644 index 00000000000000..056f37730b90eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_com2_atomic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_com2_atomic_pipeline pipeline DeBertaEmbeddings from tqfang229 +author: John Snow Labs +name: deberta_v3_large_com2_atomic_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_com2_atomic_pipeline` is a English model originally trained by tqfang229. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_com2_atomic_pipeline_en_5.5.0_3.0_1725230317285.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_com2_atomic_pipeline_en_5.5.0_3.0_1725230317285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_com2_atomic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_com2_atomic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_com2_atomic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/tqfang229/deberta-v3-large-com2-atomic + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_com2_car_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_com2_car_en.md new file mode 100644 index 00000000000000..92fef368e3cd42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_com2_car_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_com2_car DeBertaEmbeddings from tqfang229 +author: John Snow Labs +name: deberta_v3_large_com2_car +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_com2_car` is a English model originally trained by tqfang229. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_com2_car_en_5.5.0_3.0_1725230828863.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_com2_car_en_5.5.0_3.0_1725230828863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large_com2_car","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large_com2_car","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_com2_car| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/tqfang229/deberta-v3-large-com2-car \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_conll2003_breast_v1_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_conll2003_breast_v1_en.md new file mode 100644 index 00000000000000..6d0f4a4eb87db8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_conll2003_breast_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_conll2003_breast_v1 DeBertaForTokenClassification from Yanis +author: John Snow Labs +name: deberta_v3_large_conll2003_breast_v1 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_conll2003_breast_v1` is a English model originally trained by Yanis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_conll2003_breast_v1_en_5.4.2_3.0_1725197773794.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_conll2003_breast_v1_en_5.4.2_3.0_1725197773794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_conll2003_breast_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_conll2003_breast_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_conll2003_breast_v1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/Yanis/deberta-v3-large_conll2003_breast_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_fewnerd_fine_ner_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_fewnerd_fine_ner_en.md new file mode 100644 index 00000000000000..83629d2021f614 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_fewnerd_fine_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_fewnerd_fine_ner DeBertaForTokenClassification from eek +author: John Snow Labs +name: deberta_v3_large_fewnerd_fine_ner +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_fewnerd_fine_ner` is a English model originally trained by eek. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_fewnerd_fine_ner_en_5.5.0_3.0_1725233592572.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_fewnerd_fine_ner_en_5.5.0_3.0_1725233592572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_fewnerd_fine_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_fewnerd_fine_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_fewnerd_fine_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/eek/deberta-v3-large-fewnerd-fine-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_fewnerd_fine_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_fewnerd_fine_ner_pipeline_en.md new file mode 100644 index 00000000000000..ff64efd52e12b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_fewnerd_fine_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_fewnerd_fine_ner_pipeline pipeline DeBertaForTokenClassification from eek +author: John Snow Labs +name: deberta_v3_large_fewnerd_fine_ner_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_fewnerd_fine_ner_pipeline` is a English model originally trained by eek. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_fewnerd_fine_ner_pipeline_en_5.5.0_3.0_1725233691968.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_fewnerd_fine_ner_pipeline_en_5.5.0_3.0_1725233691968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_fewnerd_fine_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_fewnerd_fine_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_fewnerd_fine_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/eek/deberta-v3-large-fewnerd-fine-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_en.md new file mode 100644 index 00000000000000..564b83c8ab2e74 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1 DeBertaEmbeddings from quastrinos +author: John Snow Labs +name: deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1` is a English model originally trained by quastrinos. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_en_5.5.0_3.0_1725217693203.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_en_5.5.0_3.0_1725217693203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/quastrinos/deberta-v3-large-finetuned-mlm-accelerate-v2-xp-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_pipeline_en.md new file mode 100644 index 00000000000000..c2627aa732df94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_pipeline pipeline DeBertaEmbeddings from quastrinos +author: John Snow Labs +name: deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_pipeline` is a English model originally trained by quastrinos. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_pipeline_en_5.5.0_3.0_1725217777745.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_pipeline_en_5.5.0_3.0_1725217777745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_mlm_accelerate_v2_xp_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/quastrinos/deberta-v3-large-finetuned-mlm-accelerate-v2-xp-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_squadv2_en.md new file mode 100644 index 00000000000000..ef4304dffd990e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_squadv2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_squadv2 DeBertaForQuestionAnswering from ahotrod +author: John Snow Labs +name: deberta_v3_large_finetuned_squadv2 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_squadv2` is a English model originally trained by ahotrod. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_squadv2_en_5.5.0_3.0_1725221350130.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_squadv2_en_5.5.0_3.0_1725221350130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_finetuned_squadv2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_finetuned_squadv2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_squadv2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/ahotrod/deberta-v3-large-finetuned-squadv2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_squadv2_pipeline_en.md new file mode 100644 index 00000000000000..70180e8d0fd965 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_squadv2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_squadv2_pipeline pipeline DeBertaForQuestionAnswering from ahotrod +author: John Snow Labs +name: deberta_v3_large_finetuned_squadv2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_squadv2_pipeline` is a English model originally trained by ahotrod. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_squadv2_pipeline_en_5.5.0_3.0_1725221450315.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_squadv2_pipeline_en_5.5.0_3.0_1725221450315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_finetuned_squadv2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_finetuned_squadv2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_squadv2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/ahotrod/deberta-v3-large-finetuned-squadv2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_not_bloom_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_not_bloom_pipeline_en.md new file mode 100644 index 00000000000000..6210c3f5578df2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_not_bloom_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_syndag_multiclass_not_bloom_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_finetuned_syndag_multiclass_not_bloom_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_syndag_multiclass_not_bloom_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_syndag_multiclass_not_bloom_pipeline_en_5.4.2_3.0_1725182422184.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_syndag_multiclass_not_bloom_pipeline_en_5.4.2_3.0_1725182422184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_finetuned_syndag_multiclass_not_bloom_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_finetuned_syndag_multiclass_not_bloom_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_syndag_multiclass_not_bloom_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-finetuned-syndag-multiclass-not-bloom + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_en.md new file mode 100644 index 00000000000000..9686aa8e884ff5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_en_5.5.0_3.0_1725209030750.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_en_5.5.0_3.0_1725209030750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-finetuned-syndag-multiclass-not-gpt2-arxiv \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_pipeline_en.md new file mode 100644 index 00000000000000..aa0c14fd87ad7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_pipeline_en_5.5.0_3.0_1725209116365.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_pipeline_en_5.5.0_3.0_1725209116365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_syndag_multiclass_not_gpt2_arxiv_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-finetuned-syndag-multiclass-not-gpt2-arxiv + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_en.md new file mode 100644 index 00000000000000..c68a87ef6d95f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_en_5.5.0_3.0_1725211001566.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_en_5.5.0_3.0_1725211001566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-finetuned-syndag-multiclass-remove-google-scielo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_pipeline_en.md new file mode 100644 index 00000000000000..d2207e3392f6dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_pipeline_en_5.5.0_3.0_1725211087402.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_pipeline_en_5.5.0_3.0_1725211087402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_syndag_multiclass_remove_google_scielo_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-finetuned-syndag-multiclass-remove-google-scielo + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_synthetic_generated_only_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_synthetic_generated_only_en.md new file mode 100644 index 00000000000000..61ae63b5e2695e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_synthetic_generated_only_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_synthetic_generated_only DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_finetuned_synthetic_generated_only +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_synthetic_generated_only` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_synthetic_generated_only_en_5.5.0_3.0_1725223354189.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_synthetic_generated_only_en_5.5.0_3.0_1725223354189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_finetuned_synthetic_generated_only","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_finetuned_synthetic_generated_only", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_synthetic_generated_only| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-finetuned-synthetic-generated-only \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_synthetic_generated_only_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_synthetic_generated_only_pipeline_en.md new file mode 100644 index 00000000000000..6d70ee0cf47f8b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_finetuned_synthetic_generated_only_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_synthetic_generated_only_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_finetuned_synthetic_generated_only_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_synthetic_generated_only_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_synthetic_generated_only_pipeline_en_5.5.0_3.0_1725223444590.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_synthetic_generated_only_pipeline_en_5.5.0_3.0_1725223444590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_finetuned_synthetic_generated_only_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_finetuned_synthetic_generated_only_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_synthetic_generated_only_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-finetuned-synthetic-generated-only + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_hf_weights_v2_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_hf_weights_v2_en.md new file mode 100644 index 00000000000000..d8f8fd4f980d0c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_hf_weights_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_hf_weights_v2 DeBertaEmbeddings from nagupv +author: John Snow Labs +name: deberta_v3_large_hf_weights_v2 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_hf_weights_v2` is a English model originally trained by nagupv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_hf_weights_v2_en_5.5.0_3.0_1725230658928.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_hf_weights_v2_en_5.5.0_3.0_1725230658928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large_hf_weights_v2","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large_hf_weights_v2","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_hf_weights_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/nagupv/deberta-v3-large-hf-weights_v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_hf_weights_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_hf_weights_v2_pipeline_en.md new file mode 100644 index 00000000000000..22cbd01ae8bc1c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_hf_weights_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_hf_weights_v2_pipeline pipeline DeBertaEmbeddings from nagupv +author: John Snow Labs +name: deberta_v3_large_hf_weights_v2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_hf_weights_v2_pipeline` is a English model originally trained by nagupv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_hf_weights_v2_pipeline_en_5.5.0_3.0_1725230743029.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_hf_weights_v2_pipeline_en_5.5.0_3.0_1725230743029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_hf_weights_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_hf_weights_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_hf_weights_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/nagupv/deberta-v3-large-hf-weights_v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_mlm_reddit_gab_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_mlm_reddit_gab_en.md new file mode 100644 index 00000000000000..bd74efe9d3b9af --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_mlm_reddit_gab_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_mlm_reddit_gab DeBertaEmbeddings from MilaNLProc +author: John Snow Labs +name: deberta_v3_large_mlm_reddit_gab +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_mlm_reddit_gab` is a English model originally trained by MilaNLProc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_mlm_reddit_gab_en_5.5.0_3.0_1725217282027.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_mlm_reddit_gab_en_5.5.0_3.0_1725217282027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large_mlm_reddit_gab","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large_mlm_reddit_gab","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_mlm_reddit_gab| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/MilaNLProc/deberta-v3-large-mlm-reddit-gab \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_mlm_reddit_gab_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_mlm_reddit_gab_pipeline_en.md new file mode 100644 index 00000000000000..757cc07e10e36d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_mlm_reddit_gab_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_mlm_reddit_gab_pipeline pipeline DeBertaEmbeddings from MilaNLProc +author: John Snow Labs +name: deberta_v3_large_mlm_reddit_gab_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_mlm_reddit_gab_pipeline` is a English model originally trained by MilaNLProc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_mlm_reddit_gab_pipeline_en_5.5.0_3.0_1725217366535.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_mlm_reddit_gab_pipeline_en_5.5.0_3.0_1725217366535.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_mlm_reddit_gab_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_mlm_reddit_gab_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_mlm_reddit_gab_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/MilaNLProc/deberta-v3-large-mlm-reddit-gab + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_mrqa_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_mrqa_en.md new file mode 100644 index 00000000000000..74180c25ede007 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_mrqa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_large_mrqa DeBertaForQuestionAnswering from VMware +author: John Snow Labs +name: deberta_v3_large_mrqa +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_mrqa` is a English model originally trained by VMware. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_mrqa_en_5.5.0_3.0_1725218986560.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_mrqa_en_5.5.0_3.0_1725218986560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_mrqa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_mrqa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_mrqa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/VMware/deberta-v3-large-mrqa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_mrqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_mrqa_pipeline_en.md new file mode 100644 index 00000000000000..a49a8aa5decaf8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_mrqa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_large_mrqa_pipeline pipeline DeBertaForQuestionAnswering from VMware +author: John Snow Labs +name: deberta_v3_large_mrqa_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_mrqa_pipeline` is a English model originally trained by VMware. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_mrqa_pipeline_en_5.5.0_3.0_1725219071661.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_mrqa_pipeline_en_5.5.0_3.0_1725219071661.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_mrqa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_mrqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_mrqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/VMware/deberta-v3-large-mrqa + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_squad2_deepset_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_squad2_deepset_en.md new file mode 100644 index 00000000000000..5a9c36652a9f96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_squad2_deepset_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_large_squad2_deepset DeBertaForQuestionAnswering from deepset +author: John Snow Labs +name: deberta_v3_large_squad2_deepset +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_squad2_deepset` is a English model originally trained by deepset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_deepset_en_5.5.0_3.0_1725218502154.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_deepset_en_5.5.0_3.0_1725218502154.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_squad2_deepset","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_squad2_deepset", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_squad2_deepset| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/deepset/deberta-v3-large-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_squad2_deepset_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_squad2_deepset_pipeline_en.md new file mode 100644 index 00000000000000..5c7a4a13131392 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_squad2_deepset_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_large_squad2_deepset_pipeline pipeline DeBertaForQuestionAnswering from deepset +author: John Snow Labs +name: deberta_v3_large_squad2_deepset_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_squad2_deepset_pipeline` is a English model originally trained by deepset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_deepset_pipeline_en_5.5.0_3.0_1725218603949.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_deepset_pipeline_en_5.5.0_3.0_1725218603949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_squad2_deepset_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_squad2_deepset_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_squad2_deepset_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/deepset/deberta-v3-large-squad2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_squad2_sjrhuschlee_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_squad2_sjrhuschlee_en.md new file mode 100644 index 00000000000000..f799aa5ce08ebd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_squad2_sjrhuschlee_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_large_squad2_sjrhuschlee DeBertaForQuestionAnswering from sjrhuschlee +author: John Snow Labs +name: deberta_v3_large_squad2_sjrhuschlee +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_squad2_sjrhuschlee` is a English model originally trained by sjrhuschlee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_sjrhuschlee_en_5.5.0_3.0_1725219801709.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_sjrhuschlee_en_5.5.0_3.0_1725219801709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_squad2_sjrhuschlee","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_squad2_sjrhuschlee", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_squad2_sjrhuschlee| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.4 GB| + +## References + +https://huggingface.co/sjrhuschlee/deberta-v3-large-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_squad2_sjrhuschlee_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_squad2_sjrhuschlee_pipeline_en.md new file mode 100644 index 00000000000000..8166c4852b5122 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_squad2_sjrhuschlee_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_large_squad2_sjrhuschlee_pipeline pipeline DeBertaForQuestionAnswering from sjrhuschlee +author: John Snow Labs +name: deberta_v3_large_squad2_sjrhuschlee_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_squad2_sjrhuschlee_pipeline` is a English model originally trained by sjrhuschlee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_sjrhuschlee_pipeline_en_5.5.0_3.0_1725219953360.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_sjrhuschlee_pipeline_en_5.5.0_3.0_1725219953360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_squad2_sjrhuschlee_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_squad2_sjrhuschlee_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_squad2_sjrhuschlee_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.4 GB| + +## References + +https://huggingface.co/sjrhuschlee/deberta-v3-large-squad2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_en.md new file mode 100644 index 00000000000000..5f61710e3281c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4 DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_en_5.5.0_3.0_1725209752069.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_en_5.5.0_3.0_1725209752069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-cross_passage_consistency-rater-all-gpt4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_pipeline_en.md new file mode 100644 index 00000000000000..6092d8cd5591e7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_pipeline_en_5.5.0_3.0_1725209842888.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_pipeline_en_5.5.0_3.0_1725209842888.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_cross_passage_consistency_rater_all_gpt4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-cross_passage_consistency-rater-all-gpt4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_cross_passage_consistency_rater_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_cross_passage_consistency_rater_gpt4_pipeline_en.md new file mode 100644 index 00000000000000..4fe70806bed06a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_cross_passage_consistency_rater_gpt4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_survey_cross_passage_consistency_rater_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_cross_passage_consistency_rater_gpt4_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_cross_passage_consistency_rater_gpt4_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_cross_passage_consistency_rater_gpt4_pipeline_en_5.4.2_3.0_1725183888113.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_cross_passage_consistency_rater_gpt4_pipeline_en_5.4.2_3.0_1725183888113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_survey_cross_passage_consistency_rater_gpt4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_survey_cross_passage_consistency_rater_gpt4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_cross_passage_consistency_rater_gpt4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-cross_passage_consistency-rater-gpt4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_main_passage_old_facts_rater_all_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_main_passage_old_facts_rater_all_en.md new file mode 100644 index 00000000000000..abca8271b1aa2a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_main_passage_old_facts_rater_all_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_survey_main_passage_old_facts_rater_all DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_main_passage_old_facts_rater_all +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_main_passage_old_facts_rater_all` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_old_facts_rater_all_en_5.5.0_3.0_1725222282267.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_old_facts_rater_all_en_5.5.0_3.0_1725222282267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_main_passage_old_facts_rater_all","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_main_passage_old_facts_rater_all", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_main_passage_old_facts_rater_all| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-main_passage_old_facts-rater-all \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_main_passage_old_facts_rater_all_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_main_passage_old_facts_rater_all_pipeline_en.md new file mode 100644 index 00000000000000..09bbbc846356c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_main_passage_old_facts_rater_all_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_survey_main_passage_old_facts_rater_all_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_main_passage_old_facts_rater_all_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_main_passage_old_facts_rater_all_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_old_facts_rater_all_pipeline_en_5.5.0_3.0_1725222381536.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_old_facts_rater_all_pipeline_en_5.5.0_3.0_1725222381536.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_survey_main_passage_old_facts_rater_all_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_survey_main_passage_old_facts_rater_all_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_main_passage_old_facts_rater_all_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-main_passage_old_facts-rater-all + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_related_passage_consistency_rater_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_related_passage_consistency_rater_en.md new file mode 100644 index 00000000000000..f226f99f4e0540 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_related_passage_consistency_rater_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_survey_related_passage_consistency_rater DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_related_passage_consistency_rater +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_related_passage_consistency_rater` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_related_passage_consistency_rater_en_5.5.0_3.0_1725222599622.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_related_passage_consistency_rater_en_5.5.0_3.0_1725222599622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_related_passage_consistency_rater","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_related_passage_consistency_rater", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_related_passage_consistency_rater| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-related_passage_consistency-rater \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_related_passage_consistency_rater_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_related_passage_consistency_rater_pipeline_en.md new file mode 100644 index 00000000000000..dda68695577c09 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_related_passage_consistency_rater_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_survey_related_passage_consistency_rater_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_related_passage_consistency_rater_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_related_passage_consistency_rater_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_related_passage_consistency_rater_pipeline_en_5.5.0_3.0_1725222742183.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_related_passage_consistency_rater_pipeline_en_5.5.0_3.0_1725222742183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_survey_related_passage_consistency_rater_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_survey_related_passage_consistency_rater_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_related_passage_consistency_rater_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-related_passage_consistency-rater + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_en.md new file mode 100644 index 00000000000000..17a6f922bfedf4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4 DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_en_5.5.0_3.0_1725210480701.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_en_5.5.0_3.0_1725210480701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-related_passage_old_facts-rater-half-gpt4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_pipeline_en.md new file mode 100644 index 00000000000000..6d68c643487e7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_pipeline_en_5.5.0_3.0_1725210577038.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_pipeline_en_5.5.0_3.0_1725210577038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_related_passage_old_facts_rater_half_gpt4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-related_passage_old_facts-rater-half-gpt4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_topicality_rater_all_gpt4_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_topicality_rater_all_gpt4_en.md new file mode 100644 index 00000000000000..e9ed430bbf4356 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_topicality_rater_all_gpt4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_survey_topicality_rater_all_gpt4 DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_topicality_rater_all_gpt4 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_topicality_rater_all_gpt4` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_topicality_rater_all_gpt4_en_5.5.0_3.0_1725223986488.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_topicality_rater_all_gpt4_en_5.5.0_3.0_1725223986488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_topicality_rater_all_gpt4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_topicality_rater_all_gpt4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_topicality_rater_all_gpt4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-topicality-rater-all-gpt4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_topicality_rater_all_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_topicality_rater_all_gpt4_pipeline_en.md new file mode 100644 index 00000000000000..1a44ad22779cd0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_survey_topicality_rater_all_gpt4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_survey_topicality_rater_all_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_topicality_rater_all_gpt4_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_topicality_rater_all_gpt4_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_topicality_rater_all_gpt4_pipeline_en_5.5.0_3.0_1725224090705.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_topicality_rater_all_gpt4_pipeline_en_5.5.0_3.0_1725224090705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_survey_topicality_rater_all_gpt4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_survey_topicality_rater_all_gpt4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_topicality_rater_all_gpt4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-topicality-rater-all-gpt4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_tapt_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_tapt_en.md new file mode 100644 index 00000000000000..c4d8c44a29c9c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_tapt_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_tapt DeBertaEmbeddings from ZZ99 +author: John Snow Labs +name: deberta_v3_large_tapt +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_tapt` is a English model originally trained by ZZ99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_tapt_en_5.5.0_3.0_1725216935259.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_tapt_en_5.5.0_3.0_1725216935259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large_tapt","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large_tapt","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_tapt| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/ZZ99/deberta-v3-large-tapt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_tapt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_tapt_pipeline_en.md new file mode 100644 index 00000000000000..9627584b578819 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_tapt_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_tapt_pipeline pipeline DeBertaEmbeddings from ZZ99 +author: John Snow Labs +name: deberta_v3_large_tapt_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_tapt_pipeline` is a English model originally trained by ZZ99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_tapt_pipeline_en_5.5.0_3.0_1725217017967.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_tapt_pipeline_en_5.5.0_3.0_1725217017967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_tapt_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_tapt_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_tapt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/ZZ99/deberta-v3-large-tapt + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_toxicity_scorer_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_toxicity_scorer_en.md new file mode 100644 index 00000000000000..c3f5233973b699 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_toxicity_scorer_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_toxicity_scorer DeBertaForSequenceClassification from cooperleong00 +author: John Snow Labs +name: deberta_v3_large_toxicity_scorer +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_toxicity_scorer` is a English model originally trained by cooperleong00. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_toxicity_scorer_en_5.5.0_3.0_1725209963713.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_toxicity_scorer_en_5.5.0_3.0_1725209963713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_toxicity_scorer","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_toxicity_scorer", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_toxicity_scorer| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/cooperleong00/deberta-v3-large_toxicity-scorer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_toxicity_scorer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_toxicity_scorer_pipeline_en.md new file mode 100644 index 00000000000000..bebe7eba660e34 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_toxicity_scorer_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_toxicity_scorer_pipeline pipeline DeBertaForSequenceClassification from cooperleong00 +author: John Snow Labs +name: deberta_v3_large_toxicity_scorer_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_toxicity_scorer_pipeline` is a English model originally trained by cooperleong00. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_toxicity_scorer_pipeline_en_5.5.0_3.0_1725210067185.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_toxicity_scorer_pipeline_en_5.5.0_3.0_1725210067185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_toxicity_scorer_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_toxicity_scorer_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_toxicity_scorer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/cooperleong00/deberta-v3-large_toxicity-scorer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_zeroshot_v2_0_28heldout_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_zeroshot_v2_0_28heldout_en.md new file mode 100644 index 00000000000000..df6f3ef63e95bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_zeroshot_v2_0_28heldout_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_zeroshot_v2_0_28heldout DeBertaForSequenceClassification from MoritzLaurer +author: John Snow Labs +name: deberta_v3_large_zeroshot_v2_0_28heldout +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_zeroshot_v2_0_28heldout` is a English model originally trained by MoritzLaurer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_zeroshot_v2_0_28heldout_en_5.5.0_3.0_1725211132035.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_zeroshot_v2_0_28heldout_en_5.5.0_3.0_1725211132035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_zeroshot_v2_0_28heldout","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_zeroshot_v2_0_28heldout", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_zeroshot_v2_0_28heldout| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/MoritzLaurer/deberta-v3-large-zeroshot-v2.0-28heldout \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_zeroshot_v2_0_28heldout_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_zeroshot_v2_0_28heldout_pipeline_en.md new file mode 100644 index 00000000000000..aceae6c4dd74dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_zeroshot_v2_0_28heldout_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_zeroshot_v2_0_28heldout_pipeline pipeline DeBertaForSequenceClassification from MoritzLaurer +author: John Snow Labs +name: deberta_v3_large_zeroshot_v2_0_28heldout_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_zeroshot_v2_0_28heldout_pipeline` is a English model originally trained by MoritzLaurer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_zeroshot_v2_0_28heldout_pipeline_en_5.5.0_3.0_1725211441989.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_zeroshot_v2_0_28heldout_pipeline_en_5.5.0_3.0_1725211441989.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_zeroshot_v2_0_28heldout_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_zeroshot_v2_0_28heldout_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_zeroshot_v2_0_28heldout_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/MoritzLaurer/deberta-v3-large-zeroshot-v2.0-28heldout + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_rel_class_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_rel_class_en.md new file mode 100644 index 00000000000000..25fdc5419d193c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_rel_class_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_rel_class DeBertaForSequenceClassification from orbis-marianne +author: John Snow Labs +name: deberta_v3_rel_class +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_rel_class` is a English model originally trained by orbis-marianne. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_rel_class_en_5.5.0_3.0_1725209558852.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_rel_class_en_5.5.0_3.0_1725209558852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_rel_class","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_rel_class", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_rel_class| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|584.1 MB| + +## References + +https://huggingface.co/orbis-marianne/deberta-v3-rel-class \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_rel_class_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_rel_class_pipeline_en.md new file mode 100644 index 00000000000000..374b04a0263edf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_rel_class_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_rel_class_pipeline pipeline DeBertaForSequenceClassification from orbis-marianne +author: John Snow Labs +name: deberta_v3_rel_class_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_rel_class_pipeline` is a English model originally trained by orbis-marianne. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_rel_class_pipeline_en_5.5.0_3.0_1725209629574.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_rel_class_pipeline_en_5.5.0_3.0_1725209629574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_rel_class_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_rel_class_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_rel_class_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|584.1 MB| + +## References + +https://huggingface.co/orbis-marianne/deberta-v3-rel-class + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_seq_tag_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_seq_tag_en.md new file mode 100644 index 00000000000000..9219963b3f6046 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_seq_tag_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_seq_tag DeBertaForTokenClassification from orbis-marianne +author: John Snow Labs +name: deberta_v3_seq_tag +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_seq_tag` is a English model originally trained by orbis-marianne. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_seq_tag_en_5.4.2_3.0_1725197206662.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_seq_tag_en_5.4.2_3.0_1725197206662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_seq_tag","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_seq_tag", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_seq_tag| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|565.4 MB| + +## References + +https://huggingface.co/orbis-marianne/deberta-v3-seq-tag \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_seq_tag_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_seq_tag_pipeline_en.md new file mode 100644 index 00000000000000..eb1744f4cd6ac4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_seq_tag_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_seq_tag_pipeline pipeline DeBertaForTokenClassification from orbis-marianne +author: John Snow Labs +name: deberta_v3_seq_tag_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_seq_tag_pipeline` is a English model originally trained by orbis-marianne. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_seq_tag_pipeline_en_5.4.2_3.0_1725197303596.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_seq_tag_pipeline_en_5.4.2_3.0_1725197303596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_seq_tag_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_seq_tag_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_seq_tag_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|565.5 MB| + +## References + +https://huggingface.co/orbis-marianne/deberta-v3-seq-tag + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_en.md new file mode 100644 index 00000000000000..7443ae2f5df57b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_en.md @@ -0,0 +1,77 @@ +--- +layout: model +title: DeBERTa small model +author: John Snow Labs +name: deberta_v3_small +date: 2024-09-01 +tags: [en, english, embeddings, deberta, v3, small, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +The DeBERTa model was proposed in [[https://arxiv.org/abs/2006.03654 DeBERTa: Decoding-enhanced BERT with Disentangled Attention]] by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen It is based on Google’s BERT model released in 2018 and Facebook’s RoBERTa model released in 2019. Compared to RoBERTa-Large, a DeBERTa model trained on half of the training data performs consistently better on a wide range of NLP tasks, achieving improvements on MNLI by +0.9% (90.2% vs. 91.1%), on SQuAD v2.0 by +2.3% (88.4% vs. 90.7%) and RACE by +3.6% (83.2% vs. 86.8%). + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_en_5.5.0_3.0_1725217400151.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_en_5.5.0_3.0_1725217400151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + +{:.model-param} + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +embeddings = DeBertaEmbeddings.pretrained("deberta_v3_small", "en") \ +.setInputCols("sentence", "token") \ +.setOutputCol("embeddings") +``` +```scala +val embeddings = DeBertaEmbeddings.pretrained("deberta_v3_small", "en") +.setInputCols("sentence", "token") +.setOutputCol("embeddings") +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.embed.deberta_v3_small").predict("""Put your text here.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|334.1 MB| + +## Benchmarking + +```bash + +Benchmarking +``` \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_essay_grading_classification_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_essay_grading_classification_en.md new file mode 100644 index 00000000000000..9d8d4c42a30514 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_essay_grading_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_small_essay_grading_classification DeBertaForSequenceClassification from antonryoung02 +author: John Snow Labs +name: deberta_v3_small_essay_grading_classification +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_essay_grading_classification` is a English model originally trained by antonryoung02. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_essay_grading_classification_en_5.5.0_3.0_1725222137195.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_essay_grading_classification_en_5.5.0_3.0_1725222137195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_essay_grading_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_essay_grading_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_essay_grading_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|226.0 MB| + +## References + +https://huggingface.co/antonryoung02/deberta-v3-small-essay-grading-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_essay_grading_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_essay_grading_classification_pipeline_en.md new file mode 100644 index 00000000000000..66f52d65b7a170 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_essay_grading_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_small_essay_grading_classification_pipeline pipeline DeBertaForSequenceClassification from antonryoung02 +author: John Snow Labs +name: deberta_v3_small_essay_grading_classification_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_essay_grading_classification_pipeline` is a English model originally trained by antonryoung02. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_essay_grading_classification_pipeline_en_5.5.0_3.0_1725222152576.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_essay_grading_classification_pipeline_en_5.5.0_3.0_1725222152576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_small_essay_grading_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_small_essay_grading_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_essay_grading_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|226.0 MB| + +## References + +https://huggingface.co/antonryoung02/deberta-v3-small-essay-grading-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_fever_classification_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_fever_classification_en.md new file mode 100644 index 00000000000000..871eac9f2d8d65 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_fever_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_small_fever_classification DeBertaForSequenceClassification from geektech +author: John Snow Labs +name: deberta_v3_small_fever_classification +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_fever_classification` is a English model originally trained by geektech. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_fever_classification_en_5.5.0_3.0_1725210399391.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_fever_classification_en_5.5.0_3.0_1725210399391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_fever_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_fever_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_fever_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|443.0 MB| + +## References + +https://huggingface.co/geektech/deberta-v3-small-fever-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_fever_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_fever_classification_pipeline_en.md new file mode 100644 index 00000000000000..4a69d780175e6f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_fever_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_small_fever_classification_pipeline pipeline DeBertaForSequenceClassification from geektech +author: John Snow Labs +name: deberta_v3_small_fever_classification_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_fever_classification_pipeline` is a English model originally trained by geektech. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_fever_classification_pipeline_en_5.5.0_3.0_1725210456020.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_fever_classification_pipeline_en_5.5.0_3.0_1725210456020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_small_fever_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_small_fever_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_fever_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|443.0 MB| + +## References + +https://huggingface.co/geektech/deberta-v3-small-fever-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_fine_disaster_tweets_part2_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_fine_disaster_tweets_part2_en.md new file mode 100644 index 00000000000000..99434292bc16d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_fine_disaster_tweets_part2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_small_fine_disaster_tweets_part2 DeBertaForSequenceClassification from victorbahlangene +author: John Snow Labs +name: deberta_v3_small_fine_disaster_tweets_part2 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_fine_disaster_tweets_part2` is a English model originally trained by victorbahlangene. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_fine_disaster_tweets_part2_en_5.5.0_3.0_1725223588099.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_fine_disaster_tweets_part2_en_5.5.0_3.0_1725223588099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_fine_disaster_tweets_part2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_fine_disaster_tweets_part2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_fine_disaster_tweets_part2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|450.1 MB| + +## References + +https://huggingface.co/victorbahlangene/deberta-v3-small-fine-Disaster-Tweets-Part2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_fine_disaster_tweets_part2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_fine_disaster_tweets_part2_pipeline_en.md new file mode 100644 index 00000000000000..3e08a043ea88a0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_fine_disaster_tweets_part2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_small_fine_disaster_tweets_part2_pipeline pipeline DeBertaForSequenceClassification from victorbahlangene +author: John Snow Labs +name: deberta_v3_small_fine_disaster_tweets_part2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_fine_disaster_tweets_part2_pipeline` is a English model originally trained by victorbahlangene. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_fine_disaster_tweets_part2_pipeline_en_5.5.0_3.0_1725223619690.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_fine_disaster_tweets_part2_pipeline_en_5.5.0_3.0_1725223619690.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_small_fine_disaster_tweets_part2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_small_fine_disaster_tweets_part2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_fine_disaster_tweets_part2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|450.2 MB| + +## References + +https://huggingface.co/victorbahlangene/deberta-v3-small-fine-Disaster-Tweets-Part2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_mnli_mrm8488_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_mnli_mrm8488_en.md new file mode 100644 index 00000000000000..8db2f20886d48a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_mnli_mrm8488_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_small_finetuned_mnli_mrm8488 DeBertaForSequenceClassification from mrm8488 +author: John Snow Labs +name: deberta_v3_small_finetuned_mnli_mrm8488 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_mnli_mrm8488` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_mnli_mrm8488_en_5.5.0_3.0_1725210985785.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_mnli_mrm8488_en_5.5.0_3.0_1725210985785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_finetuned_mnli_mrm8488","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_finetuned_mnli_mrm8488", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_finetuned_mnli_mrm8488| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|481.3 MB| + +## References + +https://huggingface.co/mrm8488/deberta-v3-small-finetuned-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_mnli_mrm8488_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_mnli_mrm8488_pipeline_en.md new file mode 100644 index 00000000000000..7bd4ed12844ea1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_mnli_mrm8488_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_small_finetuned_mnli_mrm8488_pipeline pipeline DeBertaForSequenceClassification from mrm8488 +author: John Snow Labs +name: deberta_v3_small_finetuned_mnli_mrm8488_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_mnli_mrm8488_pipeline` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_mnli_mrm8488_pipeline_en_5.5.0_3.0_1725211031471.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_mnli_mrm8488_pipeline_en_5.5.0_3.0_1725211031471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_small_finetuned_mnli_mrm8488_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_small_finetuned_mnli_mrm8488_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_finetuned_mnli_mrm8488_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|481.3 MB| + +## References + +https://huggingface.co/mrm8488/deberta-v3-small-finetuned-mnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_qnli_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_qnli_en.md new file mode 100644 index 00000000000000..2e4e51310cac48 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_qnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_small_finetuned_qnli DeBertaForSequenceClassification from mrm8488 +author: John Snow Labs +name: deberta_v3_small_finetuned_qnli +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_qnli` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_qnli_en_5.5.0_3.0_1725209930911.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_qnli_en_5.5.0_3.0_1725209930911.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_finetuned_qnli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_finetuned_qnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_finetuned_qnli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|477.9 MB| + +## References + +https://huggingface.co/mrm8488/deberta-v3-small-finetuned-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_qnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_qnli_pipeline_en.md new file mode 100644 index 00000000000000..121af72b1dfeaa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_qnli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_small_finetuned_qnli_pipeline pipeline DeBertaForSequenceClassification from mrm8488 +author: John Snow Labs +name: deberta_v3_small_finetuned_qnli_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_qnli_pipeline` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_qnli_pipeline_en_5.5.0_3.0_1725209977545.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_qnli_pipeline_en_5.5.0_3.0_1725209977545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_small_finetuned_qnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_small_finetuned_qnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_finetuned_qnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|477.9 MB| + +## References + +https://huggingface.co/mrm8488/deberta-v3-small-finetuned-qnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_squadv2_en.md new file mode 100644 index 00000000000000..306140065183b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_squadv2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_small_finetuned_squadv2 DeBertaForQuestionAnswering from mrm8488 +author: John Snow Labs +name: deberta_v3_small_finetuned_squadv2 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_squadv2` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_squadv2_en_5.5.0_3.0_1725220968392.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_squadv2_en_5.5.0_3.0_1725220968392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_small_finetuned_squadv2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_small_finetuned_squadv2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_finetuned_squadv2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|484.5 MB| + +## References + +https://huggingface.co/mrm8488/deberta-v3-small-finetuned-squadv2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_squadv2_pipeline_en.md new file mode 100644 index 00000000000000..dac3161d30c159 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_finetuned_squadv2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_small_finetuned_squadv2_pipeline pipeline DeBertaForQuestionAnswering from mrm8488 +author: John Snow Labs +name: deberta_v3_small_finetuned_squadv2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_squadv2_pipeline` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_squadv2_pipeline_en_5.5.0_3.0_1725221013890.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_squadv2_pipeline_en_5.5.0_3.0_1725221013890.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_small_finetuned_squadv2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_small_finetuned_squadv2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_finetuned_squadv2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|484.5 MB| + +## References + +https://huggingface.co/mrm8488/deberta-v3-small-finetuned-squadv2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_goemotions_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_goemotions_pipeline_en.md new file mode 100644 index 00000000000000..d4d721eab4b284 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_goemotions_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_small_goemotions_pipeline pipeline DeBertaForSequenceClassification from mrm8488 +author: John Snow Labs +name: deberta_v3_small_goemotions_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_goemotions_pipeline` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_goemotions_pipeline_en_5.4.2_3.0_1725181978630.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_goemotions_pipeline_en_5.4.2_3.0_1725181978630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_small_goemotions_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_small_goemotions_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_goemotions_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|461.8 MB| + +## References + +https://huggingface.co/mrm8488/deberta-v3-small-goemotions + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_isarcasm_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_isarcasm_en.md new file mode 100644 index 00000000000000..084244d3a071a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_isarcasm_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_small_isarcasm DeBertaForSequenceClassification from w11wo +author: John Snow Labs +name: deberta_v3_small_isarcasm +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_isarcasm` is a English model originally trained by w11wo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_isarcasm_en_5.5.0_3.0_1725224152027.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_isarcasm_en_5.5.0_3.0_1725224152027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_isarcasm","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_isarcasm", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_isarcasm| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|420.5 MB| + +## References + +https://huggingface.co/w11wo/deberta-v3-small-isarcasm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_isarcasm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_isarcasm_pipeline_en.md new file mode 100644 index 00000000000000..3d7e3eecdfc68b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_isarcasm_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_small_isarcasm_pipeline pipeline DeBertaForSequenceClassification from w11wo +author: John Snow Labs +name: deberta_v3_small_isarcasm_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_isarcasm_pipeline` is a English model originally trained by w11wo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_isarcasm_pipeline_en_5.5.0_3.0_1725224211722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_isarcasm_pipeline_en_5.5.0_3.0_1725224211722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_small_isarcasm_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_small_isarcasm_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_isarcasm_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|420.6 MB| + +## References + +https://huggingface.co/w11wo/deberta-v3-small-isarcasm + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_pipeline_en.md new file mode 100644 index 00000000000000..78d7286fbc24e8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_small_pipeline pipeline DeBertaEmbeddings from microsoft +author: John Snow Labs +name: deberta_v3_small_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_pipeline` is a English model originally trained by microsoft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_pipeline_en_5.5.0_3.0_1725217502627.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_pipeline_en_5.5.0_3.0_1725217502627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_small_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_small_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|334.1 MB| + +## References + +https://huggingface.co/microsoft/deberta-v3-small + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_sp500_edgar_10k_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_sp500_edgar_10k_en.md new file mode 100644 index 00000000000000..d1405e8d7a73d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_sp500_edgar_10k_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_small_sp500_edgar_10k DeBertaForSequenceClassification from pszemraj +author: John Snow Labs +name: deberta_v3_small_sp500_edgar_10k +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_sp500_edgar_10k` is a English model originally trained by pszemraj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_sp500_edgar_10k_en_5.5.0_3.0_1725210052507.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_sp500_edgar_10k_en_5.5.0_3.0_1725210052507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_sp500_edgar_10k","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_sp500_edgar_10k", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_sp500_edgar_10k| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/pszemraj/deberta-v3-small-sp500-edgar-10k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_sp500_edgar_10k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_sp500_edgar_10k_pipeline_en.md new file mode 100644 index 00000000000000..018003301dc104 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_small_sp500_edgar_10k_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_small_sp500_edgar_10k_pipeline pipeline DeBertaForSequenceClassification from pszemraj +author: John Snow Labs +name: deberta_v3_small_sp500_edgar_10k_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_sp500_edgar_10k_pipeline` is a English model originally trained by pszemraj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_sp500_edgar_10k_pipeline_en_5.5.0_3.0_1725210087541.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_sp500_edgar_10k_pipeline_en_5.5.0_3.0_1725210087541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_small_sp500_edgar_10k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_small_sp500_edgar_10k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_sp500_edgar_10k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/pszemraj/deberta-v3-small-sp500-edgar-10k + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_en.md new file mode 100644 index 00000000000000..a94b79948ded94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_en.md @@ -0,0 +1,77 @@ +--- +layout: model +title: DeBERTa xsmall model +author: John Snow Labs +name: deberta_v3_xsmall +date: 2024-09-01 +tags: [en, english, embeddings, deberta, xsmall, v3, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +The DeBERTa model was proposed in [[https://arxiv.org/abs/2006.03654 DeBERTa: Decoding-enhanced BERT with Disentangled Attention]] by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen It is based on Google’s BERT model released in 2018 and Facebook’s RoBERTa model released in 2019. Compared to RoBERTa-Large, a DeBERTa model trained on half of the training data performs consistently better on a wide range of NLP tasks, achieving improvements on MNLI by +0.9% (90.2% vs. 91.1%), on SQuAD v2.0 by +2.3% (88.4% vs. 90.7%) and RACE by +3.6% (83.2% vs. 86.8%). + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_en_5.5.0_3.0_1725229938718.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_en_5.5.0_3.0_1725229938718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + +{:.model-param} + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +embeddings = DeBertaEmbeddings.pretrained("deberta_v3_xsmall", "en") \ +.setInputCols("sentence", "token") \ +.setOutputCol("embeddings") +``` +```scala +val embeddings = DeBertaEmbeddings.pretrained("deberta_v3_xsmall", "en") +.setInputCols("sentence", "token") +.setOutputCol("embeddings") +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.embed.deberta_v3_xsmall").predict("""Put your text here.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|167.8 MB| + +## Benchmarking + +```bash + +Benchmarking +``` \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_finetuned_ner_exp1_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_finetuned_ner_exp1_en.md new file mode 100644 index 00000000000000..6dcd8bc71c7c00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_finetuned_ner_exp1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_xsmall_finetuned_ner_exp1 DeBertaForTokenClassification from Gozdi +author: John Snow Labs +name: deberta_v3_xsmall_finetuned_ner_exp1 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_finetuned_ner_exp1` is a English model originally trained by Gozdi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_finetuned_ner_exp1_en_5.5.0_3.0_1725232728112.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_finetuned_ner_exp1_en_5.5.0_3.0_1725232728112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_xsmall_finetuned_ner_exp1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_xsmall_finetuned_ner_exp1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_finetuned_ner_exp1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|228.5 MB| + +## References + +https://huggingface.co/Gozdi/deberta_v3_xsmall-finetuned-ner-exp1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_finetuned_ner_exp1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_finetuned_ner_exp1_pipeline_en.md new file mode 100644 index 00000000000000..372e88dd291765 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_finetuned_ner_exp1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_xsmall_finetuned_ner_exp1_pipeline pipeline DeBertaForTokenClassification from Gozdi +author: John Snow Labs +name: deberta_v3_xsmall_finetuned_ner_exp1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_finetuned_ner_exp1_pipeline` is a English model originally trained by Gozdi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_finetuned_ner_exp1_pipeline_en_5.5.0_3.0_1725232742665.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_finetuned_ner_exp1_pipeline_en_5.5.0_3.0_1725232742665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_xsmall_finetuned_ner_exp1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_xsmall_finetuned_ner_exp1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_finetuned_ner_exp1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|228.5 MB| + +## References + +https://huggingface.co/Gozdi/deberta_v3_xsmall-finetuned-ner-exp1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_finetuned_ner_exp2_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_finetuned_ner_exp2_en.md new file mode 100644 index 00000000000000..e11217213d0001 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_finetuned_ner_exp2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_xsmall_finetuned_ner_exp2 DeBertaForTokenClassification from Gozdi +author: John Snow Labs +name: deberta_v3_xsmall_finetuned_ner_exp2 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_finetuned_ner_exp2` is a English model originally trained by Gozdi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_finetuned_ner_exp2_en_5.5.0_3.0_1725233114869.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_finetuned_ner_exp2_en_5.5.0_3.0_1725233114869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_xsmall_finetuned_ner_exp2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_xsmall_finetuned_ner_exp2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_finetuned_ner_exp2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|228.4 MB| + +## References + +https://huggingface.co/Gozdi/deberta_v3_xsmall-finetuned-ner-exp2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_finetuned_ner_exp2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_finetuned_ner_exp2_pipeline_en.md new file mode 100644 index 00000000000000..d9a2ab62849e41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_finetuned_ner_exp2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_xsmall_finetuned_ner_exp2_pipeline pipeline DeBertaForTokenClassification from Gozdi +author: John Snow Labs +name: deberta_v3_xsmall_finetuned_ner_exp2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_finetuned_ner_exp2_pipeline` is a English model originally trained by Gozdi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_finetuned_ner_exp2_pipeline_en_5.5.0_3.0_1725233129487.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_finetuned_ner_exp2_pipeline_en_5.5.0_3.0_1725233129487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_xsmall_finetuned_ner_exp2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_xsmall_finetuned_ner_exp2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_finetuned_ner_exp2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|228.4 MB| + +## References + +https://huggingface.co/Gozdi/deberta_v3_xsmall-finetuned-ner-exp2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_indonesia_squadv2_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_indonesia_squadv2_en.md new file mode 100644 index 00000000000000..b67b3eedb1a1ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_indonesia_squadv2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_xsmall_indonesia_squadv2 DeBertaForQuestionAnswering from asaduas +author: John Snow Labs +name: deberta_v3_xsmall_indonesia_squadv2 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_indonesia_squadv2` is a English model originally trained by asaduas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_indonesia_squadv2_en_5.5.0_3.0_1725221578894.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_indonesia_squadv2_en_5.5.0_3.0_1725221578894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_xsmall_indonesia_squadv2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_xsmall_indonesia_squadv2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_indonesia_squadv2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|230.8 MB| + +## References + +https://huggingface.co/asaduas/deberta-v3-xsmall-indonesia-squadv2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_indonesia_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_indonesia_squadv2_pipeline_en.md new file mode 100644 index 00000000000000..972943d96b986e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_indonesia_squadv2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_xsmall_indonesia_squadv2_pipeline pipeline DeBertaForQuestionAnswering from asaduas +author: John Snow Labs +name: deberta_v3_xsmall_indonesia_squadv2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_indonesia_squadv2_pipeline` is a English model originally trained by asaduas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_indonesia_squadv2_pipeline_en_5.5.0_3.0_1725221605649.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_indonesia_squadv2_pipeline_en_5.5.0_3.0_1725221605649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_xsmall_indonesia_squadv2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_xsmall_indonesia_squadv2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_indonesia_squadv2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|230.8 MB| + +## References + +https://huggingface.co/asaduas/deberta-v3-xsmall-indonesia-squadv2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_mrqa_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_mrqa_en.md new file mode 100644 index 00000000000000..fa8a09e16ab9bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_mrqa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_xsmall_mrqa DeBertaForQuestionAnswering from VMware +author: John Snow Labs +name: deberta_v3_xsmall_mrqa +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_mrqa` is a English model originally trained by VMware. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_mrqa_en_5.5.0_3.0_1725218258096.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_mrqa_en_5.5.0_3.0_1725218258096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_xsmall_mrqa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_xsmall_mrqa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_mrqa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|688.1 MB| + +## References + +https://huggingface.co/VMware/deberta-v3-xsmall-mrqa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_mrqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_mrqa_pipeline_en.md new file mode 100644 index 00000000000000..5241f0f3352856 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_mrqa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_xsmall_mrqa_pipeline pipeline DeBertaForQuestionAnswering from VMware +author: John Snow Labs +name: deberta_v3_xsmall_mrqa_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_mrqa_pipeline` is a English model originally trained by VMware. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_mrqa_pipeline_en_5.5.0_3.0_1725218294699.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_mrqa_pipeline_en_5.5.0_3.0_1725218294699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_xsmall_mrqa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_xsmall_mrqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_mrqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|688.1 MB| + +## References + +https://huggingface.co/VMware/deberta-v3-xsmall-mrqa + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_pipeline_en.md new file mode 100644 index 00000000000000..4052d13d3eda0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_xsmall_pipeline pipeline DeBertaEmbeddings from microsoft +author: John Snow Labs +name: deberta_v3_xsmall_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_pipeline` is a English model originally trained by microsoft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_pipeline_en_5.5.0_3.0_1725229990617.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_pipeline_en_5.5.0_3.0_1725229990617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_xsmall_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_xsmall_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|167.8 MB| + +## References + +https://huggingface.co/microsoft/deberta-v3-xsmall + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_qa_squad2_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_qa_squad2_en.md new file mode 100644 index 00000000000000..f7bce3be6fef86 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_qa_squad2_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English DebertaForQuestionAnswering model (from nbroad) +author: John Snow Labs +name: deberta_v3_xsmall_qa_squad2 +date: 2024-09-01 +tags: [open_source, deberta, question_answering, en, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `deberta-v3-xsmall-squad2` is a English model originally trained by `nbroad`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qa_squad2_en_5.5.0_3.0_1725218883539.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qa_squad2_en_5.5.0_3.0_1725218883539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = DebertaForQuestionAnswering.pretrained("deberta_v3_xsmall_qa_squad2","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer")\ +.setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, spanClassifier]) + +data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifer = DebertaForQuestionAnswering.pretrained("deberta_v3_xsmall_qa_squad2","en") +.setInputCols(Array("document", "token")) +.setOutputCol("answer") +.setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) + +val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squadv2.deberta").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_qa_squad2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|250.6 MB| + +## References + +References + +https://huggingface.co/nbroad/deberta-v3-xsmall-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_qa_squad2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_qa_squad2_pipeline_en.md new file mode 100644 index 00000000000000..26d030f841794c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_qa_squad2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_xsmall_qa_squad2_pipeline pipeline DeBertaForQuestionAnswering from nbroad +author: John Snow Labs +name: deberta_v3_xsmall_qa_squad2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_qa_squad2_pipeline` is a English model originally trained by nbroad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qa_squad2_pipeline_en_5.5.0_3.0_1725218898939.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qa_squad2_pipeline_en_5.5.0_3.0_1725218898939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_xsmall_qa_squad2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_xsmall_qa_squad2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_qa_squad2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|250.6 MB| + +## References + +https://huggingface.co/nbroad/deberta-v3-xsmall-squad2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_squadv2_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_squadv2_en.md new file mode 100644 index 00000000000000..8f741e08d1e0d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_squadv2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_xsmall_squadv2 DeBertaForQuestionAnswering from cliang1453 +author: John Snow Labs +name: deberta_v3_xsmall_squadv2 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_squadv2` is a English model originally trained by cliang1453. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_squadv2_en_5.5.0_3.0_1725219458968.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_squadv2_en_5.5.0_3.0_1725219458968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_xsmall_squadv2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_xsmall_squadv2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_squadv2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|243.9 MB| + +## References + +https://huggingface.co/cliang1453/deberta-v3-xsmall-squadv2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_squadv2_pipeline_en.md new file mode 100644 index 00000000000000..ac5a70dc338b41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_xsmall_squadv2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_xsmall_squadv2_pipeline pipeline DeBertaForQuestionAnswering from cliang1453 +author: John Snow Labs +name: deberta_v3_xsmall_squadv2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_squadv2_pipeline` is a English model originally trained by cliang1453. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_squadv2_pipeline_en_5.5.0_3.0_1725219480441.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_squadv2_pipeline_en_5.5.0_3.0_1725219480441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_xsmall_squadv2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_xsmall_squadv2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_squadv2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.9 MB| + +## References + +https://huggingface.co/cliang1453/deberta-v3-xsmall-squadv2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-debertabaseeemotionbalanced_en.md b/docs/_posts/ahmedlone127/2024-09-01-debertabaseeemotionbalanced_en.md new file mode 100644 index 00000000000000..590a4c76d6960b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-debertabaseeemotionbalanced_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English debertabaseeemotionbalanced DeBertaForSequenceClassification from aliciiavs +author: John Snow Labs +name: debertabaseeemotionbalanced +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debertabaseeemotionbalanced` is a English model originally trained by aliciiavs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debertabaseeemotionbalanced_en_5.5.0_3.0_1725210701578.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debertabaseeemotionbalanced_en_5.5.0_3.0_1725210701578.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("debertabaseeemotionbalanced","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("debertabaseeemotionbalanced", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|debertabaseeemotionbalanced| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|593.4 MB| + +## References + +https://huggingface.co/aliciiavs/debertabaseeemotionbalanced \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-debertabaseeemotionbalanced_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-debertabaseeemotionbalanced_pipeline_en.md new file mode 100644 index 00000000000000..cba90c71ef4f4f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-debertabaseeemotionbalanced_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English debertabaseeemotionbalanced_pipeline pipeline DeBertaForSequenceClassification from aliciiavs +author: John Snow Labs +name: debertabaseeemotionbalanced_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debertabaseeemotionbalanced_pipeline` is a English model originally trained by aliciiavs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debertabaseeemotionbalanced_pipeline_en_5.5.0_3.0_1725210758426.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debertabaseeemotionbalanced_pipeline_en_5.5.0_3.0_1725210758426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("debertabaseeemotionbalanced_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("debertabaseeemotionbalanced_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|debertabaseeemotionbalanced_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|593.4 MB| + +## References + +https://huggingface.co/aliciiavs/debertabaseeemotionbalanced + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-debertav3small_nli4ct_en.md b/docs/_posts/ahmedlone127/2024-09-01-debertav3small_nli4ct_en.md new file mode 100644 index 00000000000000..cd1180b048f53b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-debertav3small_nli4ct_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English debertav3small_nli4ct DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: debertav3small_nli4ct +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debertav3small_nli4ct` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debertav3small_nli4ct_en_5.5.0_3.0_1725208910488.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debertav3small_nli4ct_en_5.5.0_3.0_1725208910488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("debertav3small_nli4ct","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("debertav3small_nli4ct", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|debertav3small_nli4ct| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|204.2 MB| + +## References + +https://huggingface.co/domenicrosati/debertav3small-NLI4CT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-debertav3small_nli4ct_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-debertav3small_nli4ct_pipeline_en.md new file mode 100644 index 00000000000000..499774c5a2c663 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-debertav3small_nli4ct_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English debertav3small_nli4ct_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: debertav3small_nli4ct_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debertav3small_nli4ct_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debertav3small_nli4ct_pipeline_en_5.5.0_3.0_1725208947008.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debertav3small_nli4ct_pipeline_en_5.5.0_3.0_1725208947008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("debertav3small_nli4ct_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("debertav3small_nli4ct_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|debertav3small_nli4ct_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|204.2 MB| + +## References + +https://huggingface.co/domenicrosati/debertav3small-NLI4CT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-declutr_emanuals_s10_arabic_en.md b/docs/_posts/ahmedlone127/2024-09-01-declutr_emanuals_s10_arabic_en.md new file mode 100644 index 00000000000000..f0eea2b56f0865 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-declutr_emanuals_s10_arabic_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English declutr_emanuals_s10_arabic RoBertaForSequenceClassification from AnonymousSub +author: John Snow Labs +name: declutr_emanuals_s10_arabic +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`declutr_emanuals_s10_arabic` is a English model originally trained by AnonymousSub. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/declutr_emanuals_s10_arabic_en_5.4.2_3.0_1725194310947.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/declutr_emanuals_s10_arabic_en_5.4.2_3.0_1725194310947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("declutr_emanuals_s10_arabic","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("declutr_emanuals_s10_arabic", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|declutr_emanuals_s10_arabic| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.2 MB| + +## References + +https://huggingface.co/AnonymousSub/declutr-emanuals-s10-AR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-declutr_emanuals_s10_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-declutr_emanuals_s10_arabic_pipeline_en.md new file mode 100644 index 00000000000000..54ac0e7205a6a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-declutr_emanuals_s10_arabic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English declutr_emanuals_s10_arabic_pipeline pipeline RoBertaForSequenceClassification from AnonymousSub +author: John Snow Labs +name: declutr_emanuals_s10_arabic_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`declutr_emanuals_s10_arabic_pipeline` is a English model originally trained by AnonymousSub. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/declutr_emanuals_s10_arabic_pipeline_en_5.4.2_3.0_1725194336506.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/declutr_emanuals_s10_arabic_pipeline_en_5.4.2_3.0_1725194336506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("declutr_emanuals_s10_arabic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("declutr_emanuals_s10_arabic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|declutr_emanuals_s10_arabic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/AnonymousSub/declutr-emanuals-s10-AR + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-declutr_s10_serbian_en.md b/docs/_posts/ahmedlone127/2024-09-01-declutr_s10_serbian_en.md new file mode 100644 index 00000000000000..c0594e46f417fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-declutr_s10_serbian_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English declutr_s10_serbian RoBertaForSequenceClassification from AnonymousSub +author: John Snow Labs +name: declutr_s10_serbian +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`declutr_s10_serbian` is a English model originally trained by AnonymousSub. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/declutr_s10_serbian_en_5.4.2_3.0_1725194550679.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/declutr_s10_serbian_en_5.4.2_3.0_1725194550679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("declutr_s10_serbian","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("declutr_s10_serbian", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|declutr_s10_serbian| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|309.1 MB| + +## References + +https://huggingface.co/AnonymousSub/declutr-s10-SR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-declutr_s10_serbian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-declutr_s10_serbian_pipeline_en.md new file mode 100644 index 00000000000000..14ef98a699bbb2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-declutr_s10_serbian_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English declutr_s10_serbian_pipeline pipeline RoBertaForSequenceClassification from AnonymousSub +author: John Snow Labs +name: declutr_s10_serbian_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`declutr_s10_serbian_pipeline` is a English model originally trained by AnonymousSub. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/declutr_s10_serbian_pipeline_en_5.4.2_3.0_1725194568114.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/declutr_s10_serbian_pipeline_en_5.4.2_3.0_1725194568114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("declutr_s10_serbian_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("declutr_s10_serbian_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|declutr_s10_serbian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|309.1 MB| + +## References + +https://huggingface.co/AnonymousSub/declutr-s10-SR + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deepak_deberta_v3_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-deepak_deberta_v3_base_en.md new file mode 100644 index 00000000000000..d0d3030e4d50dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deepak_deberta_v3_base_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deepak_deberta_v3_base DeBertaForQuestionAnswering from satishsingh90 +author: John Snow Labs +name: deepak_deberta_v3_base +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepak_deberta_v3_base` is a English model originally trained by satishsingh90. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepak_deberta_v3_base_en_5.5.0_3.0_1725221463190.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepak_deberta_v3_base_en_5.5.0_3.0_1725221463190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deepak_deberta_v3_base","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deepak_deberta_v3_base", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deepak_deberta_v3_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|565.7 MB| + +## References + +https://huggingface.co/satishsingh90/deepak_deberta_v3_base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-deepak_deberta_v3_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deepak_deberta_v3_base_pipeline_en.md new file mode 100644 index 00000000000000..82ef23e526a70e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-deepak_deberta_v3_base_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deepak_deberta_v3_base_pipeline pipeline DeBertaForQuestionAnswering from satishsingh90 +author: John Snow Labs +name: deepak_deberta_v3_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepak_deberta_v3_base_pipeline` is a English model originally trained by satishsingh90. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepak_deberta_v3_base_pipeline_en_5.5.0_3.0_1725221550326.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepak_deberta_v3_base_pipeline_en_5.5.0_3.0_1725221550326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deepak_deberta_v3_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deepak_deberta_v3_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deepak_deberta_v3_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|565.7 MB| + +## References + +https://huggingface.co/satishsingh90/deepak_deberta_v3_base + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-detect_acoso_twitter_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-01-detect_acoso_twitter_spanish_es.md new file mode 100644 index 00000000000000..ef0148ac3164b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-detect_acoso_twitter_spanish_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish detect_acoso_twitter_spanish RoBertaForSequenceClassification from somosnlp-hackathon-2022 +author: John Snow Labs +name: detect_acoso_twitter_spanish +date: 2024-09-01 +tags: [es, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`detect_acoso_twitter_spanish` is a Castilian, Spanish model originally trained by somosnlp-hackathon-2022. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/detect_acoso_twitter_spanish_es_5.5.0_3.0_1725212630355.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/detect_acoso_twitter_spanish_es_5.5.0_3.0_1725212630355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("detect_acoso_twitter_spanish","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("detect_acoso_twitter_spanish", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|detect_acoso_twitter_spanish| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|308.9 MB| + +## References + +https://huggingface.co/somosnlp-hackathon-2022/Detect-Acoso-Twitter-Es \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-detect_acoso_twitter_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-detect_acoso_twitter_spanish_pipeline_es.md new file mode 100644 index 00000000000000..753019463857d3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-detect_acoso_twitter_spanish_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish detect_acoso_twitter_spanish_pipeline pipeline RoBertaForSequenceClassification from somosnlp-hackathon-2022 +author: John Snow Labs +name: detect_acoso_twitter_spanish_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`detect_acoso_twitter_spanish_pipeline` is a Castilian, Spanish model originally trained by somosnlp-hackathon-2022. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/detect_acoso_twitter_spanish_pipeline_es_5.5.0_3.0_1725212646795.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/detect_acoso_twitter_spanish_pipeline_es_5.5.0_3.0_1725212646795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("detect_acoso_twitter_spanish_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("detect_acoso_twitter_spanish_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|detect_acoso_twitter_spanish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|309.0 MB| + +## References + +https://huggingface.co/somosnlp-hackathon-2022/Detect-Acoso-Twitter-Es + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distil_bert_fintuned_product_cfpb_complaints_en.md b/docs/_posts/ahmedlone127/2024-09-01-distil_bert_fintuned_product_cfpb_complaints_en.md new file mode 100644 index 00000000000000..1b1a7b346f558f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distil_bert_fintuned_product_cfpb_complaints_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distil_bert_fintuned_product_cfpb_complaints DistilBertForSequenceClassification from Mahesh9 +author: John Snow Labs +name: distil_bert_fintuned_product_cfpb_complaints +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_fintuned_product_cfpb_complaints` is a English model originally trained by Mahesh9. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_fintuned_product_cfpb_complaints_en_5.5.0_3.0_1725213964433.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_fintuned_product_cfpb_complaints_en_5.5.0_3.0_1725213964433.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distil_bert_fintuned_product_cfpb_complaints","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distil_bert_fintuned_product_cfpb_complaints", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distil_bert_fintuned_product_cfpb_complaints| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Mahesh9/distil-bert-fintuned-product-cfpb-complaints \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distil_bert_fintuned_product_cfpb_complaints_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distil_bert_fintuned_product_cfpb_complaints_pipeline_en.md new file mode 100644 index 00000000000000..ba877c8b441b2f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distil_bert_fintuned_product_cfpb_complaints_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distil_bert_fintuned_product_cfpb_complaints_pipeline pipeline DistilBertForSequenceClassification from Mahesh9 +author: John Snow Labs +name: distil_bert_fintuned_product_cfpb_complaints_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_fintuned_product_cfpb_complaints_pipeline` is a English model originally trained by Mahesh9. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_fintuned_product_cfpb_complaints_pipeline_en_5.5.0_3.0_1725213978083.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_fintuned_product_cfpb_complaints_pipeline_en_5.5.0_3.0_1725213978083.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distil_bert_fintuned_product_cfpb_complaints_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distil_bert_fintuned_product_cfpb_complaints_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distil_bert_fintuned_product_cfpb_complaints_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Mahesh9/distil-bert-fintuned-product-cfpb-complaints + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distil_train_token_classification_2_en.md b/docs/_posts/ahmedlone127/2024-09-01-distil_train_token_classification_2_en.md new file mode 100644 index 00000000000000..3bd424072b314a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distil_train_token_classification_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distil_train_token_classification_2 DistilBertForTokenClassification from ymgong +author: John Snow Labs +name: distil_train_token_classification_2 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_train_token_classification_2` is a English model originally trained by ymgong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_train_token_classification_2_en_5.4.2_3.0_1725172515284.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_train_token_classification_2_en_5.4.2_3.0_1725172515284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distil_train_token_classification_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distil_train_token_classification_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distil_train_token_classification_2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/ymgong/distil_train_token_classification_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_adarsh2350_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_adarsh2350_en.md new file mode 100644 index 00000000000000..310498b145f54e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_adarsh2350_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_adarsh2350 DistilBertForTokenClassification from adarsh2350 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_adarsh2350 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_adarsh2350` is a English model originally trained by adarsh2350. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_adarsh2350_en_5.4.2_3.0_1725171390816.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_adarsh2350_en_5.4.2_3.0_1725171390816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_adarsh2350","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_adarsh2350", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_adarsh2350| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/adarsh2350/distilbert-base-uncased-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_adarsh2350_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_adarsh2350_pipeline_en.md new file mode 100644 index 00000000000000..202f9de3a78011 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_adarsh2350_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_adarsh2350_pipeline pipeline DistilBertForTokenClassification from adarsh2350 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_adarsh2350_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_adarsh2350_pipeline` is a English model originally trained by adarsh2350. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_adarsh2350_pipeline_en_5.4.2_3.0_1725171404884.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_adarsh2350_pipeline_en_5.4.2_3.0_1725171404884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_adarsh2350_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_adarsh2350_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_adarsh2350_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/adarsh2350/distilbert-base-uncased-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_en.md new file mode 100644 index 00000000000000..f4a8513c687d18 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis DistilBertForTokenClassification from mireiaplalis +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis` is a English model originally trained by mireiaplalis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_en_5.4.2_3.0_1725170850420.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_en_5.4.2_3.0_1725170850420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/mireiaplalis/distilbert-base-uncased-finetuned-ner-cadec \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_pipeline_en.md new file mode 100644 index 00000000000000..180b87ef1cee45 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_pipeline pipeline DistilBertForTokenClassification from mireiaplalis +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_pipeline` is a English model originally trained by mireiaplalis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_pipeline_en_5.4.2_3.0_1725170864532.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_pipeline_en_5.4.2_3.0_1725170864532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_cadec_mireiaplalis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/mireiaplalis/distilbert-base-uncased-finetuned-ner-cadec + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_hfdsajkfd_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_hfdsajkfd_en.md new file mode 100644 index 00000000000000..b995752e83bc84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_hfdsajkfd_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_hfdsajkfd DistilBertForTokenClassification from hfdsajkfd +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_hfdsajkfd +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_hfdsajkfd` is a English model originally trained by hfdsajkfd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_hfdsajkfd_en_5.4.2_3.0_1725170741185.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_hfdsajkfd_en_5.4.2_3.0_1725170741185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_hfdsajkfd","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_hfdsajkfd", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_hfdsajkfd| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/hfdsajkfd/distilbert-base-uncased-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_hfdsajkfd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_hfdsajkfd_pipeline_en.md new file mode 100644 index 00000000000000..958311c17f99c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_hfdsajkfd_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_hfdsajkfd_pipeline pipeline DistilBertForTokenClassification from hfdsajkfd +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_hfdsajkfd_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_hfdsajkfd_pipeline` is a English model originally trained by hfdsajkfd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_hfdsajkfd_pipeline_en_5.4.2_3.0_1725170756884.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_hfdsajkfd_pipeline_en_5.4.2_3.0_1725170756884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_hfdsajkfd_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_hfdsajkfd_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_hfdsajkfd_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/hfdsajkfd/distilbert-base-uncased-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_kamaljp_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_kamaljp_en.md new file mode 100644 index 00000000000000..a7465887de9215 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_kamaljp_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_kamaljp DistilBertForTokenClassification from Kamaljp +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_kamaljp +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_kamaljp` is a English model originally trained by Kamaljp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_kamaljp_en_5.4.2_3.0_1725171044614.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_kamaljp_en_5.4.2_3.0_1725171044614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_kamaljp","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_kamaljp", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_kamaljp| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/Kamaljp/distilbert-base-uncased-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_neverlearn_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_neverlearn_en.md new file mode 100644 index 00000000000000..287894a8881953 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_neverlearn_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_neverlearn DistilBertForTokenClassification from NeverLearn +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_neverlearn +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_neverlearn` is a English model originally trained by NeverLearn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_neverlearn_en_5.4.2_3.0_1725161155514.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_neverlearn_en_5.4.2_3.0_1725161155514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_neverlearn","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_neverlearn", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_neverlearn| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.5 MB| + +## References + +https://huggingface.co/NeverLearn/distilbert-base-uncased-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_seri0uslee_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_seri0uslee_pipeline_en.md new file mode 100644 index 00000000000000..a12c5f8a60f9c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_seri0uslee_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_seri0uslee_pipeline pipeline DistilBertForTokenClassification from Seri0usLee +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_seri0uslee_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_seri0uslee_pipeline` is a English model originally trained by Seri0usLee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_seri0uslee_pipeline_en_5.4.2_3.0_1725172224498.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_seri0uslee_pipeline_en_5.4.2_3.0_1725172224498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_seri0uslee_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_seri0uslee_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_seri0uslee_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/Seri0usLee/distilbert-base-uncased-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_smmgh_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_smmgh_en.md new file mode 100644 index 00000000000000..aacdb5b9df2f13 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_smmgh_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_smmgh DistilBertForTokenClassification from smmgh +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_smmgh +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_smmgh` is a English model originally trained by smmgh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_smmgh_en_5.4.2_3.0_1725172318876.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_smmgh_en_5.4.2_3.0_1725172318876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_smmgh","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_smmgh", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_smmgh| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/smmgh/distilbert-base-uncased-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_smmgh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_smmgh_pipeline_en.md new file mode 100644 index 00000000000000..bc492a6add896d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_smmgh_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_smmgh_pipeline pipeline DistilBertForTokenClassification from smmgh +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_smmgh_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_smmgh_pipeline` is a English model originally trained by smmgh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_smmgh_pipeline_en_5.4.2_3.0_1725172332381.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_smmgh_pipeline_en_5.4.2_3.0_1725172332381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_smmgh_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_smmgh_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_smmgh_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/smmgh/distilbert-base-uncased-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_somskat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_somskat_pipeline_en.md new file mode 100644 index 00000000000000..e2c364435dd9b0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_ner_somskat_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_somskat_pipeline pipeline DistilBertForTokenClassification from somskat +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_somskat_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_somskat_pipeline` is a English model originally trained by somskat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_somskat_pipeline_en_5.4.2_3.0_1725171883351.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_somskat_pipeline_en_5.4.2_3.0_1725171883351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_somskat_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_somskat_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_somskat_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.4 MB| + +## References + +https://huggingface.co/somskat/distilbert-base-uncased-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_srl_abritez_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_srl_abritez_pipeline_en.md new file mode 100644 index 00000000000000..f9f7f621401f7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_finetuned_srl_abritez_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_srl_abritez_pipeline pipeline DistilBertForTokenClassification from abritez +author: John Snow Labs +name: distilbert_base_uncased_finetuned_srl_abritez_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_srl_abritez_pipeline` is a English model originally trained by abritez. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_srl_abritez_pipeline_en_5.4.2_3.0_1725171722365.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_srl_abritez_pipeline_en_5.4.2_3.0_1725171722365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_srl_abritez_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_srl_abritez_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_srl_abritez_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.4 MB| + +## References + +https://huggingface.co/abritez/distilbert-base-uncased-finetuned-srl + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_german_nrp_codes_entry_classification_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_german_nrp_codes_entry_classification_en.md new file mode 100644 index 00000000000000..c1770cb4455171 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_german_nrp_codes_entry_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_german_nrp_codes_entry_classification DistilBertForSequenceClassification from reflex-project +author: John Snow Labs +name: distilbert_base_uncased_german_nrp_codes_entry_classification +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_german_nrp_codes_entry_classification` is a English model originally trained by reflex-project. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_german_nrp_codes_entry_classification_en_5.5.0_3.0_1725214067885.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_german_nrp_codes_entry_classification_en_5.5.0_3.0_1725214067885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_german_nrp_codes_entry_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_german_nrp_codes_entry_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_german_nrp_codes_entry_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/reflex-project/distilbert-base-uncased-german-nrp-codes-entry-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_german_nrp_codes_entry_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_german_nrp_codes_entry_classification_pipeline_en.md new file mode 100644 index 00000000000000..ad9d657cfe4a8a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_german_nrp_codes_entry_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_german_nrp_codes_entry_classification_pipeline pipeline DistilBertForSequenceClassification from reflex-project +author: John Snow Labs +name: distilbert_base_uncased_german_nrp_codes_entry_classification_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_german_nrp_codes_entry_classification_pipeline` is a English model originally trained by reflex-project. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_german_nrp_codes_entry_classification_pipeline_en_5.5.0_3.0_1725214081636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_german_nrp_codes_entry_classification_pipeline_en_5.5.0_3.0_1725214081636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_german_nrp_codes_entry_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_german_nrp_codes_entry_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_german_nrp_codes_entry_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/reflex-project/distilbert-base-uncased-german-nrp-codes-entry-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_imdb_gregorrus_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_imdb_gregorrus_en.md new file mode 100644 index 00000000000000..b723e23fae290f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_imdb_gregorrus_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_imdb_gregorrus DistilBertForSequenceClassification from GregorRus +author: John Snow Labs +name: distilbert_base_uncased_imdb_gregorrus +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_imdb_gregorrus` is a English model originally trained by GregorRus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_imdb_gregorrus_en_5.5.0_3.0_1725213692347.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_imdb_gregorrus_en_5.5.0_3.0_1725213692347.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_imdb_gregorrus","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_imdb_gregorrus", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_imdb_gregorrus| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/GregorRus/distilbert-base-uncased-imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_imdb_gregorrus_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_imdb_gregorrus_pipeline_en.md new file mode 100644 index 00000000000000..ce65c54b145688 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_base_uncased_imdb_gregorrus_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_imdb_gregorrus_pipeline pipeline DistilBertForSequenceClassification from GregorRus +author: John Snow Labs +name: distilbert_base_uncased_imdb_gregorrus_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_imdb_gregorrus_pipeline` is a English model originally trained by GregorRus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_imdb_gregorrus_pipeline_en_5.5.0_3.0_1725213706025.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_imdb_gregorrus_pipeline_en_5.5.0_3.0_1725213706025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_imdb_gregorrus_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_imdb_gregorrus_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_imdb_gregorrus_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/GregorRus/distilbert-base-uncased-imdb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_cased_lft_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_cased_lft_pipeline_en.md new file mode 100644 index 00000000000000..5a19fa85174451 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_cased_lft_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_cased_lft_pipeline pipeline DistilBertForTokenClassification from praysimanjuntak +author: John Snow Labs +name: distilbert_cased_lft_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_cased_lft_pipeline` is a English model originally trained by praysimanjuntak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_cased_lft_pipeline_en_5.4.2_3.0_1725161278744.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_cased_lft_pipeline_en_5.4.2_3.0_1725161278744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_cased_lft_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_cased_lft_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_cased_lft_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/praysimanjuntak/distilbert-cased-lft + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_finetuned_ner_for_articles_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_finetuned_ner_for_articles_en.md new file mode 100644 index 00000000000000..2a67ae6f30322f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_finetuned_ner_for_articles_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_finetuned_ner_for_articles DistilBertForTokenClassification from colette-exe +author: John Snow Labs +name: distilbert_finetuned_ner_for_articles +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner_for_articles` is a English model originally trained by colette-exe. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_for_articles_en_5.4.2_3.0_1725161366171.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_for_articles_en_5.4.2_3.0_1725161366171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner_for_articles","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner_for_articles", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_finetuned_ner_for_articles| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/colette-exe/distilbert-finetuned-ner-for-articles \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_finetuned_ner_tushifire_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_finetuned_ner_tushifire_en.md new file mode 100644 index 00000000000000..33e08ca0d72ad0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_finetuned_ner_tushifire_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_finetuned_ner_tushifire DistilBertForTokenClassification from tushifire +author: John Snow Labs +name: distilbert_finetuned_ner_tushifire +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner_tushifire` is a English model originally trained by tushifire. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_tushifire_en_5.4.2_3.0_1725171972383.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_tushifire_en_5.4.2_3.0_1725171972383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner_tushifire","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner_tushifire", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_finetuned_ner_tushifire| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|243.9 MB| + +## References + +https://huggingface.co/tushifire/distilbert-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_finetuned_ner_tushifire_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_finetuned_ner_tushifire_pipeline_en.md new file mode 100644 index 00000000000000..b6bfac93dbe032 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_finetuned_ner_tushifire_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_finetuned_ner_tushifire_pipeline pipeline DistilBertForTokenClassification from tushifire +author: John Snow Labs +name: distilbert_finetuned_ner_tushifire_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner_tushifire_pipeline` is a English model originally trained by tushifire. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_tushifire_pipeline_en_5.4.2_3.0_1725171985351.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_tushifire_pipeline_en_5.4.2_3.0_1725171985351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_finetuned_ner_tushifire_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_finetuned_ner_tushifire_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_finetuned_ner_tushifire_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.9 MB| + +## References + +https://huggingface.co/tushifire/distilbert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_infoextract_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_infoextract_v2_pipeline_en.md new file mode 100644 index 00000000000000..3240ecad5b2f00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_infoextract_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_infoextract_v2_pipeline pipeline DistilBertForTokenClassification from tony4194 +author: John Snow Labs +name: distilbert_infoextract_v2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_infoextract_v2_pipeline` is a English model originally trained by tony4194. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_infoextract_v2_pipeline_en_5.4.2_3.0_1725172425461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_infoextract_v2_pipeline_en_5.4.2_3.0_1725172425461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_infoextract_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_infoextract_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_infoextract_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/tony4194/distilBERT-infoExtract-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_infoextract_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_infoextract_v3_pipeline_en.md new file mode 100644 index 00000000000000..65684ffc96a088 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_infoextract_v3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_infoextract_v3_pipeline pipeline DistilBertForTokenClassification from tony4194 +author: John Snow Labs +name: distilbert_infoextract_v3_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_infoextract_v3_pipeline` is a English model originally trained by tony4194. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_infoextract_v3_pipeline_en_5.4.2_3.0_1725172250704.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_infoextract_v3_pipeline_en_5.4.2_3.0_1725172250704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_infoextract_v3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_infoextract_v3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_infoextract_v3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/tony4194/distilBERT-infoExtract-v3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_nepali_ner_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_nepali_ner_en.md new file mode 100644 index 00000000000000..5ef4b9299e6e4f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_nepali_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_nepali_ner DistilBertForTokenClassification from Saugatkafley +author: John Snow Labs +name: distilbert_nepali_ner +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_nepali_ner` is a English model originally trained by Saugatkafley. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_nepali_ner_en_5.4.2_3.0_1725171983024.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_nepali_ner_en_5.4.2_3.0_1725171983024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_nepali_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_nepali_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_nepali_ner| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/Saugatkafley/distilbert-Nepali-NER \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_ner_saugatkafley_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_ner_saugatkafley_en.md new file mode 100644 index 00000000000000..e56d3a0aa77de7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_ner_saugatkafley_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_ner_saugatkafley DistilBertForTokenClassification from Saugatkafley +author: John Snow Labs +name: distilbert_ner_saugatkafley +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_saugatkafley` is a English model originally trained by Saugatkafley. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_saugatkafley_en_5.4.2_3.0_1725171414233.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_saugatkafley_en_5.4.2_3.0_1725171414233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_saugatkafley","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_saugatkafley", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_ner_saugatkafley| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/Saugatkafley/distilbert-NER \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_republican_democrat_tweets_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_republican_democrat_tweets_en.md new file mode 100644 index 00000000000000..f3967ebbd19e3f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_republican_democrat_tweets_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_republican_democrat_tweets DistilBertForSequenceClassification from juliovp +author: John Snow Labs +name: distilbert_republican_democrat_tweets +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_republican_democrat_tweets` is a English model originally trained by juliovp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_republican_democrat_tweets_en_5.5.0_3.0_1725213725237.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_republican_democrat_tweets_en_5.5.0_3.0_1725213725237.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_republican_democrat_tweets","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_republican_democrat_tweets", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_republican_democrat_tweets| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/juliovp/distilbert_republican_democrat_tweets \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_republican_democrat_tweets_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_republican_democrat_tweets_pipeline_en.md new file mode 100644 index 00000000000000..450c3cf5b73704 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_republican_democrat_tweets_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_republican_democrat_tweets_pipeline pipeline DistilBertForSequenceClassification from juliovp +author: John Snow Labs +name: distilbert_republican_democrat_tweets_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_republican_democrat_tweets_pipeline` is a English model originally trained by juliovp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_republican_democrat_tweets_pipeline_en_5.5.0_3.0_1725213744654.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_republican_democrat_tweets_pipeline_en_5.5.0_3.0_1725213744654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_republican_democrat_tweets_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_republican_democrat_tweets_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_republican_democrat_tweets_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/juliovp/distilbert_republican_democrat_tweets + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_sentiment_analysis_dt12the_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_sentiment_analysis_dt12the_en.md new file mode 100644 index 00000000000000..8b48082fdbe658 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_sentiment_analysis_dt12the_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_sentiment_analysis_dt12the DistilBertForSequenceClassification from DT12the +author: John Snow Labs +name: distilbert_sentiment_analysis_dt12the +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sentiment_analysis_dt12the` is a English model originally trained by DT12the. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sentiment_analysis_dt12the_en_5.5.0_3.0_1725214150213.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sentiment_analysis_dt12the_en_5.5.0_3.0_1725214150213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sentiment_analysis_dt12the","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sentiment_analysis_dt12the", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_sentiment_analysis_dt12the| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/DT12the/distilbert-sentiment-analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_sentiment_analysis_dt12the_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_sentiment_analysis_dt12the_pipeline_en.md new file mode 100644 index 00000000000000..027a04caedc886 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_sentiment_analysis_dt12the_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_sentiment_analysis_dt12the_pipeline pipeline DistilBertForSequenceClassification from DT12the +author: John Snow Labs +name: distilbert_sentiment_analysis_dt12the_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sentiment_analysis_dt12the_pipeline` is a English model originally trained by DT12the. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sentiment_analysis_dt12the_pipeline_en_5.5.0_3.0_1725214165014.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sentiment_analysis_dt12the_pipeline_en_5.5.0_3.0_1725214165014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_sentiment_analysis_dt12the_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_sentiment_analysis_dt12the_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_sentiment_analysis_dt12the_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/DT12the/distilbert-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_turkish_turkish_product_reviews_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_turkish_turkish_product_reviews_pipeline_tr.md new file mode 100644 index 00000000000000..74e056773ce9cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_turkish_turkish_product_reviews_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish distilbert_turkish_turkish_product_reviews_pipeline pipeline DistilBertForSequenceClassification from anilguven +author: John Snow Labs +name: distilbert_turkish_turkish_product_reviews_pipeline +date: 2024-09-01 +tags: [tr, open_source, pipeline, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_turkish_turkish_product_reviews_pipeline` is a Turkish model originally trained by anilguven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_turkish_turkish_product_reviews_pipeline_tr_5.5.0_3.0_1725213537837.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_turkish_turkish_product_reviews_pipeline_tr_5.5.0_3.0_1725213537837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_turkish_turkish_product_reviews_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_turkish_turkish_product_reviews_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_turkish_turkish_product_reviews_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|254.1 MB| + +## References + +https://huggingface.co/anilguven/distilbert_tr_turkish_product_reviews + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilbert_turkish_turkish_product_reviews_tr.md b/docs/_posts/ahmedlone127/2024-09-01-distilbert_turkish_turkish_product_reviews_tr.md new file mode 100644 index 00000000000000..48c3c307ca37ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilbert_turkish_turkish_product_reviews_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish distilbert_turkish_turkish_product_reviews DistilBertForSequenceClassification from anilguven +author: John Snow Labs +name: distilbert_turkish_turkish_product_reviews +date: 2024-09-01 +tags: [tr, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_turkish_turkish_product_reviews` is a Turkish model originally trained by anilguven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_turkish_turkish_product_reviews_tr_5.5.0_3.0_1725213521076.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_turkish_turkish_product_reviews_tr_5.5.0_3.0_1725213521076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_turkish_turkish_product_reviews","tr") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_turkish_turkish_product_reviews", "tr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_turkish_turkish_product_reviews| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|254.1 MB| + +## References + +https://huggingface.co/anilguven/distilbert_tr_turkish_product_reviews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilroberta_base_climate_s_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilroberta_base_climate_s_pipeline_en.md new file mode 100644 index 00000000000000..5999bfd5bc9e45 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilroberta_base_climate_s_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilroberta_base_climate_s_pipeline pipeline RoBertaEmbeddings from climatebert +author: John Snow Labs +name: distilroberta_base_climate_s_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_climate_s_pipeline` is a English model originally trained by climatebert. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_climate_s_pipeline_en_5.4.2_3.0_1725191358254.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_climate_s_pipeline_en_5.4.2_3.0_1725191358254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilroberta_base_climate_s_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilroberta_base_climate_s_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilroberta_base_climate_s_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|307.4 MB| + +## References + +https://huggingface.co/climatebert/distilroberta-base-climate-s + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilroberta_topic_classification_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilroberta_topic_classification_en.md new file mode 100644 index 00000000000000..3e1c6278fd133a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilroberta_topic_classification_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English distilroberta_topic_classification RoBertaForSequenceClassification from abdulmatinomotoso +author: John Snow Labs +name: distilroberta_topic_classification +date: 2024-09-01 +tags: [roberta, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_topic_classification` is a English model originally trained by abdulmatinomotoso. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_topic_classification_en_5.4.2_3.0_1725194318238.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_topic_classification_en_5.4.2_3.0_1725194318238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_topic_classification","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_topic_classification","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilroberta_topic_classification| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|309.4 MB| + +## References + +References + +https://huggingface.co/abdulmatinomotoso/distilroberta-topic-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-distilroberta_topic_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-distilroberta_topic_classification_pipeline_en.md new file mode 100644 index 00000000000000..02f6fa1993924a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-distilroberta_topic_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilroberta_topic_classification_pipeline pipeline RoBertaForSequenceClassification from valurank +author: John Snow Labs +name: distilroberta_topic_classification_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_topic_classification_pipeline` is a English model originally trained by valurank. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_topic_classification_pipeline_en_5.4.2_3.0_1725194335418.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_topic_classification_pipeline_en_5.4.2_3.0_1725194335418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilroberta_topic_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilroberta_topic_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilroberta_topic_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|309.4 MB| + +## References + +https://huggingface.co/valurank/distilroberta-topic-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-drone_sbert_en.md b/docs/_posts/ahmedlone127/2024-09-01-drone_sbert_en.md new file mode 100644 index 00000000000000..858cd7a8acbe8e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-drone_sbert_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English drone_sbert MPNetEmbeddings from swardiantara +author: John Snow Labs +name: drone_sbert +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`drone_sbert` is a English model originally trained by swardiantara. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/drone_sbert_en_5.5.0_3.0_1725225079263.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/drone_sbert_en_5.5.0_3.0_1725225079263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("drone_sbert","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("drone_sbert","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|drone_sbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/swardiantara/drone-sbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-drone_sbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-drone_sbert_pipeline_en.md new file mode 100644 index 00000000000000..ec8b97b89710e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-drone_sbert_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English drone_sbert_pipeline pipeline MPNetEmbeddings from swardiantara +author: John Snow Labs +name: drone_sbert_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`drone_sbert_pipeline` is a English model originally trained by swardiantara. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/drone_sbert_pipeline_en_5.5.0_3.0_1725225101218.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/drone_sbert_pipeline_en_5.5.0_3.0_1725225101218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("drone_sbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("drone_sbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|drone_sbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/swardiantara/drone-sbert + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-e5_large_v2_mnli_anli_en.md b/docs/_posts/ahmedlone127/2024-09-01-e5_large_v2_mnli_anli_en.md new file mode 100644 index 00000000000000..fa3ea33849fcf9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-e5_large_v2_mnli_anli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English e5_large_v2_mnli_anli BertForZeroShotClassification from mjwong +author: John Snow Labs +name: e5_large_v2_mnli_anli +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_v2_mnli_anli` is a English model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_v2_mnli_anli_en_5.5.0_3.0_1725214494401.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_v2_mnli_anli_en_5.5.0_3.0_1725214494401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("e5_large_v2_mnli_anli","en") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("e5_large_v2_mnli_anli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_large_v2_mnli_anli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/mjwong/e5-large-v2-mnli-anli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-e5_large_v2_mnli_anli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-e5_large_v2_mnli_anli_pipeline_en.md new file mode 100644 index 00000000000000..e3d3e9a09277f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-e5_large_v2_mnli_anli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English e5_large_v2_mnli_anli_pipeline pipeline BertForZeroShotClassification from mjwong +author: John Snow Labs +name: e5_large_v2_mnli_anli_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_v2_mnli_anli_pipeline` is a English model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_v2_mnli_anli_pipeline_en_5.5.0_3.0_1725214572461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_v2_mnli_anli_pipeline_en_5.5.0_3.0_1725214572461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_large_v2_mnli_anli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_large_v2_mnli_anli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_large_v2_mnli_anli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/mjwong/e5-large-v2-mnli-anli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-e5_large_v2_mnli_en.md b/docs/_posts/ahmedlone127/2024-09-01-e5_large_v2_mnli_en.md new file mode 100644 index 00000000000000..59fe07c2b6ddae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-e5_large_v2_mnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English e5_large_v2_mnli BertForZeroShotClassification from mjwong +author: John Snow Labs +name: e5_large_v2_mnli +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_v2_mnli` is a English model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_v2_mnli_en_5.4.2_3.0_1725208422586.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_v2_mnli_en_5.4.2_3.0_1725208422586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("e5_large_v2_mnli","en") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("e5_large_v2_mnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_large_v2_mnli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/mjwong/e5-large-v2-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-e5_large_v2_mnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-e5_large_v2_mnli_pipeline_en.md new file mode 100644 index 00000000000000..ee434406bc700f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-e5_large_v2_mnli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English e5_large_v2_mnli_pipeline pipeline BertForZeroShotClassification from mjwong +author: John Snow Labs +name: e5_large_v2_mnli_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_v2_mnli_pipeline` is a English model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_v2_mnli_pipeline_en_5.5.0_3.0_1725214571996.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_v2_mnli_pipeline_en_5.5.0_3.0_1725214571996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_large_v2_mnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_large_v2_mnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_large_v2_mnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/mjwong/e5-large-v2-mnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-electra_qa_large_discriminator_squad2_custom_dataset_en.md b/docs/_posts/ahmedlone127/2024-09-01-electra_qa_large_discriminator_squad2_custom_dataset_en.md new file mode 100644 index 00000000000000..09855963beff68 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-electra_qa_large_discriminator_squad2_custom_dataset_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English ElectraForQuestionAnswering model (from superspray) +author: John Snow Labs +name: electra_qa_large_discriminator_squad2_custom_dataset +date: 2024-09-01 +tags: [en, open_source, electra, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra_large_discriminator_squad2_custom_dataset` is a English model originally trained by `superspray`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_large_discriminator_squad2_custom_dataset_en_5.5.0_3.0_1725215081776.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_large_discriminator_squad2_custom_dataset_en_5.5.0_3.0_1725215081776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_large_discriminator_squad2_custom_dataset","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer")\ +.setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, spanClassifier]) + +data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_large_discriminator_squad2_custom_dataset","en") +.setInputCols(Array("document", "token")) +.setOutputCol("answer") +.setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) + +val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squadv2.electra.large.by_superspray").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|electra_qa_large_discriminator_squad2_custom_dataset| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +References + +- https://huggingface.co/superspray/electra_large_discriminator_squad2_custom_dataset \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-electra_qa_large_discriminator_squad2_custom_dataset_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-electra_qa_large_discriminator_squad2_custom_dataset_pipeline_en.md new file mode 100644 index 00000000000000..f1ca473b7003cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-electra_qa_large_discriminator_squad2_custom_dataset_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English electra_qa_large_discriminator_squad2_custom_dataset_pipeline pipeline BertForQuestionAnswering from superspray +author: John Snow Labs +name: electra_qa_large_discriminator_squad2_custom_dataset_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_large_discriminator_squad2_custom_dataset_pipeline` is a English model originally trained by superspray. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_large_discriminator_squad2_custom_dataset_pipeline_en_5.5.0_3.0_1725215151310.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_large_discriminator_squad2_custom_dataset_pipeline_en_5.5.0_3.0_1725215151310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("electra_qa_large_discriminator_squad2_custom_dataset_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("electra_qa_large_discriminator_squad2_custom_dataset_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|electra_qa_large_discriminator_squad2_custom_dataset_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/superspray/electra_large_discriminator_squad2_custom_dataset + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-electra_qa_large_squad_en.md b/docs/_posts/ahmedlone127/2024-09-01-electra_qa_large_squad_en.md new file mode 100644 index 00000000000000..ecc54fadbcc032 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-electra_qa_large_squad_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English ElectraForQuestionAnswering model (from howey) +author: John Snow Labs +name: electra_qa_large_squad +date: 2024-09-01 +tags: [en, open_source, electra, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-large-squad` is a English model originally trained by `howey`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_large_squad_en_5.5.0_3.0_1725214943555.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_large_squad_en_5.5.0_3.0_1725214943555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_large_squad","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer")\ +.setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, spanClassifier]) + +data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_large_squad","en") +.setInputCols(Array("document", "token")) +.setOutputCol("answer") +.setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) + +val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squad.electra.large").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|electra_qa_large_squad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +References + +- https://huggingface.co/howey/electra-large-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-electra_qa_large_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-electra_qa_large_squad_pipeline_en.md new file mode 100644 index 00000000000000..6464672becff0e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-electra_qa_large_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English electra_qa_large_squad_pipeline pipeline BertForQuestionAnswering from howey +author: John Snow Labs +name: electra_qa_large_squad_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_large_squad_pipeline` is a English model originally trained by howey. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_large_squad_pipeline_en_5.5.0_3.0_1725215009703.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_large_squad_pipeline_en_5.5.0_3.0_1725215009703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("electra_qa_large_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("electra_qa_large_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|electra_qa_large_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/howey/electra-large-squad + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-emo_mobilebert_lordtt13_en.md b/docs/_posts/ahmedlone127/2024-09-01-emo_mobilebert_lordtt13_en.md new file mode 100644 index 00000000000000..7464c5f9956574 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-emo_mobilebert_lordtt13_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English emo_mobilebert_lordtt13 BertForSequenceClassification from lordtt13 +author: John Snow Labs +name: emo_mobilebert_lordtt13 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emo_mobilebert_lordtt13` is a English model originally trained by lordtt13. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emo_mobilebert_lordtt13_en_5.4.2_3.0_1725204822473.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emo_mobilebert_lordtt13_en_5.4.2_3.0_1725204822473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("emo_mobilebert_lordtt13","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("emo_mobilebert_lordtt13", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|emo_mobilebert_lordtt13| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|79.4 MB| + +## References + +https://huggingface.co/lordtt13/emo-mobilebert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-emo_mobilebert_lordtt13_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-emo_mobilebert_lordtt13_pipeline_en.md new file mode 100644 index 00000000000000..6b601da9d91677 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-emo_mobilebert_lordtt13_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English emo_mobilebert_lordtt13_pipeline pipeline BertForSequenceClassification from lordtt13 +author: John Snow Labs +name: emo_mobilebert_lordtt13_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emo_mobilebert_lordtt13_pipeline` is a English model originally trained by lordtt13. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emo_mobilebert_lordtt13_pipeline_en_5.4.2_3.0_1725204826493.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emo_mobilebert_lordtt13_pipeline_en_5.4.2_3.0_1725204826493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("emo_mobilebert_lordtt13_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("emo_mobilebert_lordtt13_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|emo_mobilebert_lordtt13_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|79.5 MB| + +## References + +https://huggingface.co/lordtt13/emo-mobilebert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-english_multinerd_masked_ner_more_training_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-english_multinerd_masked_ner_more_training_pipeline_en.md new file mode 100644 index 00000000000000..cf7b2f7a37ea52 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-english_multinerd_masked_ner_more_training_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English english_multinerd_masked_ner_more_training_pipeline pipeline DistilBertForTokenClassification from pariakashani +author: John Snow Labs +name: english_multinerd_masked_ner_more_training_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_multinerd_masked_ner_more_training_pipeline` is a English model originally trained by pariakashani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_multinerd_masked_ner_more_training_pipeline_en_5.4.2_3.0_1725170902141.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_multinerd_masked_ner_more_training_pipeline_en_5.4.2_3.0_1725170902141.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("english_multinerd_masked_ner_more_training_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("english_multinerd_masked_ner_more_training_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|english_multinerd_masked_ner_more_training_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/pariakashani/en-multinerd-masked-ner-more-training + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-english_multinerd_ner_upsampled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-english_multinerd_ner_upsampled_pipeline_en.md new file mode 100644 index 00000000000000..d43c551d523092 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-english_multinerd_ner_upsampled_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English english_multinerd_ner_upsampled_pipeline pipeline DistilBertForTokenClassification from pariakashani +author: John Snow Labs +name: english_multinerd_ner_upsampled_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_multinerd_ner_upsampled_pipeline` is a English model originally trained by pariakashani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_multinerd_ner_upsampled_pipeline_en_5.4.2_3.0_1725172421805.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_multinerd_ner_upsampled_pipeline_en_5.4.2_3.0_1725172421805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("english_multinerd_ner_upsampled_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("english_multinerd_ner_upsampled_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|english_multinerd_ner_upsampled_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/pariakashani/en-multinerd-ner-upsampled + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-esg_classification_distilbert_roberta_v4_en.md b/docs/_posts/ahmedlone127/2024-09-01-esg_classification_distilbert_roberta_v4_en.md new file mode 100644 index 00000000000000..5cdcb844ff6499 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-esg_classification_distilbert_roberta_v4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English esg_classification_distilbert_roberta_v4 RoBertaForSequenceClassification from dsmsb +author: John Snow Labs +name: esg_classification_distilbert_roberta_v4 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esg_classification_distilbert_roberta_v4` is a English model originally trained by dsmsb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esg_classification_distilbert_roberta_v4_en_5.5.0_3.0_1725212011016.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esg_classification_distilbert_roberta_v4_en_5.5.0_3.0_1725212011016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("esg_classification_distilbert_roberta_v4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("esg_classification_distilbert_roberta_v4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esg_classification_distilbert_roberta_v4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|449.2 MB| + +## References + +https://huggingface.co/dsmsb/esg-classification_distilbert-roberta_v4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-esg_classification_distilbert_roberta_v4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-esg_classification_distilbert_roberta_v4_pipeline_en.md new file mode 100644 index 00000000000000..b56e74991b3f96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-esg_classification_distilbert_roberta_v4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English esg_classification_distilbert_roberta_v4_pipeline pipeline RoBertaForSequenceClassification from dsmsb +author: John Snow Labs +name: esg_classification_distilbert_roberta_v4_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esg_classification_distilbert_roberta_v4_pipeline` is a English model originally trained by dsmsb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esg_classification_distilbert_roberta_v4_pipeline_en_5.5.0_3.0_1725212038295.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esg_classification_distilbert_roberta_v4_pipeline_en_5.5.0_3.0_1725212038295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("esg_classification_distilbert_roberta_v4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("esg_classification_distilbert_roberta_v4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esg_classification_distilbert_roberta_v4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|449.2 MB| + +## References + +https://huggingface.co/dsmsb/esg-classification_distilbert-roberta_v4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ethicaleye_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-01-ethicaleye_pipeline_xx.md new file mode 100644 index 00000000000000..e7043d37fecce9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ethicaleye_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual ethicaleye_pipeline pipeline XlmRoBertaForSequenceClassification from autopilot-ai +author: John Snow Labs +name: ethicaleye_pipeline +date: 2024-09-01 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ethicaleye_pipeline` is a Multilingual model originally trained by autopilot-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ethicaleye_pipeline_xx_5.4.2_3.0_1725190819703.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ethicaleye_pipeline_xx_5.4.2_3.0_1725190819703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ethicaleye_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ethicaleye_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ethicaleye_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|809.4 MB| + +## References + +https://huggingface.co/autopilot-ai/EthicalEye + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ewe_baseline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ewe_baseline_en.md new file mode 100644 index 00000000000000..9bffcc42b3f65f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ewe_baseline_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ewe_baseline DistilBertForTokenClassification from radioapple +author: John Snow Labs +name: ewe_baseline +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ewe_baseline` is a English model originally trained by radioapple. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ewe_baseline_en_5.4.2_3.0_1725172591824.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ewe_baseline_en_5.4.2_3.0_1725172591824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("ewe_baseline","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("ewe_baseline", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ewe_baseline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|250.3 MB| + +## References + +https://huggingface.co/radioapple/EE_baseline \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ewe_baseline_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ewe_baseline_pipeline_en.md new file mode 100644 index 00000000000000..d7452a67508a86 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ewe_baseline_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ewe_baseline_pipeline pipeline DistilBertForTokenClassification from radioapple +author: John Snow Labs +name: ewe_baseline_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ewe_baseline_pipeline` is a English model originally trained by radioapple. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ewe_baseline_pipeline_en_5.4.2_3.0_1725172605389.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ewe_baseline_pipeline_en_5.4.2_3.0_1725172605389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ewe_baseline_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ewe_baseline_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ewe_baseline_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|250.4 MB| + +## References + +https://huggingface.co/radioapple/EE_baseline + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-exigent_moreepoch_bge_base_financial_matryoshka_en.md b/docs/_posts/ahmedlone127/2024-09-01-exigent_moreepoch_bge_base_financial_matryoshka_en.md new file mode 100644 index 00000000000000..32cc11b490c0d3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-exigent_moreepoch_bge_base_financial_matryoshka_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English exigent_moreepoch_bge_base_financial_matryoshka BGEEmbeddings from RishuD7 +author: John Snow Labs +name: exigent_moreepoch_bge_base_financial_matryoshka +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exigent_moreepoch_bge_base_financial_matryoshka` is a English model originally trained by RishuD7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exigent_moreepoch_bge_base_financial_matryoshka_en_5.4.2_3.0_1725198986750.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exigent_moreepoch_bge_base_financial_matryoshka_en_5.4.2_3.0_1725198986750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("exigent_moreepoch_bge_base_financial_matryoshka","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("exigent_moreepoch_bge_base_financial_matryoshka","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|exigent_moreepoch_bge_base_financial_matryoshka| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|389.0 MB| + +## References + +https://huggingface.co/RishuD7/exigent-moreepoch-bge-base-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-exigent_moreepoch_bge_base_financial_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-exigent_moreepoch_bge_base_financial_matryoshka_pipeline_en.md new file mode 100644 index 00000000000000..58232899ca82e5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-exigent_moreepoch_bge_base_financial_matryoshka_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English exigent_moreepoch_bge_base_financial_matryoshka_pipeline pipeline BGEEmbeddings from RishuD7 +author: John Snow Labs +name: exigent_moreepoch_bge_base_financial_matryoshka_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exigent_moreepoch_bge_base_financial_matryoshka_pipeline` is a English model originally trained by RishuD7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exigent_moreepoch_bge_base_financial_matryoshka_pipeline_en_5.4.2_3.0_1725199014671.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exigent_moreepoch_bge_base_financial_matryoshka_pipeline_en_5.4.2_3.0_1725199014671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("exigent_moreepoch_bge_base_financial_matryoshka_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("exigent_moreepoch_bge_base_financial_matryoshka_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|exigent_moreepoch_bge_base_financial_matryoshka_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|389.0 MB| + +## References + +https://huggingface.co/RishuD7/exigent-moreepoch-bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-expe_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-expe_1_pipeline_en.md new file mode 100644 index 00000000000000..2c16a1666495e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-expe_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English expe_1_pipeline pipeline RoBertaForSequenceClassification from BaronSch +author: John Snow Labs +name: expe_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`expe_1_pipeline` is a English model originally trained by BaronSch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/expe_1_pipeline_en_5.5.0_3.0_1725212382275.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/expe_1_pipeline_en_5.5.0_3.0_1725212382275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("expe_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("expe_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|expe_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.5 MB| + +## References + +https://huggingface.co/BaronSch/Expe_1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-fact_oriya_opinion_xlmr_greek_modern_en.md b/docs/_posts/ahmedlone127/2024-09-01-fact_oriya_opinion_xlmr_greek_modern_en.md new file mode 100644 index 00000000000000..37a6a29bde51a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-fact_oriya_opinion_xlmr_greek_modern_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English fact_oriya_opinion_xlmr_greek_modern XlmRoBertaForSequenceClassification from lighteternal +author: John Snow Labs +name: fact_oriya_opinion_xlmr_greek_modern +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fact_oriya_opinion_xlmr_greek_modern` is a English model originally trained by lighteternal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fact_oriya_opinion_xlmr_greek_modern_en_5.4.2_3.0_1725189942120.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fact_oriya_opinion_xlmr_greek_modern_en_5.4.2_3.0_1725189942120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("fact_oriya_opinion_xlmr_greek_modern","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("fact_oriya_opinion_xlmr_greek_modern", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fact_oriya_opinion_xlmr_greek_modern| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|859.4 MB| + +## References + +https://huggingface.co/lighteternal/fact-or-opinion-xlmr-el \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-fact_oriya_opinion_xlmr_greek_modern_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-fact_oriya_opinion_xlmr_greek_modern_pipeline_en.md new file mode 100644 index 00000000000000..aa39c5eb3fad78 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-fact_oriya_opinion_xlmr_greek_modern_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fact_oriya_opinion_xlmr_greek_modern_pipeline pipeline XlmRoBertaForSequenceClassification from lighteternal +author: John Snow Labs +name: fact_oriya_opinion_xlmr_greek_modern_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fact_oriya_opinion_xlmr_greek_modern_pipeline` is a English model originally trained by lighteternal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fact_oriya_opinion_xlmr_greek_modern_pipeline_en_5.4.2_3.0_1725190010297.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fact_oriya_opinion_xlmr_greek_modern_pipeline_en_5.4.2_3.0_1725190010297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fact_oriya_opinion_xlmr_greek_modern_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fact_oriya_opinion_xlmr_greek_modern_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fact_oriya_opinion_xlmr_greek_modern_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|859.4 MB| + +## References + +https://huggingface.co/lighteternal/fact-or-opinion-xlmr-el + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-feelings_text_classifier_eng_en.md b/docs/_posts/ahmedlone127/2024-09-01-feelings_text_classifier_eng_en.md new file mode 100644 index 00000000000000..c48031b5efbda1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-feelings_text_classifier_eng_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English feelings_text_classifier_eng DistilBertForSequenceClassification from LukeGPT88 +author: John Snow Labs +name: feelings_text_classifier_eng +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`feelings_text_classifier_eng` is a English model originally trained by LukeGPT88. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/feelings_text_classifier_eng_en_5.5.0_3.0_1725214144571.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/feelings_text_classifier_eng_en_5.5.0_3.0_1725214144571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("feelings_text_classifier_eng","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("feelings_text_classifier_eng", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|feelings_text_classifier_eng| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/LukeGPT88/feelings-text-classifier-eng \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-feelings_text_classifier_eng_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-feelings_text_classifier_eng_pipeline_en.md new file mode 100644 index 00000000000000..048617d281e5a3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-feelings_text_classifier_eng_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English feelings_text_classifier_eng_pipeline pipeline DistilBertForSequenceClassification from LukeGPT88 +author: John Snow Labs +name: feelings_text_classifier_eng_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`feelings_text_classifier_eng_pipeline` is a English model originally trained by LukeGPT88. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/feelings_text_classifier_eng_pipeline_en_5.5.0_3.0_1725214158185.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/feelings_text_classifier_eng_pipeline_en_5.5.0_3.0_1725214158185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("feelings_text_classifier_eng_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("feelings_text_classifier_eng_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|feelings_text_classifier_eng_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/LukeGPT88/feelings-text-classifier-eng + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-fine_tune_embedding_bge_base_hrpolicy_vfinal_en.md b/docs/_posts/ahmedlone127/2024-09-01-fine_tune_embedding_bge_base_hrpolicy_vfinal_en.md new file mode 100644 index 00000000000000..24f78285de0015 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-fine_tune_embedding_bge_base_hrpolicy_vfinal_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English fine_tune_embedding_bge_base_hrpolicy_vfinal BGEEmbeddings from kr-manish +author: John Snow Labs +name: fine_tune_embedding_bge_base_hrpolicy_vfinal +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tune_embedding_bge_base_hrpolicy_vfinal` is a English model originally trained by kr-manish. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tune_embedding_bge_base_hrpolicy_vfinal_en_5.5.0_3.0_1725229052816.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tune_embedding_bge_base_hrpolicy_vfinal_en_5.5.0_3.0_1725229052816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("fine_tune_embedding_bge_base_hrpolicy_vfinal","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("fine_tune_embedding_bge_base_hrpolicy_vfinal","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tune_embedding_bge_base_hrpolicy_vfinal| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|256.0 MB| + +## References + +https://huggingface.co/kr-manish/fine-tune-embedding-bge-base-HrPolicy_vfinal \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-fine_tune_embedding_bge_base_hrpolicy_vfinal_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-fine_tune_embedding_bge_base_hrpolicy_vfinal_pipeline_en.md new file mode 100644 index 00000000000000..c11f6cfc9e3d7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-fine_tune_embedding_bge_base_hrpolicy_vfinal_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tune_embedding_bge_base_hrpolicy_vfinal_pipeline pipeline BGEEmbeddings from kr-manish +author: John Snow Labs +name: fine_tune_embedding_bge_base_hrpolicy_vfinal_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tune_embedding_bge_base_hrpolicy_vfinal_pipeline` is a English model originally trained by kr-manish. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tune_embedding_bge_base_hrpolicy_vfinal_pipeline_en_5.5.0_3.0_1725229132660.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tune_embedding_bge_base_hrpolicy_vfinal_pipeline_en_5.5.0_3.0_1725229132660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tune_embedding_bge_base_hrpolicy_vfinal_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tune_embedding_bge_base_hrpolicy_vfinal_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tune_embedding_bge_base_hrpolicy_vfinal_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|256.0 MB| + +## References + +https://huggingface.co/kr-manish/fine-tune-embedding-bge-base-HrPolicy_vfinal + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_bert_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_bert_base_en.md new file mode 100644 index 00000000000000..5e506e7239f386 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_bert_base_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fine_tuned_bert_base BertForQuestionAnswering from kiwakwok +author: John Snow Labs +name: fine_tuned_bert_base +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bert_base` is a English model originally trained by kiwakwok. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_base_en_5.5.0_3.0_1725215270822.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_base_en_5.5.0_3.0_1725215270822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("fine_tuned_bert_base","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("fine_tuned_bert_base", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_bert_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|382.4 MB| + +## References + +https://huggingface.co/kiwakwok/fine-tuned-bert-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_bert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_bert_base_pipeline_en.md new file mode 100644 index 00000000000000..443c8444e6184b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_bert_base_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tuned_bert_base_pipeline pipeline BertForQuestionAnswering from kiwakwok +author: John Snow Labs +name: fine_tuned_bert_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bert_base_pipeline` is a English model originally trained by kiwakwok. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_base_pipeline_en_5.5.0_3.0_1725215291787.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_base_pipeline_en_5.5.0_3.0_1725215291787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_bert_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_bert_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_bert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|382.4 MB| + +## References + +https://huggingface.co/kiwakwok/fine-tuned-bert-base + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_deberta_question_answering_ptsinfotech_en.md b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_deberta_question_answering_ptsinfotech_en.md new file mode 100644 index 00000000000000..23928968420bda --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_deberta_question_answering_ptsinfotech_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fine_tuned_deberta_question_answering_ptsinfotech DeBertaForQuestionAnswering from ptsinfotech +author: John Snow Labs +name: fine_tuned_deberta_question_answering_ptsinfotech +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_deberta_question_answering_ptsinfotech` is a English model originally trained by ptsinfotech. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_question_answering_ptsinfotech_en_5.5.0_3.0_1725219143028.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_question_answering_ptsinfotech_en_5.5.0_3.0_1725219143028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("fine_tuned_deberta_question_answering_ptsinfotech","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("fine_tuned_deberta_question_answering_ptsinfotech", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_deberta_question_answering_ptsinfotech| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|651.0 MB| + +## References + +https://huggingface.co/ptsinfotech/fine_tuned_deberta_question_answering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_deberta_question_answering_ptsinfotech_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_deberta_question_answering_ptsinfotech_pipeline_en.md new file mode 100644 index 00000000000000..8e61681316bd45 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_deberta_question_answering_ptsinfotech_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tuned_deberta_question_answering_ptsinfotech_pipeline pipeline DeBertaForQuestionAnswering from ptsinfotech +author: John Snow Labs +name: fine_tuned_deberta_question_answering_ptsinfotech_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_deberta_question_answering_ptsinfotech_pipeline` is a English model originally trained by ptsinfotech. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_question_answering_ptsinfotech_pipeline_en_5.5.0_3.0_1725219189074.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_question_answering_ptsinfotech_pipeline_en_5.5.0_3.0_1725219189074.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_deberta_question_answering_ptsinfotech_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_deberta_question_answering_ptsinfotech_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_deberta_question_answering_ptsinfotech_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|651.1 MB| + +## References + +https://huggingface.co/ptsinfotech/fine_tuned_deberta_question_answering + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_deberta_question_answering_seenuvasanfoss_en.md b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_deberta_question_answering_seenuvasanfoss_en.md new file mode 100644 index 00000000000000..05469fa923896c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_deberta_question_answering_seenuvasanfoss_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fine_tuned_deberta_question_answering_seenuvasanfoss DeBertaForQuestionAnswering from seenuvasanfoss +author: John Snow Labs +name: fine_tuned_deberta_question_answering_seenuvasanfoss +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_deberta_question_answering_seenuvasanfoss` is a English model originally trained by seenuvasanfoss. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_question_answering_seenuvasanfoss_en_5.5.0_3.0_1725220953784.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_question_answering_seenuvasanfoss_en_5.5.0_3.0_1725220953784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("fine_tuned_deberta_question_answering_seenuvasanfoss","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("fine_tuned_deberta_question_answering_seenuvasanfoss", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_deberta_question_answering_seenuvasanfoss| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|651.0 MB| + +## References + +https://huggingface.co/seenuvasanfoss/fine_tuned_deberta_question_answering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_deberta_question_answering_seenuvasanfoss_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_deberta_question_answering_seenuvasanfoss_pipeline_en.md new file mode 100644 index 00000000000000..77a30760daa4bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_deberta_question_answering_seenuvasanfoss_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tuned_deberta_question_answering_seenuvasanfoss_pipeline pipeline DeBertaForQuestionAnswering from seenuvasanfoss +author: John Snow Labs +name: fine_tuned_deberta_question_answering_seenuvasanfoss_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_deberta_question_answering_seenuvasanfoss_pipeline` is a English model originally trained by seenuvasanfoss. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_question_answering_seenuvasanfoss_pipeline_en_5.5.0_3.0_1725221004798.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_question_answering_seenuvasanfoss_pipeline_en_5.5.0_3.0_1725221004798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_deberta_question_answering_seenuvasanfoss_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_deberta_question_answering_seenuvasanfoss_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_deberta_question_answering_seenuvasanfoss_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|651.1 MB| + +## References + +https://huggingface.co/seenuvasanfoss/fine_tuned_deberta_question_answering + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_viquad_hgf_en.md b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_viquad_hgf_en.md new file mode 100644 index 00000000000000..3518c02c10e197 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_viquad_hgf_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fine_tuned_viquad_hgf XlmRoBertaForQuestionAnswering from longhoang06 +author: John Snow Labs +name: fine_tuned_viquad_hgf +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_viquad_hgf` is a English model originally trained by longhoang06. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_viquad_hgf_en_5.5.0_3.0_1725235131587.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_viquad_hgf_en_5.5.0_3.0_1725235131587.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("fine_tuned_viquad_hgf","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("fine_tuned_viquad_hgf", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_viquad_hgf| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|881.2 MB| + +## References + +https://huggingface.co/longhoang06/fine-tuned-viquad-hgf \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_viquad_hgf_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_viquad_hgf_pipeline_en.md new file mode 100644 index 00000000000000..1f379941bed77d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-fine_tuned_viquad_hgf_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tuned_viquad_hgf_pipeline pipeline XlmRoBertaForQuestionAnswering from longhoang06 +author: John Snow Labs +name: fine_tuned_viquad_hgf_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_viquad_hgf_pipeline` is a English model originally trained by longhoang06. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_viquad_hgf_pipeline_en_5.5.0_3.0_1725235196072.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_viquad_hgf_pipeline_en_5.5.0_3.0_1725235196072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_viquad_hgf_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_viquad_hgf_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_viquad_hgf_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|881.2 MB| + +## References + +https://huggingface.co/longhoang06/fine-tuned-viquad-hgf + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_base_en.md new file mode 100644 index 00000000000000..588df2b885dbb8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_base_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English finetuned_bge_embeddings_v3_base BGEEmbeddings from austinpatrickm +author: John Snow Labs +name: finetuned_bge_embeddings_v3_base +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_embeddings_v3_base` is a English model originally trained by austinpatrickm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v3_base_en_5.4.2_3.0_1725199525871.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v3_base_en_5.4.2_3.0_1725199525871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("finetuned_bge_embeddings_v3_base","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("finetuned_bge_embeddings_v3_base","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bge_embeddings_v3_base| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.6 MB| + +## References + +https://huggingface.co/austinpatrickm/finetuned_bge_embeddings_v3_base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_base_pipeline_en.md new file mode 100644 index 00000000000000..54ab0825a08ad6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_base_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English finetuned_bge_embeddings_v3_base_pipeline pipeline BGEEmbeddings from austinpatrickm +author: John Snow Labs +name: finetuned_bge_embeddings_v3_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_embeddings_v3_base_pipeline` is a English model originally trained by austinpatrickm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v3_base_pipeline_en_5.4.2_3.0_1725199553563.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v3_base_pipeline_en_5.4.2_3.0_1725199553563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_bge_embeddings_v3_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_bge_embeddings_v3_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bge_embeddings_v3_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.7 MB| + +## References + +https://huggingface.co/austinpatrickm/finetuned_bge_embeddings_v3_base + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_base_v1_5_en.md b/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_base_v1_5_en.md new file mode 100644 index 00000000000000..7f2ac498fd551f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_base_v1_5_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English finetuned_bge_embeddings_v3_base_v1_5 BGEEmbeddings from austinpatrickm +author: John Snow Labs +name: finetuned_bge_embeddings_v3_base_v1_5 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_embeddings_v3_base_v1_5` is a English model originally trained by austinpatrickm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v3_base_v1_5_en_5.5.0_3.0_1725229478539.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v3_base_v1_5_en_5.5.0_3.0_1725229478539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("finetuned_bge_embeddings_v3_base_v1_5","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("finetuned_bge_embeddings_v3_base_v1_5","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bge_embeddings_v3_base_v1_5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/austinpatrickm/finetuned_bge_embeddings_v3_base_v1.5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_llm_embedder_en.md b/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_llm_embedder_en.md new file mode 100644 index 00000000000000..e70eaae3479be0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_llm_embedder_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English finetuned_bge_embeddings_v3_llm_embedder BGEEmbeddings from austinpatrickm +author: John Snow Labs +name: finetuned_bge_embeddings_v3_llm_embedder +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_embeddings_v3_llm_embedder` is a English model originally trained by austinpatrickm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v3_llm_embedder_en_5.4.2_3.0_1725198473427.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v3_llm_embedder_en_5.4.2_3.0_1725198473427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("finetuned_bge_embeddings_v3_llm_embedder","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("finetuned_bge_embeddings_v3_llm_embedder","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bge_embeddings_v3_llm_embedder| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.2 MB| + +## References + +https://huggingface.co/austinpatrickm/finetuned_bge_embeddings_v3_LLM-embedder \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_llm_embedder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_llm_embedder_pipeline_en.md new file mode 100644 index 00000000000000..5172ca04cc19d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_llm_embedder_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English finetuned_bge_embeddings_v3_llm_embedder_pipeline pipeline BGEEmbeddings from austinpatrickm +author: John Snow Labs +name: finetuned_bge_embeddings_v3_llm_embedder_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_embeddings_v3_llm_embedder_pipeline` is a English model originally trained by austinpatrickm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v3_llm_embedder_pipeline_en_5.4.2_3.0_1725198509633.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v3_llm_embedder_pipeline_en_5.4.2_3.0_1725198509633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_bge_embeddings_v3_llm_embedder_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_bge_embeddings_v3_llm_embedder_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bge_embeddings_v3_llm_embedder_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.2 MB| + +## References + +https://huggingface.co/austinpatrickm/finetuned_bge_embeddings_v3_LLM-embedder + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-finetuned_sentiment_model_45000_training_examples_en.md b/docs/_posts/ahmedlone127/2024-09-01-finetuned_sentiment_model_45000_training_examples_en.md new file mode 100644 index 00000000000000..0d943ac5e203c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-finetuned_sentiment_model_45000_training_examples_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_sentiment_model_45000_training_examples DistilBertForSequenceClassification from chescore +author: John Snow Labs +name: finetuned_sentiment_model_45000_training_examples +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sentiment_model_45000_training_examples` is a English model originally trained by chescore. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_model_45000_training_examples_en_5.5.0_3.0_1725213520638.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_model_45000_training_examples_en_5.5.0_3.0_1725213520638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuned_sentiment_model_45000_training_examples","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuned_sentiment_model_45000_training_examples", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_sentiment_model_45000_training_examples| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/chescore/finetuned-sentiment-model-45000-training-examples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-finetuned_sentiment_model_45000_training_examples_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-finetuned_sentiment_model_45000_training_examples_pipeline_en.md new file mode 100644 index 00000000000000..f25f6b8e9a9dab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-finetuned_sentiment_model_45000_training_examples_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_sentiment_model_45000_training_examples_pipeline pipeline DistilBertForSequenceClassification from chescore +author: John Snow Labs +name: finetuned_sentiment_model_45000_training_examples_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sentiment_model_45000_training_examples_pipeline` is a English model originally trained by chescore. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_model_45000_training_examples_pipeline_en_5.5.0_3.0_1725213537697.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_model_45000_training_examples_pipeline_en_5.5.0_3.0_1725213537697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_sentiment_model_45000_training_examples_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_sentiment_model_45000_training_examples_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_sentiment_model_45000_training_examples_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/chescore/finetuned-sentiment-model-45000-training-examples + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-frabert_distilbert_base_uncased_complete_en.md b/docs/_posts/ahmedlone127/2024-09-01-frabert_distilbert_base_uncased_complete_en.md new file mode 100644 index 00000000000000..53c5e220532971 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-frabert_distilbert_base_uncased_complete_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English frabert_distilbert_base_uncased_complete DistilBertForSequenceClassification from Francesco0101 +author: John Snow Labs +name: frabert_distilbert_base_uncased_complete +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frabert_distilbert_base_uncased_complete` is a English model originally trained by Francesco0101. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/frabert_distilbert_base_uncased_complete_en_5.5.0_3.0_1725213622296.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frabert_distilbert_base_uncased_complete_en_5.5.0_3.0_1725213622296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("frabert_distilbert_base_uncased_complete","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("frabert_distilbert_base_uncased_complete", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|frabert_distilbert_base_uncased_complete| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Francesco0101/FRABERT-distilbert-base-uncased-COMPLETE \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-frabert_distilbert_base_uncased_complete_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-frabert_distilbert_base_uncased_complete_pipeline_en.md new file mode 100644 index 00000000000000..14466b2cc4774a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-frabert_distilbert_base_uncased_complete_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English frabert_distilbert_base_uncased_complete_pipeline pipeline DistilBertForSequenceClassification from Francesco0101 +author: John Snow Labs +name: frabert_distilbert_base_uncased_complete_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frabert_distilbert_base_uncased_complete_pipeline` is a English model originally trained by Francesco0101. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/frabert_distilbert_base_uncased_complete_pipeline_en_5.5.0_3.0_1725213635796.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frabert_distilbert_base_uncased_complete_pipeline_en_5.5.0_3.0_1725213635796.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("frabert_distilbert_base_uncased_complete_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("frabert_distilbert_base_uncased_complete_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|frabert_distilbert_base_uncased_complete_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Francesco0101/FRABERT-distilbert-base-uncased-COMPLETE + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ft_distilbert_base_uncased_with_wnut17_v_0_en.md b/docs/_posts/ahmedlone127/2024-09-01-ft_distilbert_base_uncased_with_wnut17_v_0_en.md new file mode 100644 index 00000000000000..15e9b89066c7a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ft_distilbert_base_uncased_with_wnut17_v_0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ft_distilbert_base_uncased_with_wnut17_v_0 DistilBertForTokenClassification from aisuko +author: John Snow Labs +name: ft_distilbert_base_uncased_with_wnut17_v_0 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_distilbert_base_uncased_with_wnut17_v_0` is a English model originally trained by aisuko. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_distilbert_base_uncased_with_wnut17_v_0_en_5.4.2_3.0_1725172581835.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_distilbert_base_uncased_with_wnut17_v_0_en_5.4.2_3.0_1725172581835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("ft_distilbert_base_uncased_with_wnut17_v_0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("ft_distilbert_base_uncased_with_wnut17_v_0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ft_distilbert_base_uncased_with_wnut17_v_0| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/aisuko/ft-distilbert-base-uncased-with-wnut17-v-0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ft_distilbert_base_uncased_with_wnut17_v_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ft_distilbert_base_uncased_with_wnut17_v_0_pipeline_en.md new file mode 100644 index 00000000000000..cbccc48d5727da --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ft_distilbert_base_uncased_with_wnut17_v_0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ft_distilbert_base_uncased_with_wnut17_v_0_pipeline pipeline DistilBertForTokenClassification from aisuko +author: John Snow Labs +name: ft_distilbert_base_uncased_with_wnut17_v_0_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_distilbert_base_uncased_with_wnut17_v_0_pipeline` is a English model originally trained by aisuko. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_distilbert_base_uncased_with_wnut17_v_0_pipeline_en_5.4.2_3.0_1725172596126.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_distilbert_base_uncased_with_wnut17_v_0_pipeline_en_5.4.2_3.0_1725172596126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ft_distilbert_base_uncased_with_wnut17_v_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ft_distilbert_base_uncased_with_wnut17_v_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ft_distilbert_base_uncased_with_wnut17_v_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/aisuko/ft-distilbert-base-uncased-with-wnut17-v-0 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ft_robert_en.md b/docs/_posts/ahmedlone127/2024-09-01-ft_robert_en.md new file mode 100644 index 00000000000000..5c50c4b4dcc24c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ft_robert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ft_robert RoBertaForSequenceClassification from aibreaker +author: John Snow Labs +name: ft_robert +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_robert` is a English model originally trained by aibreaker. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_robert_en_5.4.2_3.0_1725194925256.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_robert_en_5.4.2_3.0_1725194925256.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("ft_robert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("ft_robert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ft_robert| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/aibreaker/ft_robert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ft_robert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ft_robert_pipeline_en.md new file mode 100644 index 00000000000000..60ee5cbca5b330 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ft_robert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ft_robert_pipeline pipeline RoBertaForSequenceClassification from aibreaker +author: John Snow Labs +name: ft_robert_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_robert_pipeline` is a English model originally trained by aibreaker. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_robert_pipeline_en_5.4.2_3.0_1725195017814.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_robert_pipeline_en_5.4.2_3.0_1725195017814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ft_robert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ft_robert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ft_robert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/aibreaker/ft_robert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-gbert_large_zeroshot_nli_de.md b/docs/_posts/ahmedlone127/2024-09-01-gbert_large_zeroshot_nli_de.md new file mode 100644 index 00000000000000..bad76098246430 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-gbert_large_zeroshot_nli_de.md @@ -0,0 +1,94 @@ +--- +layout: model +title: German gbert_large_zeroshot_nli BertForZeroShotClassification from svalabs +author: John Snow Labs +name: gbert_large_zeroshot_nli +date: 2024-09-01 +tags: [de, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: de +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_large_zeroshot_nli` is a German model originally trained by svalabs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gbert_large_zeroshot_nli_de_5.4.2_3.0_1725208183733.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_large_zeroshot_nli_de_5.4.2_3.0_1725208183733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("gbert_large_zeroshot_nli","de") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("gbert_large_zeroshot_nli", "de") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gbert_large_zeroshot_nli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|1.3 GB| + +## References + +https://huggingface.co/svalabs/gbert-large-zeroshot-nli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-gbert_large_zeroshot_nli_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-01-gbert_large_zeroshot_nli_pipeline_de.md new file mode 100644 index 00000000000000..20ab14352fa56b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-gbert_large_zeroshot_nli_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German gbert_large_zeroshot_nli_pipeline pipeline BertForZeroShotClassification from svalabs +author: John Snow Labs +name: gbert_large_zeroshot_nli_pipeline +date: 2024-09-01 +tags: [de, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: de +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_large_zeroshot_nli_pipeline` is a German model originally trained by svalabs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gbert_large_zeroshot_nli_pipeline_de_5.4.2_3.0_1725208249403.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_large_zeroshot_nli_pipeline_de_5.4.2_3.0_1725208249403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gbert_large_zeroshot_nli_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gbert_large_zeroshot_nli_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gbert_large_zeroshot_nli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|1.3 GB| + +## References + +https://huggingface.co/svalabs/gbert-large-zeroshot-nli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-gender_classification_amanaccessassist_en.md b/docs/_posts/ahmedlone127/2024-09-01-gender_classification_amanaccessassist_en.md new file mode 100644 index 00000000000000..13beb6b5312d2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-gender_classification_amanaccessassist_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English gender_classification_amanaccessassist RoBertaForSequenceClassification from Amanaccessassist +author: John Snow Labs +name: gender_classification_amanaccessassist +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gender_classification_amanaccessassist` is a English model originally trained by Amanaccessassist. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gender_classification_amanaccessassist_en_5.5.0_3.0_1725212350039.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gender_classification_amanaccessassist_en_5.5.0_3.0_1725212350039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("gender_classification_amanaccessassist","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("gender_classification_amanaccessassist", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gender_classification_amanaccessassist| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|431.7 MB| + +## References + +https://huggingface.co/Amanaccessassist/Gender-Classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-gender_classification_amanaccessassist_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-gender_classification_amanaccessassist_pipeline_en.md new file mode 100644 index 00000000000000..a23060cee66278 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-gender_classification_amanaccessassist_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English gender_classification_amanaccessassist_pipeline pipeline RoBertaForSequenceClassification from Amanaccessassist +author: John Snow Labs +name: gender_classification_amanaccessassist_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gender_classification_amanaccessassist_pipeline` is a English model originally trained by Amanaccessassist. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gender_classification_amanaccessassist_pipeline_en_5.5.0_3.0_1725212378068.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gender_classification_amanaccessassist_pipeline_en_5.5.0_3.0_1725212378068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gender_classification_amanaccessassist_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gender_classification_amanaccessassist_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gender_classification_amanaccessassist_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|431.7 MB| + +## References + +https://huggingface.co/Amanaccessassist/Gender-Classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-genesis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-genesis_pipeline_en.md new file mode 100644 index 00000000000000..a7a2b222394c04 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-genesis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English genesis_pipeline pipeline DistilBertForTokenClassification from Raj-sharma01 +author: John Snow Labs +name: genesis_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`genesis_pipeline` is a English model originally trained by Raj-sharma01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/genesis_pipeline_en_5.4.2_3.0_1725160948557.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/genesis_pipeline_en_5.4.2_3.0_1725160948557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("genesis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("genesis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|genesis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.4 MB| + +## References + +https://huggingface.co/Raj-sharma01/Genesis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-german_zeroshot_de.md b/docs/_posts/ahmedlone127/2024-09-01-german_zeroshot_de.md new file mode 100644 index 00000000000000..d859bf939c0204 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-german_zeroshot_de.md @@ -0,0 +1,94 @@ +--- +layout: model +title: German german_zeroshot BertForZeroShotClassification from Sahajtomar +author: John Snow Labs +name: german_zeroshot +date: 2024-09-01 +tags: [de, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: de +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`german_zeroshot` is a German model originally trained by Sahajtomar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/german_zeroshot_de_5.4.2_3.0_1725202292533.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/german_zeroshot_de_5.4.2_3.0_1725202292533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("german_zeroshot","de") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("german_zeroshot", "de") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|german_zeroshot| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Sahajtomar/German_Zeroshot \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-german_zeroshot_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-01-german_zeroshot_pipeline_de.md new file mode 100644 index 00000000000000..413858268a8585 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-german_zeroshot_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German german_zeroshot_pipeline pipeline BertForZeroShotClassification from Sahajtomar +author: John Snow Labs +name: german_zeroshot_pipeline +date: 2024-09-01 +tags: [de, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: de +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`german_zeroshot_pipeline` is a German model originally trained by Sahajtomar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/german_zeroshot_pipeline_de_5.4.2_3.0_1725202360533.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/german_zeroshot_pipeline_de_5.4.2_3.0_1725202360533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("german_zeroshot_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("german_zeroshot_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|german_zeroshot_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Sahajtomar/German_Zeroshot + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-gqa_roberta_legal_squad_complete_augmented_2000_en.md b/docs/_posts/ahmedlone127/2024-09-01-gqa_roberta_legal_squad_complete_augmented_2000_en.md new file mode 100644 index 00000000000000..436523321fb45c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-gqa_roberta_legal_squad_complete_augmented_2000_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English gqa_roberta_legal_squad_complete_augmented_2000 RoBertaForQuestionAnswering from farid1088 +author: John Snow Labs +name: gqa_roberta_legal_squad_complete_augmented_2000 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gqa_roberta_legal_squad_complete_augmented_2000` is a English model originally trained by farid1088. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gqa_roberta_legal_squad_complete_augmented_2000_en_5.4.2_3.0_1725200162171.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gqa_roberta_legal_squad_complete_augmented_2000_en_5.4.2_3.0_1725200162171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("gqa_roberta_legal_squad_complete_augmented_2000","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("gqa_roberta_legal_squad_complete_augmented_2000", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gqa_roberta_legal_squad_complete_augmented_2000| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|465.8 MB| + +## References + +https://huggingface.co/farid1088/GQA_RoBERTa_legal_SQuAD_complete_augmented_2000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-gqa_roberta_legal_squad_complete_augmented_2000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-gqa_roberta_legal_squad_complete_augmented_2000_pipeline_en.md new file mode 100644 index 00000000000000..9b98ce2bfb742a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-gqa_roberta_legal_squad_complete_augmented_2000_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English gqa_roberta_legal_squad_complete_augmented_2000_pipeline pipeline RoBertaForQuestionAnswering from farid1088 +author: John Snow Labs +name: gqa_roberta_legal_squad_complete_augmented_2000_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gqa_roberta_legal_squad_complete_augmented_2000_pipeline` is a English model originally trained by farid1088. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gqa_roberta_legal_squad_complete_augmented_2000_pipeline_en_5.4.2_3.0_1725200187382.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gqa_roberta_legal_squad_complete_augmented_2000_pipeline_en_5.4.2_3.0_1725200187382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gqa_roberta_legal_squad_complete_augmented_2000_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gqa_roberta_legal_squad_complete_augmented_2000_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gqa_roberta_legal_squad_complete_augmented_2000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.8 MB| + +## References + +https://huggingface.co/farid1088/GQA_RoBERTa_legal_SQuAD_complete_augmented_2000 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-graphcodebert_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-graphcodebert_base_en.md new file mode 100644 index 00000000000000..f3ec5a910c88e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-graphcodebert_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English graphcodebert_base RoBertaEmbeddings from microsoft +author: John Snow Labs +name: graphcodebert_base +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`graphcodebert_base` is a English model originally trained by microsoft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/graphcodebert_base_en_5.4.2_3.0_1725186221971.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/graphcodebert_base_en_5.4.2_3.0_1725186221971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("graphcodebert_base","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("graphcodebert_base","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|graphcodebert_base| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|465.9 MB| + +## References + +https://huggingface.co/microsoft/graphcodebert-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-graphcodebert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-graphcodebert_base_pipeline_en.md new file mode 100644 index 00000000000000..d602fbd606d702 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-graphcodebert_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English graphcodebert_base_pipeline pipeline RoBertaEmbeddings from microsoft +author: John Snow Labs +name: graphcodebert_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`graphcodebert_base_pipeline` is a English model originally trained by microsoft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/graphcodebert_base_pipeline_en_5.4.2_3.0_1725186249615.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/graphcodebert_base_pipeline_en_5.4.2_3.0_1725186249615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("graphcodebert_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("graphcodebert_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|graphcodebert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|466.0 MB| + +## References + +https://huggingface.co/microsoft/graphcodebert-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-gte_large_mnli_anli_en.md b/docs/_posts/ahmedlone127/2024-09-01-gte_large_mnli_anli_en.md new file mode 100644 index 00000000000000..76d0af15bce687 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-gte_large_mnli_anli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English gte_large_mnli_anli BertForZeroShotClassification from mjwong +author: John Snow Labs +name: gte_large_mnli_anli +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gte_large_mnli_anli` is a English model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gte_large_mnli_anli_en_5.4.2_3.0_1725202190136.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gte_large_mnli_anli_en_5.4.2_3.0_1725202190136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("gte_large_mnli_anli","en") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("gte_large_mnli_anli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gte_large_mnli_anli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/mjwong/gte-large-mnli-anli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-gte_large_mnli_anli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-gte_large_mnli_anli_pipeline_en.md new file mode 100644 index 00000000000000..9feb680c30d348 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-gte_large_mnli_anli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English gte_large_mnli_anli_pipeline pipeline BertForZeroShotClassification from mjwong +author: John Snow Labs +name: gte_large_mnli_anli_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gte_large_mnli_anli_pipeline` is a English model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gte_large_mnli_anli_pipeline_en_5.4.2_3.0_1725202260214.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gte_large_mnli_anli_pipeline_en_5.4.2_3.0_1725202260214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gte_large_mnli_anli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gte_large_mnli_anli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gte_large_mnli_anli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/mjwong/gte-large-mnli-anli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-hasoc19_microsoft_mdeberta_v3_base_targinsult1_en.md b/docs/_posts/ahmedlone127/2024-09-01-hasoc19_microsoft_mdeberta_v3_base_targinsult1_en.md new file mode 100644 index 00000000000000..749c353070f477 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-hasoc19_microsoft_mdeberta_v3_base_targinsult1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hasoc19_microsoft_mdeberta_v3_base_targinsult1 DeBertaForSequenceClassification from SiddharthaM +author: John Snow Labs +name: hasoc19_microsoft_mdeberta_v3_base_targinsult1 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hasoc19_microsoft_mdeberta_v3_base_targinsult1` is a English model originally trained by SiddharthaM. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hasoc19_microsoft_mdeberta_v3_base_targinsult1_en_5.4.2_3.0_1725183326576.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hasoc19_microsoft_mdeberta_v3_base_targinsult1_en_5.4.2_3.0_1725183326576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("hasoc19_microsoft_mdeberta_v3_base_targinsult1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("hasoc19_microsoft_mdeberta_v3_base_targinsult1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hasoc19_microsoft_mdeberta_v3_base_targinsult1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|815.2 MB| + +## References + +https://huggingface.co/SiddharthaM/hasoc19-microsoft-mdeberta-v3-base-targinsult1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_en.md b/docs/_posts/ahmedlone127/2024-09-01-hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_en.md new file mode 100644 index 00000000000000..b3ddd372cdc8fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m RoBertaForSequenceClassification from tweettemposhift +author: John Snow Labs +name: hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m` is a English model originally trained by tweettemposhift. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_en_5.5.0_3.0_1725212719906.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_en_5.5.0_3.0_1725212719906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/tweettemposhift/hate-hate_balance_random3_seed0-twitter-roberta-base-2019-90m \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_pipeline_en.md new file mode 100644 index 00000000000000..bd03dea5c9285b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_pipeline pipeline RoBertaForSequenceClassification from tweettemposhift +author: John Snow Labs +name: hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_pipeline` is a English model originally trained by tweettemposhift. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_pipeline_en_5.5.0_3.0_1725212745101.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_pipeline_en_5.5.0_3.0_1725212745101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hate_hate_balance_random3_seed0_twitter_roberta_base_2019_90m_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/tweettemposhift/hate-hate_balance_random3_seed0-twitter-roberta-base-2019-90m + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-hesroberta_hausa_en.md b/docs/_posts/ahmedlone127/2024-09-01-hesroberta_hausa_en.md new file mode 100644 index 00000000000000..d2a5b2176f82cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-hesroberta_hausa_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hesroberta_hausa RoBertaForSequenceClassification from Chettaniiay +author: John Snow Labs +name: hesroberta_hausa +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hesroberta_hausa` is a English model originally trained by Chettaniiay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hesroberta_hausa_en_5.4.2_3.0_1725194003293.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hesroberta_hausa_en_5.4.2_3.0_1725194003293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("hesroberta_hausa","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("hesroberta_hausa", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hesroberta_hausa| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.6 MB| + +## References + +https://huggingface.co/Chettaniiay/HESRoberTA-HA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-hesroberta_hausa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-hesroberta_hausa_pipeline_en.md new file mode 100644 index 00000000000000..02d708aed5a6ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-hesroberta_hausa_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hesroberta_hausa_pipeline pipeline RoBertaForSequenceClassification from Chettaniiay +author: John Snow Labs +name: hesroberta_hausa_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hesroberta_hausa_pipeline` is a English model originally trained by Chettaniiay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hesroberta_hausa_pipeline_en_5.4.2_3.0_1725194035406.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hesroberta_hausa_pipeline_en_5.4.2_3.0_1725194035406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hesroberta_hausa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hesroberta_hausa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hesroberta_hausa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.6 MB| + +## References + +https://huggingface.co/Chettaniiay/HESRoberTA-HA + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-hindi_albert_hi.md b/docs/_posts/ahmedlone127/2024-09-01-hindi_albert_hi.md new file mode 100644 index 00000000000000..e4182f7cd5fa81 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-hindi_albert_hi.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Hindi hindi_albert AlbertEmbeddings from l3cube-pune +author: John Snow Labs +name: hindi_albert +date: 2024-09-01 +tags: [hi, open_source, onnx, embeddings, albert] +task: Embeddings +language: hi +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hindi_albert` is a Hindi model originally trained by l3cube-pune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hindi_albert_hi_5.4.2_3.0_1725206201987.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hindi_albert_hi_5.4.2_3.0_1725206201987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = AlbertEmbeddings.pretrained("hindi_albert","hi") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = AlbertEmbeddings.pretrained("hindi_albert","hi") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hindi_albert| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[albert]| +|Language:|hi| +|Size:|125.4 MB| + +## References + +https://huggingface.co/l3cube-pune/hindi-albert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-hindi_albert_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-01-hindi_albert_pipeline_hi.md new file mode 100644 index 00000000000000..f000255796f974 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-hindi_albert_pipeline_hi.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Hindi hindi_albert_pipeline pipeline AlbertEmbeddings from l3cube-pune +author: John Snow Labs +name: hindi_albert_pipeline +date: 2024-09-01 +tags: [hi, open_source, pipeline, onnx] +task: Embeddings +language: hi +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hindi_albert_pipeline` is a Hindi model originally trained by l3cube-pune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hindi_albert_pipeline_hi_5.4.2_3.0_1725206208136.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hindi_albert_pipeline_hi_5.4.2_3.0_1725206208136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hindi_albert_pipeline", lang = "hi") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hindi_albert_pipeline", lang = "hi") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hindi_albert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|hi| +|Size:|125.4 MB| + +## References + +https://huggingface.co/l3cube-pune/hindi-albert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-hinglish_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-01-hinglish_distilbert_en.md new file mode 100644 index 00000000000000..dfe41de1fc0829 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-hinglish_distilbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hinglish_distilbert DistilBertEmbeddings from meghanabhange +author: John Snow Labs +name: hinglish_distilbert +date: 2024-09-01 +tags: [distilbert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hinglish_distilbert` is a English model originally trained by meghanabhange. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hinglish_distilbert_en_5.5.0_3.0_1725213753531.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hinglish_distilbert_en_5.5.0_3.0_1725213753531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =DistilBertEmbeddings.pretrained("hinglish_distilbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = DistilBertEmbeddings + .pretrained("hinglish_distilbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hinglish_distilbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|245.9 MB| + +## References + +References + +References + +https://huggingface.co/meghanabhange/Hinglish-DistilBert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-hinglish_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-hinglish_distilbert_pipeline_en.md new file mode 100644 index 00000000000000..aa0b26b56c675e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-hinglish_distilbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hinglish_distilbert_pipeline pipeline DistilBertForSequenceClassification from Narasimha +author: John Snow Labs +name: hinglish_distilbert_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hinglish_distilbert_pipeline` is a English model originally trained by Narasimha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hinglish_distilbert_pipeline_en_5.5.0_3.0_1725213767079.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hinglish_distilbert_pipeline_en_5.5.0_3.0_1725213767079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hinglish_distilbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hinglish_distilbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hinglish_distilbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|245.9 MB| + +## References + +https://huggingface.co/Narasimha/hinglish-distilbert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-hnai_model_en.md b/docs/_posts/ahmedlone127/2024-09-01-hnai_model_en.md new file mode 100644 index 00000000000000..882710894858c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-hnai_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hnai_model XlmRoBertaForSequenceClassification from 203427as321 +author: John Snow Labs +name: hnai_model +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hnai_model` is a English model originally trained by 203427as321. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hnai_model_en_5.4.2_3.0_1725169597311.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hnai_model_en_5.4.2_3.0_1725169597311.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("hnai_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("hnai_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hnai_model| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|850.2 MB| + +## References + +https://huggingface.co/203427as321/hnai_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-imdb_microsoft_deberta_v3_large_seed_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-imdb_microsoft_deberta_v3_large_seed_1_pipeline_en.md new file mode 100644 index 00000000000000..422a1f8d6f82ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-imdb_microsoft_deberta_v3_large_seed_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English imdb_microsoft_deberta_v3_large_seed_1_pipeline pipeline DeBertaForSequenceClassification from utahnlp +author: John Snow Labs +name: imdb_microsoft_deberta_v3_large_seed_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_microsoft_deberta_v3_large_seed_1_pipeline` is a English model originally trained by utahnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdb_microsoft_deberta_v3_large_seed_1_pipeline_en_5.5.0_3.0_1725209422777.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_microsoft_deberta_v3_large_seed_1_pipeline_en_5.5.0_3.0_1725209422777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("imdb_microsoft_deberta_v3_large_seed_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("imdb_microsoft_deberta_v3_large_seed_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|imdb_microsoft_deberta_v3_large_seed_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/utahnlp/imdb_microsoft_deberta-v3-large_seed-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-immunization_classification_model_en.md b/docs/_posts/ahmedlone127/2024-09-01-immunization_classification_model_en.md new file mode 100644 index 00000000000000..8c3622248383ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-immunization_classification_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English immunization_classification_model DistilBertForSequenceClassification from peterkros +author: John Snow Labs +name: immunization_classification_model +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`immunization_classification_model` is a English model originally trained by peterkros. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/immunization_classification_model_en_5.5.0_3.0_1725213666616.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/immunization_classification_model_en_5.5.0_3.0_1725213666616.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("immunization_classification_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("immunization_classification_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|immunization_classification_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/peterkros/immunization-classification-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-immunization_classification_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-immunization_classification_model_pipeline_en.md new file mode 100644 index 00000000000000..90ec3749c0a6c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-immunization_classification_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English immunization_classification_model_pipeline pipeline DistilBertForSequenceClassification from peterkros +author: John Snow Labs +name: immunization_classification_model_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`immunization_classification_model_pipeline` is a English model originally trained by peterkros. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/immunization_classification_model_pipeline_en_5.5.0_3.0_1725213683317.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/immunization_classification_model_pipeline_en_5.5.0_3.0_1725213683317.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("immunization_classification_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("immunization_classification_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|immunization_classification_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/peterkros/immunization-classification-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-indic_bert_finetuned_ours_ds_en.md b/docs/_posts/ahmedlone127/2024-09-01-indic_bert_finetuned_ours_ds_en.md new file mode 100644 index 00000000000000..81bfcb7f105951 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-indic_bert_finetuned_ours_ds_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English indic_bert_finetuned_ours_ds AlbertForSequenceClassification from IIIT-L +author: John Snow Labs +name: indic_bert_finetuned_ours_ds +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_finetuned_ours_ds` is a English model originally trained by IIIT-L. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_finetuned_ours_ds_en_5.4.2_3.0_1725188306187.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_finetuned_ours_ds_en_5.4.2_3.0_1725188306187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("indic_bert_finetuned_ours_ds","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("indic_bert_finetuned_ours_ds", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indic_bert_finetuned_ours_ds| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|127.8 MB| + +## References + +https://huggingface.co/IIIT-L/indic-bert-finetuned-ours-DS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-indicbert_arabic_urdu_en.md b/docs/_posts/ahmedlone127/2024-09-01-indicbert_arabic_urdu_en.md new file mode 100644 index 00000000000000..4f64efafb818e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-indicbert_arabic_urdu_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English indicbert_arabic_urdu AlbertForTokenClassification from anwesham +author: John Snow Labs +name: indicbert_arabic_urdu +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, albert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indicbert_arabic_urdu` is a English model originally trained by anwesham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indicbert_arabic_urdu_en_5.4.2_3.0_1725203013530.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indicbert_arabic_urdu_en_5.4.2_3.0_1725203013530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = AlbertForTokenClassification.pretrained("indicbert_arabic_urdu","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = AlbertForTokenClassification.pretrained("indicbert_arabic_urdu", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indicbert_arabic_urdu| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|125.6 MB| + +## References + +https://huggingface.co/anwesham/indicbert_ar_ur \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-indicbert_arabic_urdu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-indicbert_arabic_urdu_pipeline_en.md new file mode 100644 index 00000000000000..b1fc1ab436d998 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-indicbert_arabic_urdu_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English indicbert_arabic_urdu_pipeline pipeline AlbertForTokenClassification from anwesham +author: John Snow Labs +name: indicbert_arabic_urdu_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indicbert_arabic_urdu_pipeline` is a English model originally trained by anwesham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indicbert_arabic_urdu_pipeline_en_5.4.2_3.0_1725203019907.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indicbert_arabic_urdu_pipeline_en_5.4.2_3.0_1725203019907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indicbert_arabic_urdu_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indicbert_arabic_urdu_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indicbert_arabic_urdu_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|125.6 MB| + +## References + +https://huggingface.co/anwesham/indicbert_ar_ur + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-indobert_for_eqa_finetuned_ms.md b/docs/_posts/ahmedlone127/2024-09-01-indobert_for_eqa_finetuned_ms.md new file mode 100644 index 00000000000000..c34dad8d41a500 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-indobert_for_eqa_finetuned_ms.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Malay (macrolanguage) indobert_for_eqa_finetuned BertForQuestionAnswering from primasr +author: John Snow Labs +name: indobert_for_eqa_finetuned +date: 2024-09-01 +tags: [ms, open_source, onnx, question_answering, bert] +task: Question Answering +language: ms +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_for_eqa_finetuned` is a Malay (macrolanguage) model originally trained by primasr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_for_eqa_finetuned_ms_5.5.0_3.0_1725215228647.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_for_eqa_finetuned_ms_5.5.0_3.0_1725215228647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("indobert_for_eqa_finetuned","ms") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("indobert_for_eqa_finetuned", "ms") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobert_for_eqa_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|ms| +|Size:|411.7 MB| + +## References + +https://huggingface.co/primasr/indobert-for-eqa-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-indobert_for_eqa_finetuned_pipeline_ms.md b/docs/_posts/ahmedlone127/2024-09-01-indobert_for_eqa_finetuned_pipeline_ms.md new file mode 100644 index 00000000000000..d60dade0c0f2f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-indobert_for_eqa_finetuned_pipeline_ms.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Malay (macrolanguage) indobert_for_eqa_finetuned_pipeline pipeline BertForQuestionAnswering from primasr +author: John Snow Labs +name: indobert_for_eqa_finetuned_pipeline +date: 2024-09-01 +tags: [ms, open_source, pipeline, onnx] +task: Question Answering +language: ms +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_for_eqa_finetuned_pipeline` is a Malay (macrolanguage) model originally trained by primasr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_for_eqa_finetuned_pipeline_ms_5.5.0_3.0_1725215251402.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_for_eqa_finetuned_pipeline_ms_5.5.0_3.0_1725215251402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indobert_for_eqa_finetuned_pipeline", lang = "ms") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indobert_for_eqa_finetuned_pipeline", lang = "ms") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobert_for_eqa_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ms| +|Size:|411.7 MB| + +## References + +https://huggingface.co/primasr/indobert-for-eqa-finetuned + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-indobert_lite_squadx_id.md b/docs/_posts/ahmedlone127/2024-09-01-indobert_lite_squadx_id.md new file mode 100644 index 00000000000000..b08725a853f6df --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-indobert_lite_squadx_id.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Indonesian indobert_lite_squadx BertForQuestionAnswering from Wikidepia +author: John Snow Labs +name: indobert_lite_squadx +date: 2024-09-01 +tags: [id, open_source, onnx, question_answering, bert] +task: Question Answering +language: id +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_lite_squadx` is a Indonesian model originally trained by Wikidepia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_lite_squadx_id_5.4.2_3.0_1725184733563.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_lite_squadx_id_5.4.2_3.0_1725184733563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("indobert_lite_squadx","id") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("indobert_lite_squadx", "id") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobert_lite_squadx| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|id| +|Size:|41.9 MB| + +## References + +https://huggingface.co/Wikidepia/indobert-lite-squadx \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-jerteh_81_pipeline_sr.md b/docs/_posts/ahmedlone127/2024-09-01-jerteh_81_pipeline_sr.md new file mode 100644 index 00000000000000..aab464d4bedcad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-jerteh_81_pipeline_sr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Serbian jerteh_81_pipeline pipeline RoBertaEmbeddings from jerteh +author: John Snow Labs +name: jerteh_81_pipeline +date: 2024-09-01 +tags: [sr, open_source, pipeline, onnx] +task: Embeddings +language: sr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jerteh_81_pipeline` is a Serbian model originally trained by jerteh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jerteh_81_pipeline_sr_5.4.2_3.0_1725186106877.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jerteh_81_pipeline_sr_5.4.2_3.0_1725186106877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("jerteh_81_pipeline", lang = "sr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("jerteh_81_pipeline", lang = "sr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|jerteh_81_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|sr| +|Size:|289.9 MB| + +## References + +https://huggingface.co/jerteh/Jerteh-81 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-jerteh_81_sr.md b/docs/_posts/ahmedlone127/2024-09-01-jerteh_81_sr.md new file mode 100644 index 00000000000000..654940e0dab9d8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-jerteh_81_sr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Serbian jerteh_81 RoBertaEmbeddings from jerteh +author: John Snow Labs +name: jerteh_81 +date: 2024-09-01 +tags: [sr, open_source, onnx, embeddings, roberta] +task: Embeddings +language: sr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jerteh_81` is a Serbian model originally trained by jerteh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jerteh_81_sr_5.4.2_3.0_1725186090240.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jerteh_81_sr_5.4.2_3.0_1725186090240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("jerteh_81","sr") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("jerteh_81","sr") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|jerteh_81| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|sr| +|Size:|289.9 MB| + +## References + +https://huggingface.co/jerteh/Jerteh-81 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-kmdb_ner_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-kmdb_ner_model_pipeline_en.md new file mode 100644 index 00000000000000..5d63adcb35cbae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-kmdb_ner_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English kmdb_ner_model_pipeline pipeline BertForTokenClassification from boapps +author: John Snow Labs +name: kmdb_ner_model_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kmdb_ner_model_pipeline` is a English model originally trained by boapps. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kmdb_ner_model_pipeline_en_5.4.2_3.0_1725163893805.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kmdb_ner_model_pipeline_en_5.4.2_3.0_1725163893805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("kmdb_ner_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("kmdb_ner_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kmdb_ner_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.5 MB| + +## References + +https://huggingface.co/boapps/kmdb_ner_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-langdetect_en.md b/docs/_posts/ahmedlone127/2024-09-01-langdetect_en.md new file mode 100644 index 00000000000000..fc0825504dbf88 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-langdetect_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English langdetect XlmRoBertaForSequenceClassification from ERCDiDip +author: John Snow Labs +name: langdetect +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`langdetect` is a English model originally trained by ERCDiDip. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/langdetect_en_5.4.2_3.0_1725169113465.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/langdetect_en_5.4.2_3.0_1725169113465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("langdetect","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("langdetect", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|langdetect| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|927.0 MB| + +## References + +https://huggingface.co/ERCDiDip/langdetect \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-latest_model_en.md b/docs/_posts/ahmedlone127/2024-09-01-latest_model_en.md new file mode 100644 index 00000000000000..5d77467a89f5db --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-latest_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English latest_model DistilBertForTokenClassification from Gkumi +author: John Snow Labs +name: latest_model +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`latest_model` is a English model originally trained by Gkumi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/latest_model_en_5.4.2_3.0_1725170616606.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/latest_model_en_5.4.2_3.0_1725170616606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("latest_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("latest_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|latest_model| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|244.0 MB| + +## References + +https://huggingface.co/Gkumi/latest-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-lenu_german_en.md b/docs/_posts/ahmedlone127/2024-09-01-lenu_german_en.md new file mode 100644 index 00000000000000..f1e6d98710bdc6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-lenu_german_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English lenu_german BertForSequenceClassification from Sociovestix +author: John Snow Labs +name: lenu_german +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_german` is a English model originally trained by Sociovestix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lenu_german_en_5.4.2_3.0_1725205359648.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_german_en_5.4.2_3.0_1725205359648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("lenu_german","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("lenu_german", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lenu_german| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/Sociovestix/lenu_DE \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-lenu_german_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-lenu_german_pipeline_en.md new file mode 100644 index 00000000000000..4f9b4ab603941f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-lenu_german_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lenu_german_pipeline pipeline BertForSequenceClassification from Sociovestix +author: John Snow Labs +name: lenu_german_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_german_pipeline` is a English model originally trained by Sociovestix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lenu_german_pipeline_en_5.4.2_3.0_1725205382798.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_german_pipeline_en_5.4.2_3.0_1725205382798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lenu_german_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lenu_german_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lenu_german_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/Sociovestix/lenu_DE + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-lenu_spanish_en.md b/docs/_posts/ahmedlone127/2024-09-01-lenu_spanish_en.md new file mode 100644 index 00000000000000..3090bd562cf9db --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-lenu_spanish_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English lenu_spanish BertForSequenceClassification from Sociovestix +author: John Snow Labs +name: lenu_spanish +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_spanish` is a English model originally trained by Sociovestix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lenu_spanish_en_5.4.2_3.0_1725205062828.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_spanish_en_5.4.2_3.0_1725205062828.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("lenu_spanish","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("lenu_spanish", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lenu_spanish| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|627.8 MB| + +## References + +https://huggingface.co/Sociovestix/lenu_ES \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-lenu_spanish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-lenu_spanish_pipeline_en.md new file mode 100644 index 00000000000000..b63fcc5a713463 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-lenu_spanish_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lenu_spanish_pipeline pipeline BertForSequenceClassification from Sociovestix +author: John Snow Labs +name: lenu_spanish_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_spanish_pipeline` is a English model originally trained by Sociovestix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lenu_spanish_pipeline_en_5.4.2_3.0_1725205098089.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_spanish_pipeline_en_5.4.2_3.0_1725205098089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lenu_spanish_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lenu_spanish_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lenu_spanish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|627.9 MB| + +## References + +https://huggingface.co/Sociovestix/lenu_ES + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-linkbert_large_en.md b/docs/_posts/ahmedlone127/2024-09-01-linkbert_large_en.md new file mode 100644 index 00000000000000..6805d85e5da95c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-linkbert_large_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English linkbert_large BertEmbeddings from michiyasunaga +author: John Snow Labs +name: linkbert_large +date: 2024-09-01 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`linkbert_large` is a English model originally trained by michiyasunaga. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/linkbert_large_en_5.4.2_3.0_1725204641527.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/linkbert_large_en_5.4.2_3.0_1725204641527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("linkbert_large","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("linkbert_large", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|linkbert_large| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.2 GB| + +## References + +References + +https://huggingface.co/michiyasunaga/LinkBERT-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-linkbert_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-linkbert_large_pipeline_en.md new file mode 100644 index 00000000000000..110543907ec7b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-linkbert_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English linkbert_large_pipeline pipeline BertForSequenceClassification from michiyasunaga +author: John Snow Labs +name: linkbert_large_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`linkbert_large_pipeline` is a English model originally trained by michiyasunaga. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/linkbert_large_pipeline_en_5.4.2_3.0_1725204709140.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/linkbert_large_pipeline_en_5.4.2_3.0_1725204709140.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("linkbert_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("linkbert_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|linkbert_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/michiyasunaga/LinkBERT-large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-literary_bge_en.md b/docs/_posts/ahmedlone127/2024-09-01-literary_bge_en.md new file mode 100644 index 00000000000000..4c0e32cabc0870 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-literary_bge_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English literary_bge BGEEmbeddings from crazyjeannot +author: John Snow Labs +name: literary_bge +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`literary_bge` is a English model originally trained by crazyjeannot. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/literary_bge_en_5.4.2_3.0_1725198781006.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/literary_bge_en_5.4.2_3.0_1725198781006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("literary_bge","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("literary_bge","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|literary_bge| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/crazyjeannot/literary_bge \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-literary_bge_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-literary_bge_pipeline_en.md new file mode 100644 index 00000000000000..5d5c36cefd083d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-literary_bge_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English literary_bge_pipeline pipeline BGEEmbeddings from crazyjeannot +author: John Snow Labs +name: literary_bge_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`literary_bge_pipeline` is a English model originally trained by crazyjeannot. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/literary_bge_pipeline_en_5.4.2_3.0_1725198857530.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/literary_bge_pipeline_en_5.4.2_3.0_1725198857530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("literary_bge_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("literary_bge_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|literary_bge_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/crazyjeannot/literary_bge + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-lithuanian_namesonly_en.md b/docs/_posts/ahmedlone127/2024-09-01-lithuanian_namesonly_en.md new file mode 100644 index 00000000000000..0032f2d04dcddf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-lithuanian_namesonly_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English lithuanian_namesonly MPNetEmbeddings from matthewleechen +author: John Snow Labs +name: lithuanian_namesonly +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lithuanian_namesonly` is a English model originally trained by matthewleechen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lithuanian_namesonly_en_5.5.0_3.0_1725224820747.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lithuanian_namesonly_en_5.5.0_3.0_1725224820747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("lithuanian_namesonly","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("lithuanian_namesonly","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lithuanian_namesonly| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/matthewleechen/lt_namesonly \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-lithuanian_namesonly_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-lithuanian_namesonly_pipeline_en.md new file mode 100644 index 00000000000000..6fe43818de765c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-lithuanian_namesonly_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English lithuanian_namesonly_pipeline pipeline MPNetEmbeddings from matthewleechen +author: John Snow Labs +name: lithuanian_namesonly_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lithuanian_namesonly_pipeline` is a English model originally trained by matthewleechen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lithuanian_namesonly_pipeline_en_5.5.0_3.0_1725224843449.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lithuanian_namesonly_pipeline_en_5.5.0_3.0_1725224843449.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lithuanian_namesonly_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lithuanian_namesonly_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lithuanian_namesonly_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/matthewleechen/lt_namesonly + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-llama_goodbooks_mpnet_en.md b/docs/_posts/ahmedlone127/2024-09-01-llama_goodbooks_mpnet_en.md new file mode 100644 index 00000000000000..e2fb8b11f6fe96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-llama_goodbooks_mpnet_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English llama_goodbooks_mpnet MPNetEmbeddings from beeformer +author: John Snow Labs +name: llama_goodbooks_mpnet +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_goodbooks_mpnet` is a English model originally trained by beeformer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_goodbooks_mpnet_en_5.5.0_3.0_1725224828458.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_goodbooks_mpnet_en_5.5.0_3.0_1725224828458.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("llama_goodbooks_mpnet","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("llama_goodbooks_mpnet","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_goodbooks_mpnet| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/beeformer/Llama-goodbooks-mpnet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-llama_goodbooks_mpnet_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-llama_goodbooks_mpnet_pipeline_en.md new file mode 100644 index 00000000000000..1841220bc47d5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-llama_goodbooks_mpnet_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English llama_goodbooks_mpnet_pipeline pipeline MPNetEmbeddings from beeformer +author: John Snow Labs +name: llama_goodbooks_mpnet_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_goodbooks_mpnet_pipeline` is a English model originally trained by beeformer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_goodbooks_mpnet_pipeline_en_5.5.0_3.0_1725224853112.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_goodbooks_mpnet_pipeline_en_5.5.0_3.0_1725224853112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("llama_goodbooks_mpnet_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("llama_goodbooks_mpnet_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_goodbooks_mpnet_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/beeformer/Llama-goodbooks-mpnet + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-llama_movielens_mpnet_en.md b/docs/_posts/ahmedlone127/2024-09-01-llama_movielens_mpnet_en.md new file mode 100644 index 00000000000000..93c48c63835f0f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-llama_movielens_mpnet_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English llama_movielens_mpnet MPNetEmbeddings from beeformer +author: John Snow Labs +name: llama_movielens_mpnet +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_movielens_mpnet` is a English model originally trained by beeformer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_movielens_mpnet_en_5.5.0_3.0_1725224681897.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_movielens_mpnet_en_5.5.0_3.0_1725224681897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("llama_movielens_mpnet","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("llama_movielens_mpnet","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_movielens_mpnet| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/beeformer/Llama-movielens-mpnet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-llama_movielens_mpnet_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-llama_movielens_mpnet_pipeline_en.md new file mode 100644 index 00000000000000..1c3c98d4997584 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-llama_movielens_mpnet_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English llama_movielens_mpnet_pipeline pipeline MPNetEmbeddings from beeformer +author: John Snow Labs +name: llama_movielens_mpnet_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_movielens_mpnet_pipeline` is a English model originally trained by beeformer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_movielens_mpnet_pipeline_en_5.5.0_3.0_1725224704050.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_movielens_mpnet_pipeline_en_5.5.0_3.0_1725224704050.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("llama_movielens_mpnet_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("llama_movielens_mpnet_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_movielens_mpnet_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/beeformer/Llama-movielens-mpnet + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-m1_mlm_en.md b/docs/_posts/ahmedlone127/2024-09-01-m1_mlm_en.md new file mode 100644 index 00000000000000..bff1ed75205a2d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-m1_mlm_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English m1_mlm AlbertEmbeddings from S2312dal +author: John Snow Labs +name: m1_mlm +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, albert] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m1_mlm` is a English model originally trained by S2312dal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m1_mlm_en_5.4.2_3.0_1725205796426.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m1_mlm_en_5.4.2_3.0_1725205796426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = AlbertEmbeddings.pretrained("m1_mlm","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = AlbertEmbeddings.pretrained("m1_mlm","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|m1_mlm| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[albert]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/S2312dal/M1_MLM \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-m1_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-m1_mlm_pipeline_en.md new file mode 100644 index 00000000000000..817033e7fccb85 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-m1_mlm_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English m1_mlm_pipeline pipeline AlbertEmbeddings from S2312dal +author: John Snow Labs +name: m1_mlm_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m1_mlm_pipeline` is a English model originally trained by S2312dal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m1_mlm_pipeline_en_5.4.2_3.0_1725205798847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m1_mlm_pipeline_en_5.4.2_3.0_1725205798847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("m1_mlm_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("m1_mlm_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|m1_mlm_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/S2312dal/M1_MLM + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-malayalambert_en.md b/docs/_posts/ahmedlone127/2024-09-01-malayalambert_en.md new file mode 100644 index 00000000000000..e0c4e7e72b0897 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-malayalambert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English malayalambert RoBertaEmbeddings from eliasedwin7 +author: John Snow Labs +name: malayalambert +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malayalambert` is a English model originally trained by eliasedwin7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malayalambert_en_5.4.2_3.0_1725191218628.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malayalambert_en_5.4.2_3.0_1725191218628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("malayalambert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("malayalambert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|malayalambert| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|311.8 MB| + +## References + +https://huggingface.co/eliasedwin7/MalayalamBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-marathi_question_answering_squad_bert_mr.md b/docs/_posts/ahmedlone127/2024-09-01-marathi_question_answering_squad_bert_mr.md new file mode 100644 index 00000000000000..d7610a90c5acfc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-marathi_question_answering_squad_bert_mr.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Marathi marathi_question_answering_squad_bert BertForQuestionAnswering from l3cube-pune +author: John Snow Labs +name: marathi_question_answering_squad_bert +date: 2024-09-01 +tags: [mr, open_source, onnx, question_answering, bert] +task: Question Answering +language: mr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marathi_question_answering_squad_bert` is a Marathi model originally trained by l3cube-pune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marathi_question_answering_squad_bert_mr_5.4.2_3.0_1725185301925.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marathi_question_answering_squad_bert_mr_5.4.2_3.0_1725185301925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("marathi_question_answering_squad_bert","mr") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("marathi_question_answering_squad_bert", "mr") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marathi_question_answering_squad_bert| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|mr| +|Size:|890.6 MB| + +## References + +https://huggingface.co/l3cube-pune/marathi-question-answering-squad-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mariobert_448_inpaint_context_length_en.md b/docs/_posts/ahmedlone127/2024-09-01-mariobert_448_inpaint_context_length_en.md new file mode 100644 index 00000000000000..de219466f9e16f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mariobert_448_inpaint_context_length_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mariobert_448_inpaint_context_length RoBertaEmbeddings from shyamsn97 +author: John Snow Labs +name: mariobert_448_inpaint_context_length +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mariobert_448_inpaint_context_length` is a English model originally trained by shyamsn97. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mariobert_448_inpaint_context_length_en_5.4.2_3.0_1725165490106.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mariobert_448_inpaint_context_length_en_5.4.2_3.0_1725165490106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("mariobert_448_inpaint_context_length","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("mariobert_448_inpaint_context_length","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mariobert_448_inpaint_context_length| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|305.6 MB| + +## References + +https://huggingface.co/shyamsn97/MarioBert-448-inpaint-context-length \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-marsilia_embeddings_english_large_en.md b/docs/_posts/ahmedlone127/2024-09-01-marsilia_embeddings_english_large_en.md new file mode 100644 index 00000000000000..dac207e41b1d8e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-marsilia_embeddings_english_large_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English marsilia_embeddings_english_large BGEEmbeddings from sujet-ai +author: John Snow Labs +name: marsilia_embeddings_english_large +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marsilia_embeddings_english_large` is a English model originally trained by sujet-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marsilia_embeddings_english_large_en_5.5.0_3.0_1725228930175.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marsilia_embeddings_english_large_en_5.5.0_3.0_1725228930175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("marsilia_embeddings_english_large","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("marsilia_embeddings_english_large","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marsilia_embeddings_english_large| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/sujet-ai/Marsilia-Embeddings-EN-Large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-marsilia_embeddings_english_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-marsilia_embeddings_english_large_pipeline_en.md new file mode 100644 index 00000000000000..53c66a7254f4c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-marsilia_embeddings_english_large_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English marsilia_embeddings_english_large_pipeline pipeline BGEEmbeddings from sujet-ai +author: John Snow Labs +name: marsilia_embeddings_english_large_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marsilia_embeddings_english_large_pipeline` is a English model originally trained by sujet-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marsilia_embeddings_english_large_pipeline_en_5.5.0_3.0_1725229003570.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marsilia_embeddings_english_large_pipeline_en_5.5.0_3.0_1725229003570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marsilia_embeddings_english_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marsilia_embeddings_english_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marsilia_embeddings_english_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/sujet-ai/Marsilia-Embeddings-EN-Large + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mathberta_en.md b/docs/_posts/ahmedlone127/2024-09-01-mathberta_en.md new file mode 100644 index 00000000000000..89614110fef773 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mathberta_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mathberta RoBertaEmbeddings from witiko +author: John Snow Labs +name: mathberta +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mathberta` is a English model originally trained by witiko. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mathberta_en_5.4.2_3.0_1725186190581.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mathberta_en_5.4.2_3.0_1725186190581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("mathberta","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("mathberta","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mathberta| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|548.3 MB| + +## References + +https://huggingface.co/witiko/mathberta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mathberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mathberta_pipeline_en.md new file mode 100644 index 00000000000000..dea6f27e1a0bdb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mathberta_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mathberta_pipeline pipeline RoBertaEmbeddings from witiko +author: John Snow Labs +name: mathberta_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mathberta_pipeline` is a English model originally trained by witiko. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mathberta_pipeline_en_5.4.2_3.0_1725186219507.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mathberta_pipeline_en_5.4.2_3.0_1725186219507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mathberta_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mathberta_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mathberta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|548.3 MB| + +## References + +https://huggingface.co/witiko/mathberta + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mcontriever_msmarco_xnli_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-01-mcontriever_msmarco_xnli_pipeline_xx.md new file mode 100644 index 00000000000000..a3ae2ba6ab6b90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mcontriever_msmarco_xnli_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual mcontriever_msmarco_xnli_pipeline pipeline BertForZeroShotClassification from mjwong +author: John Snow Labs +name: mcontriever_msmarco_xnli_pipeline +date: 2024-09-01 +tags: [xx, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mcontriever_msmarco_xnli_pipeline` is a Multilingual model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mcontriever_msmarco_xnli_pipeline_xx_5.4.2_3.0_1725202432638.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mcontriever_msmarco_xnli_pipeline_xx_5.4.2_3.0_1725202432638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mcontriever_msmarco_xnli_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mcontriever_msmarco_xnli_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mcontriever_msmarco_xnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|665.8 MB| + +## References + +https://huggingface.co/mjwong/mcontriever-msmarco-xnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mcontriever_msmarco_xnli_xx.md b/docs/_posts/ahmedlone127/2024-09-01-mcontriever_msmarco_xnli_xx.md new file mode 100644 index 00000000000000..912a4c6558bdc0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mcontriever_msmarco_xnli_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual mcontriever_msmarco_xnli BertForZeroShotClassification from mjwong +author: John Snow Labs +name: mcontriever_msmarco_xnli +date: 2024-09-01 +tags: [xx, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mcontriever_msmarco_xnli` is a Multilingual model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mcontriever_msmarco_xnli_xx_5.4.2_3.0_1725202395904.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mcontriever_msmarco_xnli_xx_5.4.2_3.0_1725202395904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("mcontriever_msmarco_xnli","xx") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("mcontriever_msmarco_xnli", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mcontriever_msmarco_xnli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|665.8 MB| + +## References + +https://huggingface.co/mjwong/mcontriever-msmarco-xnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mcontriever_xnli_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-01-mcontriever_xnli_pipeline_xx.md new file mode 100644 index 00000000000000..4e7392cc8a327e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mcontriever_xnli_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual mcontriever_xnli_pipeline pipeline BertForZeroShotClassification from mjwong +author: John Snow Labs +name: mcontriever_xnli_pipeline +date: 2024-09-01 +tags: [xx, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mcontriever_xnli_pipeline` is a Multilingual model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mcontriever_xnli_pipeline_xx_5.4.2_3.0_1725201609456.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mcontriever_xnli_pipeline_xx_5.4.2_3.0_1725201609456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mcontriever_xnli_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mcontriever_xnli_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mcontriever_xnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|665.8 MB| + +## References + +https://huggingface.co/mjwong/mcontriever-xnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mcontriever_xnli_xx.md b/docs/_posts/ahmedlone127/2024-09-01-mcontriever_xnli_xx.md new file mode 100644 index 00000000000000..08a5626d81758b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mcontriever_xnli_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual mcontriever_xnli BertForZeroShotClassification from mjwong +author: John Snow Labs +name: mcontriever_xnli +date: 2024-09-01 +tags: [xx, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mcontriever_xnli` is a Multilingual model originally trained by mjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mcontriever_xnli_xx_5.4.2_3.0_1725201570842.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mcontriever_xnli_xx_5.4.2_3.0_1725201570842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("mcontriever_xnli","xx") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("mcontriever_xnli", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mcontriever_xnli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|665.8 MB| + +## References + +https://huggingface.co/mjwong/mcontriever-xnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_all_15_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_all_15_en.md new file mode 100644 index 00000000000000..6930370009af90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_all_15_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mdeberta_all_15 DeBertaForTokenClassification from ricardo-filho +author: John Snow Labs +name: mdeberta_all_15 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_all_15` is a English model originally trained by ricardo-filho. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_all_15_en_5.4.2_3.0_1725197391174.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_all_15_en_5.4.2_3.0_1725197391174.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_all_15","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_all_15", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_all_15| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|886.2 MB| + +## References + +https://huggingface.co/ricardo-filho/mdeberta_all_15 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_all_15_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_all_15_pipeline_en.md new file mode 100644 index 00000000000000..e95790c7e4b37f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_all_15_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_all_15_pipeline pipeline DeBertaForTokenClassification from ricardo-filho +author: John Snow Labs +name: mdeberta_all_15_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_all_15_pipeline` is a English model originally trained by ricardo-filho. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_all_15_pipeline_en_5.4.2_3.0_1725197502340.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_all_15_pipeline_en_5.4.2_3.0_1725197502340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_all_15_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_all_15_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_all_15_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|886.2 MB| + +## References + +https://huggingface.co/ricardo-filho/mdeberta_all_15 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_cased_portuguese_ccorpus_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_cased_portuguese_ccorpus_en.md new file mode 100644 index 00000000000000..dc98b68155c8aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_cased_portuguese_ccorpus_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mdeberta_base_cased_portuguese_ccorpus DeBertaEmbeddings from rosimeirecosta +author: John Snow Labs +name: mdeberta_base_cased_portuguese_ccorpus +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_base_cased_portuguese_ccorpus` is a English model originally trained by rosimeirecosta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_base_cased_portuguese_ccorpus_en_5.5.0_3.0_1725217577930.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_base_cased_portuguese_ccorpus_en_5.5.0_3.0_1725217577930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("mdeberta_base_cased_portuguese_ccorpus","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("mdeberta_base_cased_portuguese_ccorpus","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_base_cased_portuguese_ccorpus| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/rosimeirecosta/mdeberta-base-cased-pt-ccorpus \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_cased_portuguese_ccorpus_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_cased_portuguese_ccorpus_pipeline_en.md new file mode 100644 index 00000000000000..465039abeff208 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_cased_portuguese_ccorpus_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_base_cased_portuguese_ccorpus_pipeline pipeline DeBertaEmbeddings from rosimeirecosta +author: John Snow Labs +name: mdeberta_base_cased_portuguese_ccorpus_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_base_cased_portuguese_ccorpus_pipeline` is a English model originally trained by rosimeirecosta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_base_cased_portuguese_ccorpus_pipeline_en_5.5.0_3.0_1725217634714.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_base_cased_portuguese_ccorpus_pipeline_en_5.5.0_3.0_1725217634714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_base_cased_portuguese_ccorpus_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_base_cased_portuguese_ccorpus_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_base_cased_portuguese_ccorpus_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/rosimeirecosta/mdeberta-base-cased-pt-ccorpus + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_formality_ranker_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_formality_ranker_pipeline_en.md new file mode 100644 index 00000000000000..1ecef49b523905 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_formality_ranker_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_base_formality_ranker_pipeline pipeline DeBertaForSequenceClassification from s-nlp +author: John Snow Labs +name: mdeberta_base_formality_ranker_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_base_formality_ranker_pipeline` is a English model originally trained by s-nlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_base_formality_ranker_pipeline_en_5.4.2_3.0_1725184228534.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_base_formality_ranker_pipeline_en_5.4.2_3.0_1725184228534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_base_formality_ranker_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_base_formality_ranker_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_base_formality_ranker_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|875.0 MB| + +## References + +https://huggingface.co/s-nlp/mdeberta-base-formality-ranker + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_v3_3_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_v3_3_en.md new file mode 100644 index 00000000000000..dd71dc24b9de55 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_v3_3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mdeberta_base_v3_3 DeBertaForSequenceClassification from alyazharr +author: John Snow Labs +name: mdeberta_base_v3_3 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_base_v3_3` is a English model originally trained by alyazharr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_base_v3_3_en_5.5.0_3.0_1725224030538.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_base_v3_3_en_5.5.0_3.0_1725224030538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_base_v3_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_base_v3_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_base_v3_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|831.7 MB| + +## References + +https://huggingface.co/alyazharr/mdeberta_base_v3_3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_v3_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_v3_3_pipeline_en.md new file mode 100644 index 00000000000000..bb7d80dd599cf1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_base_v3_3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_base_v3_3_pipeline pipeline DeBertaForSequenceClassification from alyazharr +author: John Snow Labs +name: mdeberta_base_v3_3_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_base_v3_3_pipeline` is a English model originally trained by alyazharr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_base_v3_3_pipeline_en_5.5.0_3.0_1725224111678.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_base_v3_3_pipeline_en_5.5.0_3.0_1725224111678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_base_v3_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_base_v3_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_base_v3_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|831.7 MB| + +## References + +https://huggingface.co/alyazharr/mdeberta_base_v3_3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_idkmrc_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_idkmrc_en.md new file mode 100644 index 00000000000000..26ca7c994d4e18 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_idkmrc_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_idkmrc DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: mdeberta_idkmrc +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_idkmrc` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_idkmrc_en_5.5.0_3.0_1725220683744.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_idkmrc_en_5.5.0_3.0_1725220683744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_idkmrc","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_idkmrc", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_idkmrc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|844.0 MB| + +## References + +https://huggingface.co/intanm/mdeberta-idkmrc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_idkmrc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_idkmrc_pipeline_en.md new file mode 100644 index 00000000000000..efc8c5a4040962 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_idkmrc_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_idkmrc_pipeline pipeline DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: mdeberta_idkmrc_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_idkmrc_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_idkmrc_pipeline_en_5.5.0_3.0_1725220796523.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_idkmrc_pipeline_en_5.5.0_3.0_1725220796523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_idkmrc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_idkmrc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_idkmrc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|844.0 MB| + +## References + +https://huggingface.co/intanm/mdeberta-idkmrc + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_idkmrc_webis_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_idkmrc_webis_en.md new file mode 100644 index 00000000000000..960c435fe67164 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_idkmrc_webis_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_idkmrc_webis DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: mdeberta_idkmrc_webis +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_idkmrc_webis` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_idkmrc_webis_en_5.5.0_3.0_1725220975115.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_idkmrc_webis_en_5.5.0_3.0_1725220975115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_idkmrc_webis","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_idkmrc_webis", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_idkmrc_webis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|870.2 MB| + +## References + +https://huggingface.co/intanm/mdeberta-idkmrc-webis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_idkmrc_webis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_idkmrc_webis_pipeline_en.md new file mode 100644 index 00000000000000..af3564396a7bee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_idkmrc_webis_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_idkmrc_webis_pipeline pipeline DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: mdeberta_idkmrc_webis_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_idkmrc_webis_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_idkmrc_webis_pipeline_en_5.5.0_3.0_1725221083745.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_idkmrc_webis_pipeline_en_5.5.0_3.0_1725221083745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_idkmrc_webis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_idkmrc_webis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_idkmrc_webis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|870.2 MB| + +## References + +https://huggingface.co/intanm/mdeberta-idkmrc-webis + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_assin2_similarity_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_assin2_similarity_pipeline_pt.md new file mode 100644 index 00000000000000..93b917cd871c50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_assin2_similarity_pipeline_pt.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Portuguese mdeberta_v3_base_assin2_similarity_pipeline pipeline DeBertaForSequenceClassification from ruanchaves +author: John Snow Labs +name: mdeberta_v3_base_assin2_similarity_pipeline +date: 2024-09-01 +tags: [pt, open_source, pipeline, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_assin2_similarity_pipeline` is a Portuguese model originally trained by ruanchaves. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_assin2_similarity_pipeline_pt_5.5.0_3.0_1725210284001.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_assin2_similarity_pipeline_pt_5.5.0_3.0_1725210284001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_assin2_similarity_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_assin2_similarity_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_assin2_similarity_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|836.2 MB| + +## References + +https://huggingface.co/ruanchaves/mdeberta-v3-base-assin2-similarity + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_assin2_similarity_pt.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_assin2_similarity_pt.md new file mode 100644 index 00000000000000..3b1653bac87de7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_assin2_similarity_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese mdeberta_v3_base_assin2_similarity DeBertaForSequenceClassification from ruanchaves +author: John Snow Labs +name: mdeberta_v3_base_assin2_similarity +date: 2024-09-01 +tags: [pt, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_assin2_similarity` is a Portuguese model originally trained by ruanchaves. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_assin2_similarity_pt_5.5.0_3.0_1725210226398.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_assin2_similarity_pt_5.5.0_3.0_1725210226398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_assin2_similarity","pt") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_assin2_similarity", "pt") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_assin2_similarity| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|836.2 MB| + +## References + +https://huggingface.co/ruanchaves/mdeberta-v3-base-assin2-similarity \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_claimbuster_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_claimbuster_en.md new file mode 100644 index 00000000000000..4e7787d7c934b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_claimbuster_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mdeberta_v3_base_claimbuster DeBertaForSequenceClassification from Nithiwat +author: John Snow Labs +name: mdeberta_v3_base_claimbuster +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_claimbuster` is a English model originally trained by Nithiwat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_claimbuster_en_5.5.0_3.0_1725223698840.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_claimbuster_en_5.5.0_3.0_1725223698840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_claimbuster","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_claimbuster", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_claimbuster| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|845.2 MB| + +## References + +https://huggingface.co/Nithiwat/mdeberta-v3-base_claimbuster \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_claimbuster_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_claimbuster_pipeline_en.md new file mode 100644 index 00000000000000..4c6a19f3ff593d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_claimbuster_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_v3_base_claimbuster_pipeline pipeline DeBertaForSequenceClassification from Nithiwat +author: John Snow Labs +name: mdeberta_v3_base_claimbuster_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_claimbuster_pipeline` is a English model originally trained by Nithiwat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_claimbuster_pipeline_en_5.5.0_3.0_1725223759678.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_claimbuster_pipeline_en_5.5.0_3.0_1725223759678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_claimbuster_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_claimbuster_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_claimbuster_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|845.2 MB| + +## References + +https://huggingface.co/Nithiwat/mdeberta-v3-base_claimbuster + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_distemist_es.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_distemist_es.md new file mode 100644 index 00000000000000..752b9d15bb54a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_distemist_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish mdeberta_v3_base_distemist DeBertaForTokenClassification from IIC +author: John Snow Labs +name: mdeberta_v3_base_distemist +date: 2024-09-01 +tags: [es, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_distemist` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_distemist_es_5.4.2_3.0_1725196928709.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_distemist_es_5.4.2_3.0_1725196928709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_distemist","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_distemist", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_distemist| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|792.4 MB| + +## References + +https://huggingface.co/IIC/mdeberta-v3-base-distemist \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_distemist_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_distemist_pipeline_es.md new file mode 100644 index 00000000000000..225f2fb6bcf39a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_distemist_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish mdeberta_v3_base_distemist_pipeline pipeline DeBertaForTokenClassification from IIC +author: John Snow Labs +name: mdeberta_v3_base_distemist_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_distemist_pipeline` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_distemist_pipeline_es_5.4.2_3.0_1725197079257.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_distemist_pipeline_es_5.4.2_3.0_1725197079257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_distemist_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_distemist_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_distemist_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|792.4 MB| + +## References + +https://huggingface.co/IIC/mdeberta-v3-base-distemist + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_en.md new file mode 100644 index 00000000000000..e725cd88090860 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0 DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_en_5.5.0_3.0_1725221251297.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_en_5.5.0_3.0_1725221251297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|811.4 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-v3-base_EW-TT-PE_U1_S0_DROP1_mdeberta_E2_DEV100.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline_en.md new file mode 100644 index 00000000000000..39292e939f9268 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline pipeline DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline_en_5.5.0_3.0_1725221367713.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline_en_5.5.0_3.0_1725221367713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|811.4 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-v3-base_EW-TT-PE_U1_S0_DROP1_mdeberta_E2_DEV100.0 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_en.md new file mode 100644 index 00000000000000..fe2fb512f7aba8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati DeBertaForSequenceClassification from Sleoruiz +author: John Snow Labs +name: mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati` is a English model originally trained by Sleoruiz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_en_5.5.0_3.0_1725222791461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_en_5.5.0_3.0_1725222791461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|824.1 MB| + +## References + +https://huggingface.co/Sleoruiz/mdeberta-v3-base-fine-tuned-text-classificarion-ds-ss \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_pipeline_en.md new file mode 100644 index 00000000000000..b4b52abb9816b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_pipeline pipeline DeBertaForSequenceClassification from Sleoruiz +author: John Snow Labs +name: mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_pipeline` is a English model originally trained by Sleoruiz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_pipeline_en_5.5.0_3.0_1725222923072.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_pipeline_en_5.5.0_3.0_1725222923072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_fine_tuned_text_classificarion_ds_swati_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|824.1 MB| + +## References + +https://huggingface.co/Sleoruiz/mdeberta-v3-base-fine-tuned-text-classificarion-ds-ss + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_livingner1_es.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_livingner1_es.md new file mode 100644 index 00000000000000..1010d11dff1c5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_livingner1_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish mdeberta_v3_base_livingner1 DeBertaForTokenClassification from IIC +author: John Snow Labs +name: mdeberta_v3_base_livingner1 +date: 2024-09-01 +tags: [es, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_livingner1` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_livingner1_es_5.4.2_3.0_1725196457027.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_livingner1_es_5.4.2_3.0_1725196457027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_livingner1","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_livingner1", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_livingner1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|797.2 MB| + +## References + +https://huggingface.co/IIC/mdeberta-v3-base-livingner1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_livingner1_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_livingner1_pipeline_es.md new file mode 100644 index 00000000000000..039d09255f19c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_livingner1_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish mdeberta_v3_base_livingner1_pipeline pipeline DeBertaForTokenClassification from IIC +author: John Snow Labs +name: mdeberta_v3_base_livingner1_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_livingner1_pipeline` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_livingner1_pipeline_es_5.4.2_3.0_1725196605169.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_livingner1_pipeline_es_5.4.2_3.0_1725196605169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_livingner1_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_livingner1_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_livingner1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|797.2 MB| + +## References + +https://huggingface.co/IIC/mdeberta-v3-base-livingner1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_en.md new file mode 100644 index 00000000000000..d4301999a05f18 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0 DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_en_5.5.0_3.0_1725219325911.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_en_5.5.0_3.0_1725219325911.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|810.6 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-v3-base_mdeberta_EW-TT-PE_U0_S1_DROP1_E8_DEV93.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_pipeline_en.md new file mode 100644 index 00000000000000..3870d91dd6a418 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_pipeline pipeline DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_pipeline` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_pipeline_en_5.5.0_3.0_1725219443994.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_pipeline_en_5.5.0_3.0_1725219443994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev93_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|810.6 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-v3-base_mdeberta_EW-TT-PE_U0_S1_DROP1_E8_DEV93.0 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_meddocan_es.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_meddocan_es.md new file mode 100644 index 00000000000000..4abdaafb17e2fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_meddocan_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish mdeberta_v3_base_meddocan DeBertaForTokenClassification from IIC +author: John Snow Labs +name: mdeberta_v3_base_meddocan +date: 2024-09-01 +tags: [es, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_meddocan` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_meddocan_es_5.4.2_3.0_1725196663947.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_meddocan_es_5.4.2_3.0_1725196663947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_meddocan","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_meddocan", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_meddocan| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|795.8 MB| + +## References + +https://huggingface.co/IIC/mdeberta-v3-base-meddocan \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_meddocan_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_meddocan_pipeline_es.md new file mode 100644 index 00000000000000..5f8da267dade10 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_meddocan_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish mdeberta_v3_base_meddocan_pipeline pipeline DeBertaForTokenClassification from IIC +author: John Snow Labs +name: mdeberta_v3_base_meddocan_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_meddocan_pipeline` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_meddocan_pipeline_es_5.4.2_3.0_1725196811476.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_meddocan_pipeline_es_5.4.2_3.0_1725196811476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_meddocan_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_meddocan_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_meddocan_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|795.8 MB| + +## References + +https://huggingface.co/IIC/mdeberta-v3-base-meddocan + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_mnli_10_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_mnli_10_en.md new file mode 100644 index 00000000000000..49abaad6437a30 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_mnli_10_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mdeberta_v3_base_mnli_10 DeBertaForSequenceClassification from tmnam20 +author: John Snow Labs +name: mdeberta_v3_base_mnli_10 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_mnli_10` is a English model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mnli_10_en_5.5.0_3.0_1725223852428.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mnli_10_en_5.5.0_3.0_1725223852428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_mnli_10","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_mnli_10", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_mnli_10| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|818.9 MB| + +## References + +https://huggingface.co/tmnam20/mdeberta-v3-base-mnli-10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_mnli_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_mnli_10_pipeline_en.md new file mode 100644 index 00000000000000..03b86bb19a777e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_mnli_10_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_v3_base_mnli_10_pipeline pipeline DeBertaForSequenceClassification from tmnam20 +author: John Snow Labs +name: mdeberta_v3_base_mnli_10_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_mnli_10_pipeline` is a English model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mnli_10_pipeline_en_5.5.0_3.0_1725223993933.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mnli_10_pipeline_en_5.5.0_3.0_1725223993933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_mnli_10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_mnli_10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_mnli_10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|818.9 MB| + +## References + +https://huggingface.co/tmnam20/mdeberta-v3-base-mnli-10 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_on_custom_kural_500_iiserkbikram_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_on_custom_kural_500_iiserkbikram_en.md new file mode 100644 index 00000000000000..936cbe3295de2f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_on_custom_kural_500_iiserkbikram_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mdeberta_v3_base_on_custom_kural_500_iiserkbikram DeBertaForSequenceClassification from iiserkbikram +author: John Snow Labs +name: mdeberta_v3_base_on_custom_kural_500_iiserkbikram +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_on_custom_kural_500_iiserkbikram` is a English model originally trained by iiserkbikram. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_on_custom_kural_500_iiserkbikram_en_5.5.0_3.0_1725222715978.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_on_custom_kural_500_iiserkbikram_en_5.5.0_3.0_1725222715978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_on_custom_kural_500_iiserkbikram","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_on_custom_kural_500_iiserkbikram", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_on_custom_kural_500_iiserkbikram| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|778.0 MB| + +## References + +https://huggingface.co/iiserkbikram/mdeberta-v3-base-on-custom-kural-500 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_on_custom_kural_500_iiserkbikram_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_on_custom_kural_500_iiserkbikram_pipeline_en.md new file mode 100644 index 00000000000000..3e741e66714c67 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_on_custom_kural_500_iiserkbikram_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_v3_base_on_custom_kural_500_iiserkbikram_pipeline pipeline DeBertaForSequenceClassification from iiserkbikram +author: John Snow Labs +name: mdeberta_v3_base_on_custom_kural_500_iiserkbikram_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_on_custom_kural_500_iiserkbikram_pipeline` is a English model originally trained by iiserkbikram. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_on_custom_kural_500_iiserkbikram_pipeline_en_5.5.0_3.0_1725222876125.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_on_custom_kural_500_iiserkbikram_pipeline_en_5.5.0_3.0_1725222876125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_on_custom_kural_500_iiserkbikram_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_on_custom_kural_500_iiserkbikram_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_on_custom_kural_500_iiserkbikram_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|778.0 MB| + +## References + +https://huggingface.co/iiserkbikram/mdeberta-v3-base-on-custom-kural-500 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_open_ner_english_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_open_ner_english_en.md new file mode 100644 index 00000000000000..459e58593ded4d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_open_ner_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mdeberta_v3_base_open_ner_english DeBertaForTokenClassification from datasciathlete +author: John Snow Labs +name: mdeberta_v3_base_open_ner_english +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_open_ner_english` is a English model originally trained by datasciathlete. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_open_ner_english_en_5.4.2_3.0_1725196255780.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_open_ner_english_en_5.4.2_3.0_1725196255780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_open_ner_english","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_open_ner_english", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_open_ner_english| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|940.5 MB| + +## References + +https://huggingface.co/datasciathlete/mdeberta-v3-base-open-ner-english \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_open_ner_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_open_ner_english_pipeline_en.md new file mode 100644 index 00000000000000..c15b338f703f70 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_open_ner_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_v3_base_open_ner_english_pipeline pipeline DeBertaForTokenClassification from datasciathlete +author: John Snow Labs +name: mdeberta_v3_base_open_ner_english_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_open_ner_english_pipeline` is a English model originally trained by datasciathlete. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_open_ner_english_pipeline_en_5.4.2_3.0_1725196321516.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_open_ner_english_pipeline_en_5.4.2_3.0_1725196321516.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_open_ner_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_open_ner_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_open_ner_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|940.5 MB| + +## References + +https://huggingface.co/datasciathlete/mdeberta-v3-base-open-ner-english + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_pharmaconer_es.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_pharmaconer_es.md new file mode 100644 index 00000000000000..4c5d00bfc1a367 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_pharmaconer_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish mdeberta_v3_base_pharmaconer DeBertaForTokenClassification from IIC +author: John Snow Labs +name: mdeberta_v3_base_pharmaconer +date: 2024-09-01 +tags: [es, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_pharmaconer` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_pharmaconer_es_5.4.2_3.0_1725197759052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_pharmaconer_es_5.4.2_3.0_1725197759052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_pharmaconer","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_pharmaconer", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_pharmaconer| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|795.2 MB| + +## References + +https://huggingface.co/IIC/mdeberta-v3-base-pharmaconer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_pharmaconer_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_pharmaconer_pipeline_es.md new file mode 100644 index 00000000000000..336cf814201a77 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_pharmaconer_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish mdeberta_v3_base_pharmaconer_pipeline pipeline DeBertaForTokenClassification from IIC +author: John Snow Labs +name: mdeberta_v3_base_pharmaconer_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_pharmaconer_pipeline` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_pharmaconer_pipeline_es_5.4.2_3.0_1725197905786.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_pharmaconer_pipeline_es_5.4.2_3.0_1725197905786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_pharmaconer_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_pharmaconer_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_pharmaconer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|795.3 MB| + +## References + +https://huggingface.co/IIC/mdeberta-v3-base-pharmaconer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_qa_squad_v1_norwegian_bokml_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_qa_squad_v1_norwegian_bokml_en.md new file mode 100644 index 00000000000000..3d3d0679914428 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_qa_squad_v1_norwegian_bokml_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_v3_base_qa_squad_v1_norwegian_bokml DeBertaForQuestionAnswering from eanderson +author: John Snow Labs +name: mdeberta_v3_base_qa_squad_v1_norwegian_bokml +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_qa_squad_v1_norwegian_bokml` is a English model originally trained by eanderson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_qa_squad_v1_norwegian_bokml_en_5.5.0_3.0_1725219363949.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_qa_squad_v1_norwegian_bokml_en_5.5.0_3.0_1725219363949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_v3_base_qa_squad_v1_norwegian_bokml","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_v3_base_qa_squad_v1_norwegian_bokml", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_qa_squad_v1_norwegian_bokml| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|874.6 MB| + +## References + +https://huggingface.co/eanderson/mdeberta-v3-base-qa-squad_v1_nb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_qa_squad_v1_norwegian_bokml_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_qa_squad_v1_norwegian_bokml_pipeline_en.md new file mode 100644 index 00000000000000..51747440e6e8dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_qa_squad_v1_norwegian_bokml_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_v3_base_qa_squad_v1_norwegian_bokml_pipeline pipeline DeBertaForQuestionAnswering from eanderson +author: John Snow Labs +name: mdeberta_v3_base_qa_squad_v1_norwegian_bokml_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_qa_squad_v1_norwegian_bokml_pipeline` is a English model originally trained by eanderson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_qa_squad_v1_norwegian_bokml_pipeline_en_5.5.0_3.0_1725219466784.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_qa_squad_v1_norwegian_bokml_pipeline_en_5.5.0_3.0_1725219466784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_qa_squad_v1_norwegian_bokml_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_qa_squad_v1_norwegian_bokml_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_qa_squad_v1_norwegian_bokml_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|874.6 MB| + +## References + +https://huggingface.co/eanderson/mdeberta-v3-base-qa-squad_v1_nb + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_rte_1_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_rte_1_en.md new file mode 100644 index 00000000000000..1a860ff213d471 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_rte_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mdeberta_v3_base_rte_1 DeBertaForSequenceClassification from tmnam20 +author: John Snow Labs +name: mdeberta_v3_base_rte_1 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_rte_1` is a English model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_rte_1_en_5.5.0_3.0_1725223155413.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_rte_1_en_5.5.0_3.0_1725223155413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_rte_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_rte_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_rte_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|790.6 MB| + +## References + +https://huggingface.co/tmnam20/mdeberta-v3-base-rte-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_rte_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_rte_1_pipeline_en.md new file mode 100644 index 00000000000000..34014d8a5601ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_rte_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_v3_base_rte_1_pipeline pipeline DeBertaForSequenceClassification from tmnam20 +author: John Snow Labs +name: mdeberta_v3_base_rte_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_rte_1_pipeline` is a English model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_rte_1_pipeline_en_5.5.0_3.0_1725223307378.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_rte_1_pipeline_en_5.5.0_3.0_1725223307378.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_rte_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_rte_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_rte_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|790.7 MB| + +## References + +https://huggingface.co/tmnam20/mdeberta-v3-base-rte-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_sst2_10_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_sst2_10_en.md new file mode 100644 index 00000000000000..3281f1c8962992 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_sst2_10_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mdeberta_v3_base_sst2_10 DeBertaForSequenceClassification from tmnam20 +author: John Snow Labs +name: mdeberta_v3_base_sst2_10 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_sst2_10` is a English model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_sst2_10_en_5.5.0_3.0_1725210651471.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_sst2_10_en_5.5.0_3.0_1725210651471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_sst2_10","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_sst2_10", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_sst2_10| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|785.6 MB| + +## References + +https://huggingface.co/tmnam20/mdeberta-v3-base-sst2-10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_sst2_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_sst2_10_pipeline_en.md new file mode 100644 index 00000000000000..148b56f1122955 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_base_sst2_10_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_v3_base_sst2_10_pipeline pipeline DeBertaForSequenceClassification from tmnam20 +author: John Snow Labs +name: mdeberta_v3_base_sst2_10_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_sst2_10_pipeline` is a English model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_sst2_10_pipeline_en_5.5.0_3.0_1725210807914.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_sst2_10_pipeline_en_5.5.0_3.0_1725210807914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_sst2_10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_sst2_10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_sst2_10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|785.6 MB| + +## References + +https://huggingface.co/tmnam20/mdeberta-v3-base-sst2-10 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_kor_further_ner_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_kor_further_ner_en.md new file mode 100644 index 00000000000000..ac040e2277890c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_kor_further_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mdeberta_v3_kor_further_ner DeBertaForTokenClassification from dontgive99 +author: John Snow Labs +name: mdeberta_v3_kor_further_ner +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_kor_further_ner` is a English model originally trained by dontgive99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_kor_further_ner_en_5.4.2_3.0_1725196413219.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_kor_further_ner_en_5.4.2_3.0_1725196413219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_kor_further_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_kor_further_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_kor_further_ner| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|841.5 MB| + +## References + +https://huggingface.co/dontgive99/mdeberta-v3-kor-further-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_kor_further_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_kor_further_ner_pipeline_en.md new file mode 100644 index 00000000000000..e02fec5bb090ee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_kor_further_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_v3_kor_further_ner_pipeline pipeline DeBertaForTokenClassification from dontgive99 +author: John Snow Labs +name: mdeberta_v3_kor_further_ner_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_kor_further_ner_pipeline` is a English model originally trained by dontgive99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_kor_further_ner_pipeline_en_5.4.2_3.0_1725196490114.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_kor_further_ner_pipeline_en_5.4.2_3.0_1725196490114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_kor_further_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_kor_further_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_kor_further_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|841.5 MB| + +## References + +https://huggingface.co/dontgive99/mdeberta-v3-kor-further-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_ud_thai_pud_upos_pipeline_th.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_ud_thai_pud_upos_pipeline_th.md new file mode 100644 index 00000000000000..199ae79954327b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_ud_thai_pud_upos_pipeline_th.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Thai mdeberta_v3_ud_thai_pud_upos_pipeline pipeline DeBertaForTokenClassification from Pavarissy +author: John Snow Labs +name: mdeberta_v3_ud_thai_pud_upos_pipeline +date: 2024-09-01 +tags: [th, open_source, pipeline, onnx] +task: Named Entity Recognition +language: th +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_ud_thai_pud_upos_pipeline` is a Thai model originally trained by Pavarissy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_ud_thai_pud_upos_pipeline_th_5.5.0_3.0_1725233205299.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_ud_thai_pud_upos_pipeline_th_5.5.0_3.0_1725233205299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_ud_thai_pud_upos_pipeline", lang = "th") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_ud_thai_pud_upos_pipeline", lang = "th") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_ud_thai_pud_upos_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|th| +|Size:|807.4 MB| + +## References + +https://huggingface.co/Pavarissy/mdeberta-v3-ud-thai-pud-upos + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_ud_thai_pud_upos_th.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_ud_thai_pud_upos_th.md new file mode 100644 index 00000000000000..15ff0789ca5f92 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_v3_ud_thai_pud_upos_th.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Thai mdeberta_v3_ud_thai_pud_upos DeBertaForTokenClassification from Pavarissy +author: John Snow Labs +name: mdeberta_v3_ud_thai_pud_upos +date: 2024-09-01 +tags: [th, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: th +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_ud_thai_pud_upos` is a Thai model originally trained by Pavarissy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_ud_thai_pud_upos_th_5.5.0_3.0_1725233083563.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_ud_thai_pud_upos_th_5.5.0_3.0_1725233083563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_ud_thai_pud_upos","th") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_ud_thai_pud_upos", "th") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_ud_thai_pud_upos| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|th| +|Size:|807.4 MB| + +## References + +https://huggingface.co/Pavarissy/mdeberta-v3-ud-thai-pud-upos \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_vitaminc_mnli_anli_wanli_lingnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_vitaminc_mnli_anli_wanli_lingnli_pipeline_en.md new file mode 100644 index 00000000000000..70dd650fc3d297 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_vitaminc_mnli_anli_wanli_lingnli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_vitaminc_mnli_anli_wanli_lingnli_pipeline pipeline DeBertaForSequenceClassification from m0baxter +author: John Snow Labs +name: mdeberta_vitaminc_mnli_anli_wanli_lingnli_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_vitaminc_mnli_anli_wanli_lingnli_pipeline` is a English model originally trained by m0baxter. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_vitaminc_mnli_anli_wanli_lingnli_pipeline_en_5.4.2_3.0_1725183241998.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_vitaminc_mnli_anli_wanli_lingnli_pipeline_en_5.4.2_3.0_1725183241998.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_vitaminc_mnli_anli_wanli_lingnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_vitaminc_mnli_anli_wanli_lingnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_vitaminc_mnli_anli_wanli_lingnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|875.5 MB| + +## References + +https://huggingface.co/m0baxter/mdeberta-vitaminc-mnli-anli-wanli-lingnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_en.md new file mode 100644 index 00000000000000..d4c1046f2cb74d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0 DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_en_5.5.0_3.0_1725220833022.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_en_5.5.0_3.0_1725220833022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|817.8 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-xlwa-en-it_EW-TT-PE_U0_S1_Tingredient_P0.25_DROP1_mdeberta_E5_DEV95.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_pipeline_en.md new file mode 100644 index 00000000000000..f4974dc4e79e18 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_pipeline pipeline DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_pipeline` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_pipeline_en_5.5.0_3.0_1725220949436.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_pipeline_en_5.5.0_3.0_1725220949436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e5_dev95_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|817.8 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-xlwa-en-it_EW-TT-PE_U0_S1_Tingredient_P0.25_DROP1_mdeberta_E5_DEV95.0 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_en.md new file mode 100644 index 00000000000000..7457e54f5bc739 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0 DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_en_5.5.0_3.0_1725220656355.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_en_5.5.0_3.0_1725220656355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|817.9 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-xlwa-en-it_EW-TT-PE_U0_S1_Tingredient_P1_DROP1_mdeberta_E5_DEV96.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_pipeline_en.md new file mode 100644 index 00000000000000..28bcbb2ff499f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_pipeline pipeline DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_pipeline` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_pipeline_en_5.5.0_3.0_1725220772762.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_pipeline_en_5.5.0_3.0_1725220772762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p1_drop1_mdeberta_e5_dev96_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|817.9 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-xlwa-en-it_EW-TT-PE_U0_S1_Tingredient_P1_DROP1_mdeberta_E5_DEV96.0 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_en.md new file mode 100644 index 00000000000000..dfa9da3cc7c440 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0 DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_en_5.5.0_3.0_1725220324367.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_en_5.5.0_3.0_1725220324367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|819.0 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-xlwa-en-it_mdeberta_EW-TT-PE_U0_S1_DROP1_E8_DEV92.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_pipeline_en.md new file mode 100644 index 00000000000000..e2e603351605ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_pipeline pipeline DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_pipeline` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_pipeline_en_5.5.0_3.0_1725220438920.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_pipeline_en_5.5.0_3.0_1725220438920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_xlwa_english_italian_mdeberta_ew_tatar_pe_u0_s1_drop1_e8_dev92_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|819.0 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-xlwa-en-it_mdeberta_EW-TT-PE_U0_S1_DROP1_E8_DEV92.0 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdebertav3_subjectivity_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mdebertav3_subjectivity_english_pipeline_en.md new file mode 100644 index 00000000000000..33d61eef983ca1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdebertav3_subjectivity_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdebertav3_subjectivity_english_pipeline pipeline DeBertaForSequenceClassification from GroNLP +author: John Snow Labs +name: mdebertav3_subjectivity_english_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdebertav3_subjectivity_english_pipeline` is a English model originally trained by GroNLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdebertav3_subjectivity_english_pipeline_en_5.4.2_3.0_1725182720942.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdebertav3_subjectivity_english_pipeline_en_5.4.2_3.0_1725182720942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdebertav3_subjectivity_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdebertav3_subjectivity_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdebertav3_subjectivity_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|809.7 MB| + +## References + +https://huggingface.co/GroNLP/mdebertav3-subjectivity-english + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdebertav3_subjectivity_german_de.md b/docs/_posts/ahmedlone127/2024-09-01-mdebertav3_subjectivity_german_de.md new file mode 100644 index 00000000000000..78d875bc3cb696 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdebertav3_subjectivity_german_de.md @@ -0,0 +1,94 @@ +--- +layout: model +title: German mdebertav3_subjectivity_german DeBertaForSequenceClassification from GroNLP +author: John Snow Labs +name: mdebertav3_subjectivity_german +date: 2024-09-01 +tags: [de, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdebertav3_subjectivity_german` is a German model originally trained by GroNLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdebertav3_subjectivity_german_de_5.5.0_3.0_1725208775647.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdebertav3_subjectivity_german_de_5.5.0_3.0_1725208775647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdebertav3_subjectivity_german","de") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdebertav3_subjectivity_german", "de") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdebertav3_subjectivity_german| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|860.3 MB| + +## References + +https://huggingface.co/GroNLP/mdebertav3-subjectivity-german \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdebertav3_subjectivity_german_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-01-mdebertav3_subjectivity_german_pipeline_de.md new file mode 100644 index 00000000000000..9fa0efdd67c3ea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdebertav3_subjectivity_german_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German mdebertav3_subjectivity_german_pipeline pipeline DeBertaForSequenceClassification from GroNLP +author: John Snow Labs +name: mdebertav3_subjectivity_german_pipeline +date: 2024-09-01 +tags: [de, open_source, pipeline, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdebertav3_subjectivity_german_pipeline` is a German model originally trained by GroNLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdebertav3_subjectivity_german_pipeline_de_5.5.0_3.0_1725208838891.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdebertav3_subjectivity_german_pipeline_de_5.5.0_3.0_1725208838891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdebertav3_subjectivity_german_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdebertav3_subjectivity_german_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdebertav3_subjectivity_german_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|860.3 MB| + +## References + +https://huggingface.co/GroNLP/mdebertav3-subjectivity-german + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mdebertav3_subjectivity_multilingual_xx.md b/docs/_posts/ahmedlone127/2024-09-01-mdebertav3_subjectivity_multilingual_xx.md new file mode 100644 index 00000000000000..50666f60521591 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mdebertav3_subjectivity_multilingual_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual mdebertav3_subjectivity_multilingual DeBertaForSequenceClassification from GroNLP +author: John Snow Labs +name: mdebertav3_subjectivity_multilingual +date: 2024-09-01 +tags: [xx, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdebertav3_subjectivity_multilingual` is a Multilingual model originally trained by GroNLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdebertav3_subjectivity_multilingual_xx_5.4.2_3.0_1725182797401.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdebertav3_subjectivity_multilingual_xx_5.4.2_3.0_1725182797401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdebertav3_subjectivity_multilingual","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdebertav3_subjectivity_multilingual", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdebertav3_subjectivity_multilingual| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|864.5 MB| + +## References + +https://huggingface.co/GroNLP/mdebertav3-subjectivity-multilingual \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-medcpt_cross_encoder_en.md b/docs/_posts/ahmedlone127/2024-09-01-medcpt_cross_encoder_en.md new file mode 100644 index 00000000000000..d8bb894ce6b53d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-medcpt_cross_encoder_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English medcpt_cross_encoder BertForSequenceClassification from ncbi +author: John Snow Labs +name: medcpt_cross_encoder +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medcpt_cross_encoder` is a English model originally trained by ncbi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medcpt_cross_encoder_en_5.4.2_3.0_1725204520079.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medcpt_cross_encoder_en_5.4.2_3.0_1725204520079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("medcpt_cross_encoder","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("medcpt_cross_encoder", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|medcpt_cross_encoder| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|410.4 MB| + +## References + +https://huggingface.co/ncbi/MedCPT-Cross-Encoder \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-medcpt_cross_encoder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-medcpt_cross_encoder_pipeline_en.md new file mode 100644 index 00000000000000..cc77ffc1103010 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-medcpt_cross_encoder_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English medcpt_cross_encoder_pipeline pipeline BertForSequenceClassification from ncbi +author: John Snow Labs +name: medcpt_cross_encoder_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medcpt_cross_encoder_pipeline` is a English model originally trained by ncbi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medcpt_cross_encoder_pipeline_en_5.4.2_3.0_1725204545490.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medcpt_cross_encoder_pipeline_en_5.4.2_3.0_1725204545490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("medcpt_cross_encoder_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("medcpt_cross_encoder_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|medcpt_cross_encoder_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|410.4 MB| + +## References + +https://huggingface.co/ncbi/MedCPT-Cross-Encoder + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-memo_model_4200_en.md b/docs/_posts/ahmedlone127/2024-09-01-memo_model_4200_en.md new file mode 100644 index 00000000000000..abe2a50fc41dcc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-memo_model_4200_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English memo_model_4200 XlmRoBertaEmbeddings from yemen2016 +author: John Snow Labs +name: memo_model_4200 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_model_4200` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_model_4200_en_5.4.2_3.0_1725177211540.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_model_4200_en_5.4.2_3.0_1725177211540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("memo_model_4200","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("memo_model_4200","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|memo_model_4200| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/memo_model_4200 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-memo_model_4200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-memo_model_4200_pipeline_en.md new file mode 100644 index 00000000000000..afb3356da37ef2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-memo_model_4200_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English memo_model_4200_pipeline pipeline XlmRoBertaEmbeddings from yemen2016 +author: John Snow Labs +name: memo_model_4200_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_model_4200_pipeline` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_model_4200_pipeline_en_5.4.2_3.0_1725177265370.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_model_4200_pipeline_en_5.4.2_3.0_1725177265370.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("memo_model_4200_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("memo_model_4200_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|memo_model_4200_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/memo_model_4200 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-merged_model_distil_bert_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-merged_model_distil_bert_finetuned_ner_pipeline_en.md new file mode 100644 index 00000000000000..b5e83caceb65d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-merged_model_distil_bert_finetuned_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English merged_model_distil_bert_finetuned_ner_pipeline pipeline DistilBertForTokenClassification from sahillihas +author: John Snow Labs +name: merged_model_distil_bert_finetuned_ner_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_model_distil_bert_finetuned_ner_pipeline` is a English model originally trained by sahillihas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_model_distil_bert_finetuned_ner_pipeline_en_5.4.2_3.0_1725160595299.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_model_distil_bert_finetuned_ner_pipeline_en_5.4.2_3.0_1725160595299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("merged_model_distil_bert_finetuned_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("merged_model_distil_bert_finetuned_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|merged_model_distil_bert_finetuned_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/sahillihas/merged-model-distil-bert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_en.md b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_en.md new file mode 100644 index 00000000000000..0ff832d077166d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English microsoft_deberta_v3_large_cls_sst2_ghatgetanuj DeBertaForSequenceClassification from ghatgetanuj +author: John Snow Labs +name: microsoft_deberta_v3_large_cls_sst2_ghatgetanuj +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_cls_sst2_ghatgetanuj` is a English model originally trained by ghatgetanuj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_en_5.5.0_3.0_1725223397966.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_en_5.5.0_3.0_1725223397966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("microsoft_deberta_v3_large_cls_sst2_ghatgetanuj","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("microsoft_deberta_v3_large_cls_sst2_ghatgetanuj", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|microsoft_deberta_v3_large_cls_sst2_ghatgetanuj| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/ghatgetanuj/microsoft-deberta-v3-large_cls_sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_pipeline_en.md new file mode 100644 index 00000000000000..d3a26d9200185f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_pipeline pipeline DeBertaForSequenceClassification from ghatgetanuj +author: John Snow Labs +name: microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_pipeline` is a English model originally trained by ghatgetanuj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_pipeline_en_5.5.0_3.0_1725223489252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_pipeline_en_5.5.0_3.0_1725223489252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|microsoft_deberta_v3_large_cls_sst2_ghatgetanuj_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/ghatgetanuj/microsoft-deberta-v3-large_cls_sst2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_en.md b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_en.md new file mode 100644 index 00000000000000..3849910bb94f19 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon DeBertaForTokenClassification from Yanis +author: John Snow Labs +name: microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon` is a English model originally trained by Yanis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_en_5.4.2_3.0_1725196694742.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_en_5.4.2_3.0_1725196694742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-breast-without-castellon \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_pipeline_en.md new file mode 100644 index 00000000000000..a4ccc1d621f483 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_pipeline pipeline DeBertaForTokenClassification from Yanis +author: John Snow Labs +name: microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_pipeline` is a English model originally trained by Yanis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_pipeline_en_5.4.2_3.0_1725196780917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_pipeline_en_5.4.2_3.0_1725196780917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-breast-without-castellon + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_en.md b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_en.md new file mode 100644 index 00000000000000..e9746b19747e2e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English microsoft_deberta_v3_large_ner_conll2003 DeBertaForTokenClassification from Gladiator +author: John Snow Labs +name: microsoft_deberta_v3_large_ner_conll2003 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003` is a English model originally trained by Gladiator. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_en_5.4.2_3.0_1725196886398.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_en_5.4.2_3.0_1725196886398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|microsoft_deberta_v3_large_ner_conll2003| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/Gladiator/microsoft-deberta-v3-large_ner_conll2003 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_en.md b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_en.md new file mode 100644 index 00000000000000..b6a25ea194c06e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1 DeBertaForTokenClassification from Yanis +author: John Snow Labs +name: microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1` is a English model originally trained by Yanis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_en_5.4.2_3.0_1725197511734.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_en_5.4.2_3.0_1725197511734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-inca-la_fe-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_pipeline_en.md new file mode 100644 index 00000000000000..4ea5b9d5122c2b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_pipeline pipeline DeBertaForTokenClassification from Yanis +author: John Snow Labs +name: microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_pipeline` is a English model originally trained by Yanis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_pipeline_en_5.4.2_3.0_1725197609434.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_pipeline_en_5.4.2_3.0_1725197609434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-inca-la_fe-v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_en.md b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_en.md new file mode 100644 index 00000000000000..aa928c964b840a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2 DeBertaForTokenClassification from Yanis +author: John Snow Labs +name: microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2` is a English model originally trained by Yanis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_en_5.4.2_3.0_1725196195589.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_en_5.4.2_3.0_1725196195589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-inca-la_fe-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_pipeline_en.md new file mode 100644 index 00000000000000..0e0223dedec2d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_pipeline pipeline DeBertaForTokenClassification from Yanis +author: John Snow Labs +name: microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_pipeline` is a English model originally trained by Yanis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_pipeline_en_5.4.2_3.0_1725196286249.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_pipeline_en_5.4.2_3.0_1725196286249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|microsoft_deberta_v3_large_ner_conll2003_inca_latin_fe_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-inca-la_fe-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_pipeline_en.md new file mode 100644 index 00000000000000..4cf9a4ced6356a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_large_ner_conll2003_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English microsoft_deberta_v3_large_ner_conll2003_pipeline pipeline DeBertaForTokenClassification from Gladiator +author: John Snow Labs +name: microsoft_deberta_v3_large_ner_conll2003_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_pipeline` is a English model originally trained by Gladiator. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_pipeline_en_5.4.2_3.0_1725196977039.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_pipeline_en_5.4.2_3.0_1725196977039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|microsoft_deberta_v3_large_ner_conll2003_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/Gladiator/microsoft-deberta-v3-large_ner_conll2003 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_small_1024_en.md b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_small_1024_en.md new file mode 100644 index 00000000000000..45ed87755aae55 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_small_1024_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English microsoft_deberta_v3_small_1024 DeBertaForTokenClassification from abdullah +author: John Snow Labs +name: microsoft_deberta_v3_small_1024 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_small_1024` is a English model originally trained by abdullah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_small_1024_en_5.5.0_3.0_1725233563310.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_small_1024_en_5.5.0_3.0_1725233563310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_small_1024","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_small_1024", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|microsoft_deberta_v3_small_1024| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|462.0 MB| + +## References + +https://huggingface.co/abdullah/microsoft-deberta-v3-small-1024 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_small_1024_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_small_1024_pipeline_en.md new file mode 100644 index 00000000000000..74b270e3fb0f6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-microsoft_deberta_v3_small_1024_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English microsoft_deberta_v3_small_1024_pipeline pipeline DeBertaForTokenClassification from abdullah +author: John Snow Labs +name: microsoft_deberta_v3_small_1024_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_small_1024_pipeline` is a English model originally trained by abdullah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_small_1024_pipeline_en_5.5.0_3.0_1725233609569.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_small_1024_pipeline_en_5.5.0_3.0_1725233609569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("microsoft_deberta_v3_small_1024_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("microsoft_deberta_v3_small_1024_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|microsoft_deberta_v3_small_1024_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|462.0 MB| + +## References + +https://huggingface.co/abdullah/microsoft-deberta-v3-small-1024 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mimic_pubmed_deberta_small_en.md b/docs/_posts/ahmedlone127/2024-09-01-mimic_pubmed_deberta_small_en.md new file mode 100644 index 00000000000000..fa873eca909d08 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mimic_pubmed_deberta_small_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mimic_pubmed_deberta_small DeBertaEmbeddings from austin +author: John Snow Labs +name: mimic_pubmed_deberta_small +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mimic_pubmed_deberta_small` is a English model originally trained by austin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mimic_pubmed_deberta_small_en_5.5.0_3.0_1725217689962.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mimic_pubmed_deberta_small_en_5.5.0_3.0_1725217689962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("mimic_pubmed_deberta_small","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("mimic_pubmed_deberta_small","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mimic_pubmed_deberta_small| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|529.6 MB| + +## References + +https://huggingface.co/austin/mimic-pubmed-deberta-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mimic_pubmed_deberta_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mimic_pubmed_deberta_small_pipeline_en.md new file mode 100644 index 00000000000000..997560111e21d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mimic_pubmed_deberta_small_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mimic_pubmed_deberta_small_pipeline pipeline DeBertaEmbeddings from austin +author: John Snow Labs +name: mimic_pubmed_deberta_small_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mimic_pubmed_deberta_small_pipeline` is a English model originally trained by austin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mimic_pubmed_deberta_small_pipeline_en_5.5.0_3.0_1725217718323.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mimic_pubmed_deberta_small_pipeline_en_5.5.0_3.0_1725217718323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mimic_pubmed_deberta_small_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mimic_pubmed_deberta_small_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mimic_pubmed_deberta_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|529.6 MB| + +## References + +https://huggingface.co/austin/mimic-pubmed-deberta-small + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-minilm_l12_h384_uncased_nvidia_aegis_ai_safety_en.md b/docs/_posts/ahmedlone127/2024-09-01-minilm_l12_h384_uncased_nvidia_aegis_ai_safety_en.md new file mode 100644 index 00000000000000..d1e8aa9558eb69 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-minilm_l12_h384_uncased_nvidia_aegis_ai_safety_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English minilm_l12_h384_uncased_nvidia_aegis_ai_safety BertForSequenceClassification from AC +author: John Snow Labs +name: minilm_l12_h384_uncased_nvidia_aegis_ai_safety +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`minilm_l12_h384_uncased_nvidia_aegis_ai_safety` is a English model originally trained by AC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/minilm_l12_h384_uncased_nvidia_aegis_ai_safety_en_5.4.2_3.0_1725205065167.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/minilm_l12_h384_uncased_nvidia_aegis_ai_safety_en_5.4.2_3.0_1725205065167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("minilm_l12_h384_uncased_nvidia_aegis_ai_safety","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("minilm_l12_h384_uncased_nvidia_aegis_ai_safety", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|minilm_l12_h384_uncased_nvidia_aegis_ai_safety| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|114.0 MB| + +## References + +https://huggingface.co/AC/MiniLM-L12-H384-uncased_Nvidia-Aegis-AI-Safety \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-minilm_l12_h384_uncased_nvidia_aegis_ai_safety_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-minilm_l12_h384_uncased_nvidia_aegis_ai_safety_pipeline_en.md new file mode 100644 index 00000000000000..9aff71710708ee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-minilm_l12_h384_uncased_nvidia_aegis_ai_safety_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English minilm_l12_h384_uncased_nvidia_aegis_ai_safety_pipeline pipeline BertForSequenceClassification from AC +author: John Snow Labs +name: minilm_l12_h384_uncased_nvidia_aegis_ai_safety_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`minilm_l12_h384_uncased_nvidia_aegis_ai_safety_pipeline` is a English model originally trained by AC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/minilm_l12_h384_uncased_nvidia_aegis_ai_safety_pipeline_en_5.4.2_3.0_1725205074666.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/minilm_l12_h384_uncased_nvidia_aegis_ai_safety_pipeline_en_5.4.2_3.0_1725205074666.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("minilm_l12_h384_uncased_nvidia_aegis_ai_safety_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("minilm_l12_h384_uncased_nvidia_aegis_ai_safety_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|minilm_l12_h384_uncased_nvidia_aegis_ai_safety_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|114.1 MB| + +## References + +https://huggingface.co/AC/MiniLM-L12-H384-uncased_Nvidia-Aegis-AI-Safety + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-minilmv2_l6_h384_distilled_from_roberta_large_en.md b/docs/_posts/ahmedlone127/2024-09-01-minilmv2_l6_h384_distilled_from_roberta_large_en.md new file mode 100644 index 00000000000000..c3a7586a8c7434 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-minilmv2_l6_h384_distilled_from_roberta_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English minilmv2_l6_h384_distilled_from_roberta_large RoBertaEmbeddings from nreimers +author: John Snow Labs +name: minilmv2_l6_h384_distilled_from_roberta_large +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`minilmv2_l6_h384_distilled_from_roberta_large` is a English model originally trained by nreimers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/minilmv2_l6_h384_distilled_from_roberta_large_en_5.4.2_3.0_1725186872804.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/minilmv2_l6_h384_distilled_from_roberta_large_en_5.4.2_3.0_1725186872804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("minilmv2_l6_h384_distilled_from_roberta_large","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("minilmv2_l6_h384_distilled_from_roberta_large","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|minilmv2_l6_h384_distilled_from_roberta_large| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|73.1 MB| + +## References + +https://huggingface.co/nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-minilmv2_l6_h384_distilled_from_roberta_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-minilmv2_l6_h384_distilled_from_roberta_large_pipeline_en.md new file mode 100644 index 00000000000000..d7e8a18ac783cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-minilmv2_l6_h384_distilled_from_roberta_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English minilmv2_l6_h384_distilled_from_roberta_large_pipeline pipeline RoBertaEmbeddings from nreimers +author: John Snow Labs +name: minilmv2_l6_h384_distilled_from_roberta_large_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`minilmv2_l6_h384_distilled_from_roberta_large_pipeline` is a English model originally trained by nreimers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/minilmv2_l6_h384_distilled_from_roberta_large_pipeline_en_5.4.2_3.0_1725186894449.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/minilmv2_l6_h384_distilled_from_roberta_large_pipeline_en_5.4.2_3.0_1725186894449.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("minilmv2_l6_h384_distilled_from_roberta_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("minilmv2_l6_h384_distilled_from_roberta_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|minilmv2_l6_h384_distilled_from_roberta_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|73.1 MB| + +## References + +https://huggingface.co/nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-minilmv2_l6_h768_distilled_from_roberta_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-minilmv2_l6_h768_distilled_from_roberta_large_pipeline_en.md new file mode 100644 index 00000000000000..4eccf1e9869959 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-minilmv2_l6_h768_distilled_from_roberta_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English minilmv2_l6_h768_distilled_from_roberta_large_pipeline pipeline RoBertaEmbeddings from nreimers +author: John Snow Labs +name: minilmv2_l6_h768_distilled_from_roberta_large_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`minilmv2_l6_h768_distilled_from_roberta_large_pipeline` is a English model originally trained by nreimers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/minilmv2_l6_h768_distilled_from_roberta_large_pipeline_en_5.4.2_3.0_1725165827299.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/minilmv2_l6_h768_distilled_from_roberta_large_pipeline_en_5.4.2_3.0_1725165827299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("minilmv2_l6_h768_distilled_from_roberta_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("minilmv2_l6_h768_distilled_from_roberta_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|minilmv2_l6_h768_distilled_from_roberta_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|196.0 MB| + +## References + +https://huggingface.co/nreimers/MiniLMv2-L6-H768-distilled-from-RoBERTa-Large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_english_msmarco_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_english_msmarco_pipeline_en.md new file mode 100644 index 00000000000000..cba8d9828f3c5d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_english_msmarco_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mminilm_l6_v2_english_msmarco_pipeline pipeline XlmRoBertaForSequenceClassification from unicamp-dl +author: John Snow Labs +name: mminilm_l6_v2_english_msmarco_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilm_l6_v2_english_msmarco_pipeline` is a English model originally trained by unicamp-dl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_english_msmarco_pipeline_en_5.4.2_3.0_1725189927936.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_english_msmarco_pipeline_en_5.4.2_3.0_1725189927936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mminilm_l6_v2_english_msmarco_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mminilm_l6_v2_english_msmarco_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mminilm_l6_v2_english_msmarco_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|338.6 MB| + +## References + +https://huggingface.co/unicamp-dl/mMiniLM-L6-v2-en-msmarco + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_portuguese_msmarco_v1_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_portuguese_msmarco_v1_pipeline_pt.md new file mode 100644 index 00000000000000..45beb38c0217e8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_portuguese_msmarco_v1_pipeline_pt.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Portuguese mminilm_l6_v2_portuguese_msmarco_v1_pipeline pipeline XlmRoBertaForSequenceClassification from unicamp-dl +author: John Snow Labs +name: mminilm_l6_v2_portuguese_msmarco_v1_pipeline +date: 2024-09-01 +tags: [pt, open_source, pipeline, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilm_l6_v2_portuguese_msmarco_v1_pipeline` is a Portuguese model originally trained by unicamp-dl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_portuguese_msmarco_v1_pipeline_pt_5.4.2_3.0_1725190582165.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_portuguese_msmarco_v1_pipeline_pt_5.4.2_3.0_1725190582165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mminilm_l6_v2_portuguese_msmarco_v1_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mminilm_l6_v2_portuguese_msmarco_v1_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mminilm_l6_v2_portuguese_msmarco_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|342.9 MB| + +## References + +https://huggingface.co/unicamp-dl/mMiniLM-L6-v2-pt-msmarco-v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_portuguese_msmarco_v1_pt.md b/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_portuguese_msmarco_v1_pt.md new file mode 100644 index 00000000000000..1b0c6c4bdfb4f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_portuguese_msmarco_v1_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese mminilm_l6_v2_portuguese_msmarco_v1 XlmRoBertaForSequenceClassification from unicamp-dl +author: John Snow Labs +name: mminilm_l6_v2_portuguese_msmarco_v1 +date: 2024-09-01 +tags: [pt, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: pt +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilm_l6_v2_portuguese_msmarco_v1` is a Portuguese model originally trained by unicamp-dl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_portuguese_msmarco_v1_pt_5.4.2_3.0_1725190561090.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_portuguese_msmarco_v1_pt_5.4.2_3.0_1725190561090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("mminilm_l6_v2_portuguese_msmarco_v1","pt") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("mminilm_l6_v2_portuguese_msmarco_v1", "pt") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mminilm_l6_v2_portuguese_msmarco_v1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|342.9 MB| + +## References + +https://huggingface.co/unicamp-dl/mMiniLM-L6-v2-pt-msmarco-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_portuguese_v2_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_portuguese_v2_pipeline_pt.md new file mode 100644 index 00000000000000..c6fa5b2baf9779 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_portuguese_v2_pipeline_pt.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Portuguese mminilm_l6_v2_portuguese_v2_pipeline pipeline XlmRoBertaForSequenceClassification from unicamp-dl +author: John Snow Labs +name: mminilm_l6_v2_portuguese_v2_pipeline +date: 2024-09-01 +tags: [pt, open_source, pipeline, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilm_l6_v2_portuguese_v2_pipeline` is a Portuguese model originally trained by unicamp-dl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_portuguese_v2_pipeline_pt_5.4.2_3.0_1725190364205.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_portuguese_v2_pipeline_pt_5.4.2_3.0_1725190364205.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mminilm_l6_v2_portuguese_v2_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mminilm_l6_v2_portuguese_v2_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mminilm_l6_v2_portuguese_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|339.7 MB| + +## References + +https://huggingface.co/unicamp-dl/mMiniLM-L6-v2-pt-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_portuguese_v2_pt.md b/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_portuguese_v2_pt.md new file mode 100644 index 00000000000000..8c50d8bfbc09eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mminilm_l6_v2_portuguese_v2_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese mminilm_l6_v2_portuguese_v2 XlmRoBertaForSequenceClassification from unicamp-dl +author: John Snow Labs +name: mminilm_l6_v2_portuguese_v2 +date: 2024-09-01 +tags: [pt, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: pt +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilm_l6_v2_portuguese_v2` is a Portuguese model originally trained by unicamp-dl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_portuguese_v2_pt_5.4.2_3.0_1725190343147.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_portuguese_v2_pt_5.4.2_3.0_1725190343147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("mminilm_l6_v2_portuguese_v2","pt") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("mminilm_l6_v2_portuguese_v2", "pt") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mminilm_l6_v2_portuguese_v2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|339.7 MB| + +## References + +https://huggingface.co/unicamp-dl/mMiniLM-L6-v2-pt-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mobilebert_uncased_mnli_typeform_en.md b/docs/_posts/ahmedlone127/2024-09-01-mobilebert_uncased_mnli_typeform_en.md new file mode 100644 index 00000000000000..a767a5b154e296 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mobilebert_uncased_mnli_typeform_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mobilebert_uncased_mnli_typeform BertForZeroShotClassification from typeform +author: John Snow Labs +name: mobilebert_uncased_mnli_typeform +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mobilebert_uncased_mnli_typeform` is a English model originally trained by typeform. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_mnli_typeform_en_5.4.2_3.0_1725201533546.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_mnli_typeform_en_5.4.2_3.0_1725201533546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("mobilebert_uncased_mnli_typeform","en") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("mobilebert_uncased_mnli_typeform", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mobilebert_uncased_mnli_typeform| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|92.5 MB| + +## References + +https://huggingface.co/typeform/mobilebert-uncased-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mobilebert_uncased_mnli_typeform_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mobilebert_uncased_mnli_typeform_pipeline_en.md new file mode 100644 index 00000000000000..9e4639acb5f6d0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mobilebert_uncased_mnli_typeform_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mobilebert_uncased_mnli_typeform_pipeline pipeline BertForZeroShotClassification from typeform +author: John Snow Labs +name: mobilebert_uncased_mnli_typeform_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mobilebert_uncased_mnli_typeform_pipeline` is a English model originally trained by typeform. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_mnli_typeform_pipeline_en_5.4.2_3.0_1725201538514.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_mnli_typeform_pipeline_en_5.4.2_3.0_1725201538514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mobilebert_uncased_mnli_typeform_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mobilebert_uncased_mnli_typeform_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mobilebert_uncased_mnli_typeform_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|92.6 MB| + +## References + +https://huggingface.co/typeform/mobilebert-uncased-mnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mobilebert_uncased_squad_v2_csarron_en.md b/docs/_posts/ahmedlone127/2024-09-01-mobilebert_uncased_squad_v2_csarron_en.md new file mode 100644 index 00000000000000..eeb697920d31c3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mobilebert_uncased_squad_v2_csarron_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mobilebert_uncased_squad_v2_csarron BertForQuestionAnswering from csarron +author: John Snow Labs +name: mobilebert_uncased_squad_v2_csarron +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mobilebert_uncased_squad_v2_csarron` is a English model originally trained by csarron. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_squad_v2_csarron_en_5.4.2_3.0_1725185116981.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_squad_v2_csarron_en_5.4.2_3.0_1725185116981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("mobilebert_uncased_squad_v2_csarron","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("mobilebert_uncased_squad_v2_csarron", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mobilebert_uncased_squad_v2_csarron| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|92.5 MB| + +## References + +https://huggingface.co/csarron/mobilebert-uncased-squad-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-model_classification_en.md b/docs/_posts/ahmedlone127/2024-09-01-model_classification_en.md new file mode 100644 index 00000000000000..4e6d782908b53d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-model_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English model_classification DistilBertForSequenceClassification from arjun80095 +author: John Snow Labs +name: model_classification +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_classification` is a English model originally trained by arjun80095. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_classification_en_5.5.0_3.0_1725213725134.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_classification_en_5.5.0_3.0_1725213725134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("model_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("model_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/arjun80095/model_classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-model_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-model_classification_pipeline_en.md new file mode 100644 index 00000000000000..981b3d0e6f4118 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-model_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English model_classification_pipeline pipeline DistilBertForSequenceClassification from arjun80095 +author: John Snow Labs +name: model_classification_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_classification_pipeline` is a English model originally trained by arjun80095. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_classification_pipeline_en_5.5.0_3.0_1725213744536.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_classification_pipeline_en_5.5.0_3.0_1725213744536.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("model_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("model_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/arjun80095/model_classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-model_deberta3base_1024_token_classification_en.md b/docs/_posts/ahmedlone127/2024-09-01-model_deberta3base_1024_token_classification_en.md new file mode 100644 index 00000000000000..e5304a3cdafd1b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-model_deberta3base_1024_token_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English model_deberta3base_1024_token_classification DeBertaForTokenClassification from adhi29 +author: John Snow Labs +name: model_deberta3base_1024_token_classification +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_deberta3base_1024_token_classification` is a English model originally trained by adhi29. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_deberta3base_1024_token_classification_en_5.4.2_3.0_1725195683176.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_deberta3base_1024_token_classification_en_5.4.2_3.0_1725195683176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("model_deberta3base_1024_token_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("model_deberta3base_1024_token_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_deberta3base_1024_token_classification| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|620.0 MB| + +## References + +https://huggingface.co/adhi29/model_deberta3base_1024_token_classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-model_deberta3base_1024_token_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-model_deberta3base_1024_token_classification_pipeline_en.md new file mode 100644 index 00000000000000..368596bda6334d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-model_deberta3base_1024_token_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English model_deberta3base_1024_token_classification_pipeline pipeline DeBertaForTokenClassification from adhi29 +author: John Snow Labs +name: model_deberta3base_1024_token_classification_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_deberta3base_1024_token_classification_pipeline` is a English model originally trained by adhi29. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_deberta3base_1024_token_classification_pipeline_en_5.4.2_3.0_1725195738054.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_deberta3base_1024_token_classification_pipeline_en_5.4.2_3.0_1725195738054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("model_deberta3base_1024_token_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("model_deberta3base_1024_token_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_deberta3base_1024_token_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|620.0 MB| + +## References + +https://huggingface.co/adhi29/model_deberta3base_1024_token_classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-model_indicbert_small_en.md b/docs/_posts/ahmedlone127/2024-09-01-model_indicbert_small_en.md new file mode 100644 index 00000000000000..8491296a9f6833 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-model_indicbert_small_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English model_indicbert_small AlbertForTokenClassification from ashnadua01 +author: John Snow Labs +name: model_indicbert_small +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, albert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_indicbert_small` is a English model originally trained by ashnadua01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_indicbert_small_en_5.4.2_3.0_1725203628158.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_indicbert_small_en_5.4.2_3.0_1725203628158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = AlbertForTokenClassification.pretrained("model_indicbert_small","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = AlbertForTokenClassification.pretrained("model_indicbert_small", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_indicbert_small| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|125.6 MB| + +## References + +https://huggingface.co/ashnadua01/model_indicbert_small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-model_indicbert_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-model_indicbert_small_pipeline_en.md new file mode 100644 index 00000000000000..e77b22f4208bbe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-model_indicbert_small_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English model_indicbert_small_pipeline pipeline AlbertForTokenClassification from ashnadua01 +author: John Snow Labs +name: model_indicbert_small_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_indicbert_small_pipeline` is a English model originally trained by ashnadua01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_indicbert_small_pipeline_en_5.4.2_3.0_1725203634298.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_indicbert_small_pipeline_en_5.4.2_3.0_1725203634298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("model_indicbert_small_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("model_indicbert_small_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_indicbert_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|125.6 MB| + +## References + +https://huggingface.co/ashnadua01/model_indicbert_small + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-monet_en.md b/docs/_posts/ahmedlone127/2024-09-01-monet_en.md new file mode 100644 index 00000000000000..d7cc53b2d19e8c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-monet_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English monet CLIPForZeroShotClassification from suinleelab +author: John Snow Labs +name: monet +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`monet` is a English model originally trained by suinleelab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/monet_en_5.5.0_3.0_1725225946904.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/monet_en_5.5.0_3.0_1725225946904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("monet","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("monet","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|monet| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/suinleelab/monet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-monet_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-monet_pipeline_en.md new file mode 100644 index 00000000000000..c1876c081f3457 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-monet_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English monet_pipeline pipeline CLIPForZeroShotClassification from suinleelab +author: John Snow Labs +name: monet_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`monet_pipeline` is a English model originally trained by suinleelab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/monet_pipeline_en_5.5.0_3.0_1725226208320.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/monet_pipeline_en_5.5.0_3.0_1725226208320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("monet_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("monet_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|monet_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/suinleelab/monet + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mongolian_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mongolian_roberta_base_pipeline_en.md new file mode 100644 index 00000000000000..11ff6240303fae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mongolian_roberta_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mongolian_roberta_base_pipeline pipeline RoBertaEmbeddings from bayartsogt +author: John Snow Labs +name: mongolian_roberta_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mongolian_roberta_base_pipeline` is a English model originally trained by bayartsogt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mongolian_roberta_base_pipeline_en_5.4.2_3.0_1725186070730.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mongolian_roberta_base_pipeline_en_5.4.2_3.0_1725186070730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mongolian_roberta_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mongolian_roberta_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mongolian_roberta_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.7 MB| + +## References + +https://huggingface.co/bayartsogt/mongolian-roberta-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-movie_review_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-01-movie_review_classifier_en.md new file mode 100644 index 00000000000000..969cd7f3c6f2ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-movie_review_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English movie_review_classifier DistilBertForSequenceClassification from derek-harnett +author: John Snow Labs +name: movie_review_classifier +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_review_classifier` is a English model originally trained by derek-harnett. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_review_classifier_en_5.5.0_3.0_1725214045707.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_review_classifier_en_5.5.0_3.0_1725214045707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("movie_review_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("movie_review_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|movie_review_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/derek-harnett/movie-review-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-movie_review_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-movie_review_classifier_pipeline_en.md new file mode 100644 index 00000000000000..51c980ede495b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-movie_review_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English movie_review_classifier_pipeline pipeline DistilBertForSequenceClassification from derek-harnett +author: John Snow Labs +name: movie_review_classifier_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_review_classifier_pipeline` is a English model originally trained by derek-harnett. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_review_classifier_pipeline_en_5.5.0_3.0_1725214059593.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_review_classifier_pipeline_en_5.5.0_3.0_1725214059593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("movie_review_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("movie_review_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|movie_review_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/derek-harnett/movie-review-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-movie_sentiment_trainer_en.md b/docs/_posts/ahmedlone127/2024-09-01-movie_sentiment_trainer_en.md new file mode 100644 index 00000000000000..d9a84ae0a186fa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-movie_sentiment_trainer_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English movie_sentiment_trainer RoBertaForSequenceClassification from Sonny4Sonnix +author: John Snow Labs +name: movie_sentiment_trainer +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_sentiment_trainer` is a English model originally trained by Sonny4Sonnix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_sentiment_trainer_en_5.5.0_3.0_1725211722615.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_sentiment_trainer_en_5.5.0_3.0_1725211722615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("movie_sentiment_trainer","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("movie_sentiment_trainer", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|movie_sentiment_trainer| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.2 MB| + +## References + +https://huggingface.co/Sonny4Sonnix/movie_sentiment_trainer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-movie_sentiment_trainer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-movie_sentiment_trainer_pipeline_en.md new file mode 100644 index 00000000000000..742ec8bd04d2a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-movie_sentiment_trainer_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English movie_sentiment_trainer_pipeline pipeline RoBertaForSequenceClassification from Sonny4Sonnix +author: John Snow Labs +name: movie_sentiment_trainer_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_sentiment_trainer_pipeline` is a English model originally trained by Sonny4Sonnix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_sentiment_trainer_pipeline_en_5.5.0_3.0_1725211747602.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_sentiment_trainer_pipeline_en_5.5.0_3.0_1725211747602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("movie_sentiment_trainer_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("movie_sentiment_trainer_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|movie_sentiment_trainer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/Sonny4Sonnix/movie_sentiment_trainer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mpnet_base_all_nli_triplet_tomaarsen_en.md b/docs/_posts/ahmedlone127/2024-09-01-mpnet_base_all_nli_triplet_tomaarsen_en.md new file mode 100644 index 00000000000000..c70973d846302a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mpnet_base_all_nli_triplet_tomaarsen_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mpnet_base_all_nli_triplet_tomaarsen MPNetEmbeddings from tomaarsen +author: John Snow Labs +name: mpnet_base_all_nli_triplet_tomaarsen +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_all_nli_triplet_tomaarsen` is a English model originally trained by tomaarsen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_all_nli_triplet_tomaarsen_en_5.5.0_3.0_1725225168167.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_all_nli_triplet_tomaarsen_en_5.5.0_3.0_1725225168167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("mpnet_base_all_nli_triplet_tomaarsen","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("mpnet_base_all_nli_triplet_tomaarsen","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_all_nli_triplet_tomaarsen| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|390.1 MB| + +## References + +https://huggingface.co/tomaarsen/mpnet-base-all-nli-triplet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mpnet_base_all_nli_triplet_tomaarsen_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mpnet_base_all_nli_triplet_tomaarsen_pipeline_en.md new file mode 100644 index 00000000000000..bc11ddd59fd76d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mpnet_base_all_nli_triplet_tomaarsen_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mpnet_base_all_nli_triplet_tomaarsen_pipeline pipeline MPNetEmbeddings from tomaarsen +author: John Snow Labs +name: mpnet_base_all_nli_triplet_tomaarsen_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_all_nli_triplet_tomaarsen_pipeline` is a English model originally trained by tomaarsen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_all_nli_triplet_tomaarsen_pipeline_en_5.5.0_3.0_1725225196214.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_all_nli_triplet_tomaarsen_pipeline_en_5.5.0_3.0_1725225196214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mpnet_base_all_nli_triplet_tomaarsen_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mpnet_base_all_nli_triplet_tomaarsen_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_all_nli_triplet_tomaarsen_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|390.1 MB| + +## References + +https://huggingface.co/tomaarsen/mpnet-base-all-nli-triplet + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mpnet_personality_en.md b/docs/_posts/ahmedlone127/2024-09-01-mpnet_personality_en.md new file mode 100644 index 00000000000000..cb633b1758fe2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mpnet_personality_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mpnet_personality MPNetEmbeddings from dwulff +author: John Snow Labs +name: mpnet_personality +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_personality` is a English model originally trained by dwulff. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_personality_en_5.5.0_3.0_1725224802814.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_personality_en_5.5.0_3.0_1725224802814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("mpnet_personality","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("mpnet_personality","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_personality| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/dwulff/mpnet-personality \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mpnet_personality_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mpnet_personality_pipeline_en.md new file mode 100644 index 00000000000000..6be4501f326786 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mpnet_personality_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mpnet_personality_pipeline pipeline MPNetEmbeddings from dwulff +author: John Snow Labs +name: mpnet_personality_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_personality_pipeline` is a English model originally trained by dwulff. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_personality_pipeline_en_5.5.0_3.0_1725224825311.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_personality_pipeline_en_5.5.0_3.0_1725224825311.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mpnet_personality_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mpnet_personality_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_personality_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/dwulff/mpnet-personality + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mrc_er_mdeberta_v3_base_syl_viwikifc_en.md b/docs/_posts/ahmedlone127/2024-09-01-mrc_er_mdeberta_v3_base_syl_viwikifc_en.md new file mode 100644 index 00000000000000..423081a16ad1b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mrc_er_mdeberta_v3_base_syl_viwikifc_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mrc_er_mdeberta_v3_base_syl_viwikifc DeBertaForQuestionAnswering from tringuyen-uit +author: John Snow Labs +name: mrc_er_mdeberta_v3_base_syl_viwikifc +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mrc_er_mdeberta_v3_base_syl_viwikifc` is a English model originally trained by tringuyen-uit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mrc_er_mdeberta_v3_base_syl_viwikifc_en_5.5.0_3.0_1725218318863.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mrc_er_mdeberta_v3_base_syl_viwikifc_en_5.5.0_3.0_1725218318863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mrc_er_mdeberta_v3_base_syl_viwikifc","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mrc_er_mdeberta_v3_base_syl_viwikifc", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mrc_er_mdeberta_v3_base_syl_viwikifc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|813.7 MB| + +## References + +https://huggingface.co/tringuyen-uit/MRC_ER_mdeberta-v3-base_syl_ViWikiFC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-mrc_er_mdeberta_v3_base_syl_viwikifc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mrc_er_mdeberta_v3_base_syl_viwikifc_pipeline_en.md new file mode 100644 index 00000000000000..fb5a2e16703649 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-mrc_er_mdeberta_v3_base_syl_viwikifc_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mrc_er_mdeberta_v3_base_syl_viwikifc_pipeline pipeline DeBertaForQuestionAnswering from tringuyen-uit +author: John Snow Labs +name: mrc_er_mdeberta_v3_base_syl_viwikifc_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mrc_er_mdeberta_v3_base_syl_viwikifc_pipeline` is a English model originally trained by tringuyen-uit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mrc_er_mdeberta_v3_base_syl_viwikifc_pipeline_en_5.5.0_3.0_1725218439060.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mrc_er_mdeberta_v3_base_syl_viwikifc_pipeline_en_5.5.0_3.0_1725218439060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mrc_er_mdeberta_v3_base_syl_viwikifc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mrc_er_mdeberta_v3_base_syl_viwikifc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mrc_er_mdeberta_v3_base_syl_viwikifc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|813.7 MB| + +## References + +https://huggingface.co/tringuyen-uit/MRC_ER_mdeberta-v3-base_syl_ViWikiFC + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-named_entity_recognition_distilbert_a_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-named_entity_recognition_distilbert_a_pipeline_en.md new file mode 100644 index 00000000000000..bc4e8d22d39e96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-named_entity_recognition_distilbert_a_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English named_entity_recognition_distilbert_a_pipeline pipeline DistilBertForTokenClassification from imrazaa +author: John Snow Labs +name: named_entity_recognition_distilbert_a_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`named_entity_recognition_distilbert_a_pipeline` is a English model originally trained by imrazaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/named_entity_recognition_distilbert_a_pipeline_en_5.4.2_3.0_1725170632486.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/named_entity_recognition_distilbert_a_pipeline_en_5.4.2_3.0_1725170632486.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("named_entity_recognition_distilbert_a_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("named_entity_recognition_distilbert_a_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|named_entity_recognition_distilbert_a_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.4 MB| + +## References + +https://huggingface.co/imrazaa/named-entity-recognition-distilbert-A + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-nasa_smd_ibm_ranker_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-nasa_smd_ibm_ranker_pipeline_en.md new file mode 100644 index 00000000000000..45c1c36ff84592 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-nasa_smd_ibm_ranker_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nasa_smd_ibm_ranker_pipeline pipeline RoBertaForSequenceClassification from nasa-impact +author: John Snow Labs +name: nasa_smd_ibm_ranker_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nasa_smd_ibm_ranker_pipeline` is a English model originally trained by nasa-impact. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nasa_smd_ibm_ranker_pipeline_en_5.4.2_3.0_1725167279770.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nasa_smd_ibm_ranker_pipeline_en_5.4.2_3.0_1725167279770.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nasa_smd_ibm_ranker_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nasa_smd_ibm_ranker_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nasa_smd_ibm_ranker_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/nasa-impact/nasa-smd-ibm-ranker + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-nemesis_reranker_en.md b/docs/_posts/ahmedlone127/2024-09-01-nemesis_reranker_en.md new file mode 100644 index 00000000000000..96c6164ef0695a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-nemesis_reranker_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nemesis_reranker XlmRoBertaForSequenceClassification from Harmj0y +author: John Snow Labs +name: nemesis_reranker +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nemesis_reranker` is a English model originally trained by Harmj0y. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nemesis_reranker_en_5.4.2_3.0_1725169597729.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nemesis_reranker_en_5.4.2_3.0_1725169597729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("nemesis_reranker","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("nemesis_reranker", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nemesis_reranker| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|992.2 MB| + +## References + +https://huggingface.co/Harmj0y/nemesis-reranker \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-nemesis_reranker_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-nemesis_reranker_pipeline_en.md new file mode 100644 index 00000000000000..6dd1e1aa39adad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-nemesis_reranker_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nemesis_reranker_pipeline pipeline XlmRoBertaForSequenceClassification from Harmj0y +author: John Snow Labs +name: nemesis_reranker_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nemesis_reranker_pipeline` is a English model originally trained by Harmj0y. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nemesis_reranker_pipeline_en_5.4.2_3.0_1725169664545.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nemesis_reranker_pipeline_en_5.4.2_3.0_1725169664545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nemesis_reranker_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nemesis_reranker_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nemesis_reranker_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|992.2 MB| + +## References + +https://huggingface.co/Harmj0y/nemesis-reranker + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ner_bert_base_cased_portuguese_lenerbr_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-01-ner_bert_base_cased_portuguese_lenerbr_pipeline_pt.md new file mode 100644 index 00000000000000..28671a4e027ccc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ner_bert_base_cased_portuguese_lenerbr_pipeline_pt.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Portuguese ner_bert_base_cased_portuguese_lenerbr_pipeline pipeline BertForTokenClassification from pierreguillou +author: John Snow Labs +name: ner_bert_base_cased_portuguese_lenerbr_pipeline +date: 2024-09-01 +tags: [pt, open_source, pipeline, onnx] +task: Named Entity Recognition +language: pt +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_bert_base_cased_portuguese_lenerbr_pipeline` is a Portuguese model originally trained by pierreguillou. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_bert_base_cased_portuguese_lenerbr_pipeline_pt_5.4.2_3.0_1725163765506.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_bert_base_cased_portuguese_lenerbr_pipeline_pt_5.4.2_3.0_1725163765506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ner_bert_base_cased_portuguese_lenerbr_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ner_bert_base_cased_portuguese_lenerbr_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_bert_base_cased_portuguese_lenerbr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|406.0 MB| + +## References + +https://huggingface.co/pierreguillou/ner-bert-base-cased-pt-lenerbr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ner_indic_bert_en.md b/docs/_posts/ahmedlone127/2024-09-01-ner_indic_bert_en.md new file mode 100644 index 00000000000000..a74d8376a2d29c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ner_indic_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ner_indic_bert AlbertForTokenClassification from AnanthZeke +author: John Snow Labs +name: ner_indic_bert +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, albert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_indic_bert` is a English model originally trained by AnanthZeke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_indic_bert_en_5.4.2_3.0_1725203397584.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_indic_bert_en_5.4.2_3.0_1725203397584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = AlbertForTokenClassification.pretrained("ner_indic_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = AlbertForTokenClassification.pretrained("ner_indic_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_indic_bert| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|125.6 MB| + +## References + +https://huggingface.co/AnanthZeke/NER-indic-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ner_indic_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ner_indic_bert_pipeline_en.md new file mode 100644 index 00000000000000..95a617053b4c00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ner_indic_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ner_indic_bert_pipeline pipeline AlbertForTokenClassification from AnanthZeke +author: John Snow Labs +name: ner_indic_bert_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_indic_bert_pipeline` is a English model originally trained by AnanthZeke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_indic_bert_pipeline_en_5.4.2_3.0_1725203404116.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_indic_bert_pipeline_en_5.4.2_3.0_1725203404116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ner_indic_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ner_indic_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_indic_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|125.6 MB| + +## References + +https://huggingface.co/AnanthZeke/NER-indic-bert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ner_model_balciberin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ner_model_balciberin_pipeline_en.md new file mode 100644 index 00000000000000..90d1e226fee1cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ner_model_balciberin_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ner_model_balciberin_pipeline pipeline DistilBertForTokenClassification from balciberin +author: John Snow Labs +name: ner_model_balciberin_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_balciberin_pipeline` is a English model originally trained by balciberin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_balciberin_pipeline_en_5.4.2_3.0_1725171979715.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_balciberin_pipeline_en_5.4.2_3.0_1725171979715.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ner_model_balciberin_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ner_model_balciberin_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_model_balciberin_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/balciberin/ner_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ner_on_proteindata_en.md b/docs/_posts/ahmedlone127/2024-09-01-ner_on_proteindata_en.md new file mode 100644 index 00000000000000..2de3f6e58a4ede --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ner_on_proteindata_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ner_on_proteindata DistilBertForTokenClassification from Galaxyman +author: John Snow Labs +name: ner_on_proteindata +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_on_proteindata` is a English model originally trained by Galaxyman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_on_proteindata_en_5.4.2_3.0_1725171151971.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_on_proteindata_en_5.4.2_3.0_1725171151971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("ner_on_proteindata","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_on_proteindata", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_on_proteindata| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/Galaxyman/ner_on_proteindata \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ner_tune_v2_42_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ner_tune_v2_42_pipeline_en.md new file mode 100644 index 00000000000000..d4d4d6f9a4352a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ner_tune_v2_42_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ner_tune_v2_42_pipeline pipeline CamemBertForTokenClassification from Madnesss +author: John Snow Labs +name: ner_tune_v2_42_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_tune_v2_42_pipeline` is a English model originally trained by Madnesss. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_tune_v2_42_pipeline_en_5.4.2_3.0_1725175195052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_tune_v2_42_pipeline_en_5.4.2_3.0_1725175195052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ner_tune_v2_42_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ner_tune_v2_42_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_tune_v2_42_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|392.2 MB| + +## References + +https://huggingface.co/Madnesss/ner-tune-v2_42 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-norwegian_bokml_bert_base_mnli_no.md b/docs/_posts/ahmedlone127/2024-09-01-norwegian_bokml_bert_base_mnli_no.md new file mode 100644 index 00000000000000..7633852caa0565 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-norwegian_bokml_bert_base_mnli_no.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Norwegian norwegian_bokml_bert_base_mnli BertForZeroShotClassification from NbAiLab +author: John Snow Labs +name: norwegian_bokml_bert_base_mnli +date: 2024-09-01 +tags: ["no", open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: "no" +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_bert_base_mnli` is a Norwegian model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_mnli_no_5.4.2_3.0_1725202576003.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_mnli_no_5.4.2_3.0_1725202576003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("norwegian_bokml_bert_base_mnli","no") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("norwegian_bokml_bert_base_mnli", "no") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_bert_base_mnli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|no| +|Size:|666.1 MB| + +## References + +https://huggingface.co/NbAiLab/nb-bert-base-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-norwegian_bokml_bert_base_mnli_pipeline_no.md b/docs/_posts/ahmedlone127/2024-09-01-norwegian_bokml_bert_base_mnli_pipeline_no.md new file mode 100644 index 00000000000000..4cf54cdb59be71 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-norwegian_bokml_bert_base_mnli_pipeline_no.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Norwegian norwegian_bokml_bert_base_mnli_pipeline pipeline BertForZeroShotClassification from NbAiLab +author: John Snow Labs +name: norwegian_bokml_bert_base_mnli_pipeline +date: 2024-09-01 +tags: ["no", open_source, pipeline, onnx] +task: Zero-Shot Classification +language: "no" +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_bert_base_mnli_pipeline` is a Norwegian model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_mnli_pipeline_no_5.4.2_3.0_1725202613747.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_mnli_pipeline_no_5.4.2_3.0_1725202613747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("norwegian_bokml_bert_base_mnli_pipeline", lang = "no") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("norwegian_bokml_bert_base_mnli_pipeline", lang = "no") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_bert_base_mnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|no| +|Size:|666.2 MB| + +## References + +https://huggingface.co/NbAiLab/nb-bert-base-mnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-norwegian_bokml_bert_base_qa_norquad_no.md b/docs/_posts/ahmedlone127/2024-09-01-norwegian_bokml_bert_base_qa_norquad_no.md new file mode 100644 index 00000000000000..a76bd590fff87e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-norwegian_bokml_bert_base_qa_norquad_no.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Norwegian norwegian_bokml_bert_base_qa_norquad BertForQuestionAnswering from eanderson +author: John Snow Labs +name: norwegian_bokml_bert_base_qa_norquad +date: 2024-09-01 +tags: ["no", open_source, onnx, question_answering, bert] +task: Question Answering +language: "no" +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_bert_base_qa_norquad` is a Norwegian model originally trained by eanderson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_qa_norquad_no_5.5.0_3.0_1725215027572.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_qa_norquad_no_5.5.0_3.0_1725215027572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("norwegian_bokml_bert_base_qa_norquad","no") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("norwegian_bokml_bert_base_qa_norquad", "no") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_bert_base_qa_norquad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|no| +|Size:|666.2 MB| + +## References + +https://huggingface.co/eanderson/nb-bert-base-qa-norquad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-norwegian_bokml_bert_base_qa_norquad_pipeline_no.md b/docs/_posts/ahmedlone127/2024-09-01-norwegian_bokml_bert_base_qa_norquad_pipeline_no.md new file mode 100644 index 00000000000000..74ae5ac3e8deae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-norwegian_bokml_bert_base_qa_norquad_pipeline_no.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Norwegian norwegian_bokml_bert_base_qa_norquad_pipeline pipeline BertForQuestionAnswering from eanderson +author: John Snow Labs +name: norwegian_bokml_bert_base_qa_norquad_pipeline +date: 2024-09-01 +tags: ["no", open_source, pipeline, onnx] +task: Question Answering +language: "no" +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_bert_base_qa_norquad_pipeline` is a Norwegian model originally trained by eanderson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_qa_norquad_pipeline_no_5.5.0_3.0_1725215063931.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_qa_norquad_pipeline_no_5.5.0_3.0_1725215063931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("norwegian_bokml_bert_base_qa_norquad_pipeline", lang = "no") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("norwegian_bokml_bert_base_qa_norquad_pipeline", lang = "no") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_bert_base_qa_norquad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|no| +|Size:|666.2 MB| + +## References + +https://huggingface.co/eanderson/nb-bert-base-qa-norquad + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-npm_single_en.md b/docs/_posts/ahmedlone127/2024-09-01-npm_single_en.md new file mode 100644 index 00000000000000..6c274c875436f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-npm_single_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English npm_single RoBertaEmbeddings from facebook +author: John Snow Labs +name: npm_single +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`npm_single` is a English model originally trained by facebook. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/npm_single_en_5.4.2_3.0_1725187310695.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/npm_single_en_5.4.2_3.0_1725187310695.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("npm_single","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("npm_single","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|npm_single| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|843.4 MB| + +## References + +https://huggingface.co/facebook/npm-single \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-nsfw_text_detection_large_en.md b/docs/_posts/ahmedlone127/2024-09-01-nsfw_text_detection_large_en.md new file mode 100644 index 00000000000000..2e65b6c6159b87 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-nsfw_text_detection_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nsfw_text_detection_large RoBertaForSequenceClassification from MichalMlodawski +author: John Snow Labs +name: nsfw_text_detection_large +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsfw_text_detection_large` is a English model originally trained by MichalMlodawski. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nsfw_text_detection_large_en_5.4.2_3.0_1725194771837.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsfw_text_detection_large_en_5.4.2_3.0_1725194771837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("nsfw_text_detection_large","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("nsfw_text_detection_large", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nsfw_text_detection_large| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/MichalMlodawski/nsfw-text-detection-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-nsfw_text_detection_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-nsfw_text_detection_large_pipeline_en.md new file mode 100644 index 00000000000000..341a504d47c712 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-nsfw_text_detection_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nsfw_text_detection_large_pipeline pipeline RoBertaForSequenceClassification from MichalMlodawski +author: John Snow Labs +name: nsfw_text_detection_large_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsfw_text_detection_large_pipeline` is a English model originally trained by MichalMlodawski. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nsfw_text_detection_large_pipeline_en_5.4.2_3.0_1725194847608.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsfw_text_detection_large_pipeline_en_5.4.2_3.0_1725194847608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nsfw_text_detection_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nsfw_text_detection_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nsfw_text_detection_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/MichalMlodawski/nsfw-text-detection-large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ofm_clip_base_patch32_cifar10_en.md b/docs/_posts/ahmedlone127/2024-09-01-ofm_clip_base_patch32_cifar10_en.md new file mode 100644 index 00000000000000..00cb6a33316b46 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ofm_clip_base_patch32_cifar10_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English ofm_clip_base_patch32_cifar10 CLIPForZeroShotClassification from yusx-swapp +author: John Snow Labs +name: ofm_clip_base_patch32_cifar10 +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ofm_clip_base_patch32_cifar10` is a English model originally trained by yusx-swapp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ofm_clip_base_patch32_cifar10_en_5.5.0_3.0_1725225678625.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ofm_clip_base_patch32_cifar10_en_5.5.0_3.0_1725225678625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("ofm_clip_base_patch32_cifar10","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("ofm_clip_base_patch32_cifar10","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ofm_clip_base_patch32_cifar10| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|523.5 MB| + +## References + +https://huggingface.co/yusx-swapp/ofm-clip-base-patch32-cifar10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ofm_clip_base_patch32_cifar10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-ofm_clip_base_patch32_cifar10_pipeline_en.md new file mode 100644 index 00000000000000..2066c7fc62ab61 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ofm_clip_base_patch32_cifar10_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ofm_clip_base_patch32_cifar10_pipeline pipeline CLIPForZeroShotClassification from yusx-swapp +author: John Snow Labs +name: ofm_clip_base_patch32_cifar10_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ofm_clip_base_patch32_cifar10_pipeline` is a English model originally trained by yusx-swapp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ofm_clip_base_patch32_cifar10_pipeline_en_5.5.0_3.0_1725225725686.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ofm_clip_base_patch32_cifar10_pipeline_en_5.5.0_3.0_1725225725686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ofm_clip_base_patch32_cifar10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ofm_clip_base_patch32_cifar10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ofm_clip_base_patch32_cifar10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|523.5 MB| + +## References + +https://huggingface.co/yusx-swapp/ofm-clip-base-patch32-cifar10 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-openai_roberta_large_ai_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-openai_roberta_large_ai_detection_pipeline_en.md new file mode 100644 index 00000000000000..b25ef86551eb7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-openai_roberta_large_ai_detection_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English openai_roberta_large_ai_detection_pipeline pipeline RoBertaForSequenceClassification from Varun53 +author: John Snow Labs +name: openai_roberta_large_ai_detection_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`openai_roberta_large_ai_detection_pipeline` is a English model originally trained by Varun53. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/openai_roberta_large_ai_detection_pipeline_en_5.4.2_3.0_1725167684026.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/openai_roberta_large_ai_detection_pipeline_en_5.4.2_3.0_1725167684026.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("openai_roberta_large_ai_detection_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("openai_roberta_large_ai_detection_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|openai_roberta_large_ai_detection_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Varun53/openai-roberta-large-AI-detection + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-opendispatcher_v5_gpt35turbo_and_gpt4_en.md b/docs/_posts/ahmedlone127/2024-09-01-opendispatcher_v5_gpt35turbo_and_gpt4_en.md new file mode 100644 index 00000000000000..efcbb365ff292c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-opendispatcher_v5_gpt35turbo_and_gpt4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opendispatcher_v5_gpt35turbo_and_gpt4 DistilBertForSequenceClassification from gaodrew +author: John Snow Labs +name: opendispatcher_v5_gpt35turbo_and_gpt4 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opendispatcher_v5_gpt35turbo_and_gpt4` is a English model originally trained by gaodrew. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opendispatcher_v5_gpt35turbo_and_gpt4_en_5.5.0_3.0_1725213944335.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opendispatcher_v5_gpt35turbo_and_gpt4_en_5.5.0_3.0_1725213944335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("opendispatcher_v5_gpt35turbo_and_gpt4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("opendispatcher_v5_gpt35turbo_and_gpt4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opendispatcher_v5_gpt35turbo_and_gpt4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/gaodrew/OpenDispatcher_v5_gpt35turbo_and_gpt4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-opendispatcher_v5_gpt35turbo_and_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-opendispatcher_v5_gpt35turbo_and_gpt4_pipeline_en.md new file mode 100644 index 00000000000000..559067b484dd5d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-opendispatcher_v5_gpt35turbo_and_gpt4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opendispatcher_v5_gpt35turbo_and_gpt4_pipeline pipeline DistilBertForSequenceClassification from gaodrew +author: John Snow Labs +name: opendispatcher_v5_gpt35turbo_and_gpt4_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opendispatcher_v5_gpt35turbo_and_gpt4_pipeline` is a English model originally trained by gaodrew. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opendispatcher_v5_gpt35turbo_and_gpt4_pipeline_en_5.5.0_3.0_1725213958056.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opendispatcher_v5_gpt35turbo_and_gpt4_pipeline_en_5.5.0_3.0_1725213958056.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opendispatcher_v5_gpt35turbo_and_gpt4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opendispatcher_v5_gpt35turbo_and_gpt4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opendispatcher_v5_gpt35turbo_and_gpt4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/gaodrew/OpenDispatcher_v5_gpt35turbo_and_gpt4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-outputs_bittar_en.md b/docs/_posts/ahmedlone127/2024-09-01-outputs_bittar_en.md new file mode 100644 index 00000000000000..3306ae3a6fbb53 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-outputs_bittar_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English outputs_bittar XlmRoBertaForSequenceClassification from Bittar +author: John Snow Labs +name: outputs_bittar +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`outputs_bittar` is a English model originally trained by Bittar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/outputs_bittar_en_5.4.2_3.0_1725188826298.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/outputs_bittar_en_5.4.2_3.0_1725188826298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("outputs_bittar","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("outputs_bittar", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|outputs_bittar| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/Bittar/outputs \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-paraphrase_mpnet_base_v2_offensive_en.md b/docs/_posts/ahmedlone127/2024-09-01-paraphrase_mpnet_base_v2_offensive_en.md new file mode 100644 index 00000000000000..855f35084c8745 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-paraphrase_mpnet_base_v2_offensive_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English paraphrase_mpnet_base_v2_offensive MPNetEmbeddings from valurank +author: John Snow Labs +name: paraphrase_mpnet_base_v2_offensive +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_mpnet_base_v2_offensive` is a English model originally trained by valurank. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_offensive_en_5.5.0_3.0_1725225223063.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_offensive_en_5.5.0_3.0_1725225223063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("paraphrase_mpnet_base_v2_offensive","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("paraphrase_mpnet_base_v2_offensive","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|paraphrase_mpnet_base_v2_offensive| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/valurank/paraphrase-mpnet-base-v2-offensive \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-paraphrase_mpnet_base_v2_offensive_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-paraphrase_mpnet_base_v2_offensive_pipeline_en.md new file mode 100644 index 00000000000000..31aa9417104fc7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-paraphrase_mpnet_base_v2_offensive_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English paraphrase_mpnet_base_v2_offensive_pipeline pipeline MPNetEmbeddings from valurank +author: John Snow Labs +name: paraphrase_mpnet_base_v2_offensive_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_mpnet_base_v2_offensive_pipeline` is a English model originally trained by valurank. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_offensive_pipeline_en_5.5.0_3.0_1725225245129.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_offensive_pipeline_en_5.5.0_3.0_1725225245129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("paraphrase_mpnet_base_v2_offensive_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("paraphrase_mpnet_base_v2_offensive_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|paraphrase_mpnet_base_v2_offensive_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/valurank/paraphrase-mpnet-base-v2-offensive + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-per_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-01-per_classifier_en.md new file mode 100644 index 00000000000000..fc8abe4c3ed1c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-per_classifier_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English per_classifier RoBertaForSequenceClassification from soulFoo +author: John Snow Labs +name: per_classifier +date: 2024-09-01 +tags: [roberta, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`per_classifier` is a English model originally trained by soulFoo. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/per_classifier_en_5.5.0_3.0_1725212289383.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/per_classifier_en_5.5.0_3.0_1725212289383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("per_classifier","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("per_classifier","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|per_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|430.1 MB| + +## References + +References + +https://huggingface.co/soulFoo/per-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-per_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-per_classifier_pipeline_en.md new file mode 100644 index 00000000000000..115e4b45f257be --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-per_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English per_classifier_pipeline pipeline RoBertaForSequenceClassification from shai-msy +author: John Snow Labs +name: per_classifier_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`per_classifier_pipeline` is a English model originally trained by shai-msy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/per_classifier_pipeline_en_5.5.0_3.0_1725212330229.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/per_classifier_pipeline_en_5.5.0_3.0_1725212330229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("per_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("per_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|per_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|430.1 MB| + +## References + +https://huggingface.co/shai-msy/per-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-pmc_vit_l_14_hf_en.md b/docs/_posts/ahmedlone127/2024-09-01-pmc_vit_l_14_hf_en.md new file mode 100644 index 00000000000000..4586897f143657 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-pmc_vit_l_14_hf_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English pmc_vit_l_14_hf CLIPForZeroShotClassification from ryanyip7777 +author: John Snow Labs +name: pmc_vit_l_14_hf +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pmc_vit_l_14_hf` is a English model originally trained by ryanyip7777. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pmc_vit_l_14_hf_en_5.5.0_3.0_1725226893370.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pmc_vit_l_14_hf_en_5.5.0_3.0_1725226893370.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("pmc_vit_l_14_hf","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("pmc_vit_l_14_hf","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pmc_vit_l_14_hf| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/ryanyip7777/pmc_vit-l-14_hf \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-pmc_vit_l_14_hf_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-pmc_vit_l_14_hf_pipeline_en.md new file mode 100644 index 00000000000000..79fa5ac5d690e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-pmc_vit_l_14_hf_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English pmc_vit_l_14_hf_pipeline pipeline CLIPForZeroShotClassification from ryanyip7777 +author: John Snow Labs +name: pmc_vit_l_14_hf_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pmc_vit_l_14_hf_pipeline` is a English model originally trained by ryanyip7777. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pmc_vit_l_14_hf_pipeline_en_5.5.0_3.0_1725226980278.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pmc_vit_l_14_hf_pipeline_en_5.5.0_3.0_1725226980278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("pmc_vit_l_14_hf_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("pmc_vit_l_14_hf_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pmc_vit_l_14_hf_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/ryanyip7777/pmc_vit-l-14_hf + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-promptinjectiondetector_en.md b/docs/_posts/ahmedlone127/2024-09-01-promptinjectiondetector_en.md new file mode 100644 index 00000000000000..2cba38f8f87bd7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-promptinjectiondetector_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English promptinjectiondetector RoBertaForSequenceClassification from sense2k8 +author: John Snow Labs +name: promptinjectiondetector +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`promptinjectiondetector` is a English model originally trained by sense2k8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/promptinjectiondetector_en_5.4.2_3.0_1725194283325.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/promptinjectiondetector_en_5.4.2_3.0_1725194283325.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("promptinjectiondetector","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("promptinjectiondetector", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|promptinjectiondetector| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|419.9 MB| + +## References + +https://huggingface.co/sense2k8/promptInjectionDetector \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-promptinjectiondetector_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-promptinjectiondetector_pipeline_en.md new file mode 100644 index 00000000000000..0e12efb992a929 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-promptinjectiondetector_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English promptinjectiondetector_pipeline pipeline RoBertaForSequenceClassification from sense2k8 +author: John Snow Labs +name: promptinjectiondetector_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`promptinjectiondetector_pipeline` is a English model originally trained by sense2k8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/promptinjectiondetector_pipeline_en_5.4.2_3.0_1725194324170.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/promptinjectiondetector_pipeline_en_5.4.2_3.0_1725194324170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("promptinjectiondetector_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("promptinjectiondetector_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|promptinjectiondetector_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|420.0 MB| + +## References + +https://huggingface.co/sense2k8/promptInjectionDetector + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-propagandadetection_en.md b/docs/_posts/ahmedlone127/2024-09-01-propagandadetection_en.md new file mode 100644 index 00000000000000..09e6940de9d162 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-propagandadetection_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English propagandadetection DistilBertForSequenceClassification from claudio2222 +author: John Snow Labs +name: propagandadetection +date: 2024-09-01 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`propagandadetection` is a English model originally trained by claudio2222. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/propagandadetection_en_5.5.0_3.0_1725214081899.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/propagandadetection_en_5.5.0_3.0_1725214081899.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("propagandadetection","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("propagandadetection","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|propagandadetection| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +References + +https://huggingface.co/claudio2222/PropagandaDetection \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-propagandadetection_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-propagandadetection_pipeline_en.md new file mode 100644 index 00000000000000..a2f7cac566ef11 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-propagandadetection_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English propagandadetection_pipeline pipeline DistilBertForSequenceClassification from IDA-SERICS +author: John Snow Labs +name: propagandadetection_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`propagandadetection_pipeline` is a English model originally trained by IDA-SERICS. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/propagandadetection_pipeline_en_5.5.0_3.0_1725214097463.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/propagandadetection_pipeline_en_5.5.0_3.0_1725214097463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("propagandadetection_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("propagandadetection_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|propagandadetection_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/IDA-SERICS/PropagandaDetection + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-qa_model_roberta_en.md b/docs/_posts/ahmedlone127/2024-09-01-qa_model_roberta_en.md new file mode 100644 index 00000000000000..3c83917e9a7144 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-qa_model_roberta_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English qa_model_roberta RoBertaForQuestionAnswering from SMD00 +author: John Snow Labs +name: qa_model_roberta +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_roberta` is a English model originally trained by SMD00. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model_roberta_en_5.4.2_3.0_1725206551472.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_roberta_en_5.4.2_3.0_1725206551472.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("qa_model_roberta","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("qa_model_roberta", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qa_model_roberta| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/SMD00/QA_model-roberta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-qa_model_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-qa_model_roberta_pipeline_en.md new file mode 100644 index 00000000000000..028cdd97fa07d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-qa_model_roberta_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English qa_model_roberta_pipeline pipeline RoBertaForQuestionAnswering from SMD00 +author: John Snow Labs +name: qa_model_roberta_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_roberta_pipeline` is a English model originally trained by SMD00. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model_roberta_pipeline_en_5.4.2_3.0_1725206581917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_roberta_pipeline_en_5.4.2_3.0_1725206581917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("qa_model_roberta_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("qa_model_roberta_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qa_model_roberta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/SMD00/QA_model-roberta + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-qa_synth_19_sept_finetune_1_0_en.md b/docs/_posts/ahmedlone127/2024-09-01-qa_synth_19_sept_finetune_1_0_en.md new file mode 100644 index 00000000000000..a39bad28cd3548 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-qa_synth_19_sept_finetune_1_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English qa_synth_19_sept_finetune_1_0 XlmRoBertaForQuestionAnswering from am-infoweb +author: John Snow Labs +name: qa_synth_19_sept_finetune_1_0 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synth_19_sept_finetune_1_0` is a English model originally trained by am-infoweb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synth_19_sept_finetune_1_0_en_5.5.0_3.0_1725234759307.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synth_19_sept_finetune_1_0_en_5.5.0_3.0_1725234759307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_synth_19_sept_finetune_1_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_synth_19_sept_finetune_1_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qa_synth_19_sept_finetune_1_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|816.6 MB| + +## References + +https://huggingface.co/am-infoweb/QA_SYNTH_19_SEPT_FINETUNE_1.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-qa_synth_19_sept_finetune_1_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-qa_synth_19_sept_finetune_1_0_pipeline_en.md new file mode 100644 index 00000000000000..b258ea5dac46fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-qa_synth_19_sept_finetune_1_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English qa_synth_19_sept_finetune_1_0_pipeline pipeline XlmRoBertaForQuestionAnswering from am-infoweb +author: John Snow Labs +name: qa_synth_19_sept_finetune_1_0_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synth_19_sept_finetune_1_0_pipeline` is a English model originally trained by am-infoweb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synth_19_sept_finetune_1_0_pipeline_en_5.5.0_3.0_1725234862060.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synth_19_sept_finetune_1_0_pipeline_en_5.5.0_3.0_1725234862060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("qa_synth_19_sept_finetune_1_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("qa_synth_19_sept_finetune_1_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qa_synth_19_sept_finetune_1_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|816.6 MB| + +## References + +https://huggingface.co/am-infoweb/QA_SYNTH_19_SEPT_FINETUNE_1.0 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-qnli_microsoft_deberta_v3_base_seed_3_en.md b/docs/_posts/ahmedlone127/2024-09-01-qnli_microsoft_deberta_v3_base_seed_3_en.md new file mode 100644 index 00000000000000..7f7c90bb369513 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-qnli_microsoft_deberta_v3_base_seed_3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English qnli_microsoft_deberta_v3_base_seed_3 DeBertaForSequenceClassification from utahnlp +author: John Snow Labs +name: qnli_microsoft_deberta_v3_base_seed_3 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qnli_microsoft_deberta_v3_base_seed_3` is a English model originally trained by utahnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qnli_microsoft_deberta_v3_base_seed_3_en_5.5.0_3.0_1725209949486.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qnli_microsoft_deberta_v3_base_seed_3_en_5.5.0_3.0_1725209949486.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("qnli_microsoft_deberta_v3_base_seed_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("qnli_microsoft_deberta_v3_base_seed_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qnli_microsoft_deberta_v3_base_seed_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|637.9 MB| + +## References + +https://huggingface.co/utahnlp/qnli_microsoft_deberta-v3-base_seed-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-qnli_microsoft_deberta_v3_base_seed_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-qnli_microsoft_deberta_v3_base_seed_3_pipeline_en.md new file mode 100644 index 00000000000000..df26ea3930696b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-qnli_microsoft_deberta_v3_base_seed_3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English qnli_microsoft_deberta_v3_base_seed_3_pipeline pipeline DeBertaForSequenceClassification from utahnlp +author: John Snow Labs +name: qnli_microsoft_deberta_v3_base_seed_3_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qnli_microsoft_deberta_v3_base_seed_3_pipeline` is a English model originally trained by utahnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qnli_microsoft_deberta_v3_base_seed_3_pipeline_en_5.5.0_3.0_1725210003839.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qnli_microsoft_deberta_v3_base_seed_3_pipeline_en_5.5.0_3.0_1725210003839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("qnli_microsoft_deberta_v3_base_seed_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("qnli_microsoft_deberta_v3_base_seed_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qnli_microsoft_deberta_v3_base_seed_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|637.9 MB| + +## References + +https://huggingface.co/utahnlp/qnli_microsoft_deberta-v3-base_seed-3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-question_answering_albert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-question_answering_albert_base_pipeline_en.md new file mode 100644 index 00000000000000..6c102377c6b9f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-question_answering_albert_base_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English question_answering_albert_base_pipeline pipeline AlbertForQuestionAnswering from TunahanGokcimen +author: John Snow Labs +name: question_answering_albert_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_albert_base_pipeline` is a English model originally trained by TunahanGokcimen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_answering_albert_base_pipeline_en_5.4.2_3.0_1725193434258.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_albert_base_pipeline_en_5.4.2_3.0_1725193434258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("question_answering_albert_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("question_answering_albert_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|question_answering_albert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/TunahanGokcimen/Question-Answering-Albert-base + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-quiltnet_b_32_en.md b/docs/_posts/ahmedlone127/2024-09-01-quiltnet_b_32_en.md new file mode 100644 index 00000000000000..1b5326be66d628 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-quiltnet_b_32_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English quiltnet_b_32 CLIPForZeroShotClassification from wisdomik +author: John Snow Labs +name: quiltnet_b_32 +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`quiltnet_b_32` is a English model originally trained by wisdomik. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/quiltnet_b_32_en_5.5.0_3.0_1725227758487.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/quiltnet_b_32_en_5.5.0_3.0_1725227758487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("quiltnet_b_32","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("quiltnet_b_32","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|quiltnet_b_32| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/wisdomik/QuiltNet-B-32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-quiltnet_b_32_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-quiltnet_b_32_pipeline_en.md new file mode 100644 index 00000000000000..0749f639dd0b94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-quiltnet_b_32_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English quiltnet_b_32_pipeline pipeline CLIPForZeroShotClassification from wisdomik +author: John Snow Labs +name: quiltnet_b_32_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`quiltnet_b_32_pipeline` is a English model originally trained by wisdomik. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/quiltnet_b_32_pipeline_en_5.5.0_3.0_1725227788331.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/quiltnet_b_32_pipeline_en_5.5.0_3.0_1725227788331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("quiltnet_b_32_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("quiltnet_b_32_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|quiltnet_b_32_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/wisdomik/QuiltNet-B-32 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-rap_phase2_model2_31jan_10i_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-rap_phase2_model2_31jan_10i_pipeline_en.md new file mode 100644 index 00000000000000..940f6b7b233642 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-rap_phase2_model2_31jan_10i_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English rap_phase2_model2_31jan_10i_pipeline pipeline XlmRoBertaForQuestionAnswering from am-infoweb +author: John Snow Labs +name: rap_phase2_model2_31jan_10i_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rap_phase2_model2_31jan_10i_pipeline` is a English model originally trained by am-infoweb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rap_phase2_model2_31jan_10i_pipeline_en_5.4.2_3.0_1725158212397.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rap_phase2_model2_31jan_10i_pipeline_en_5.4.2_3.0_1725158212397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("rap_phase2_model2_31jan_10i_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("rap_phase2_model2_31jan_10i_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rap_phase2_model2_31jan_10i_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|802.4 MB| + +## References + +https://huggingface.co/am-infoweb/rap_phase2_MODEL2_31jan_10i + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-readability_spanish_3class_paragraphs_es.md b/docs/_posts/ahmedlone127/2024-09-01-readability_spanish_3class_paragraphs_es.md new file mode 100644 index 00000000000000..d426c35f7e7676 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-readability_spanish_3class_paragraphs_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish readability_spanish_3class_paragraphs RoBertaForSequenceClassification from somosnlp-hackathon-2022 +author: John Snow Labs +name: readability_spanish_3class_paragraphs +date: 2024-09-01 +tags: [es, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`readability_spanish_3class_paragraphs` is a Castilian, Spanish model originally trained by somosnlp-hackathon-2022. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/readability_spanish_3class_paragraphs_es_5.4.2_3.0_1725195364041.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/readability_spanish_3class_paragraphs_es_5.4.2_3.0_1725195364041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("readability_spanish_3class_paragraphs","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("readability_spanish_3class_paragraphs", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|readability_spanish_3class_paragraphs| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|441.9 MB| + +## References + +https://huggingface.co/somosnlp-hackathon-2022/readability-es-3class-paragraphs \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-readability_spanish_3class_paragraphs_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-readability_spanish_3class_paragraphs_pipeline_es.md new file mode 100644 index 00000000000000..c38c2cb7608a50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-readability_spanish_3class_paragraphs_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish readability_spanish_3class_paragraphs_pipeline pipeline RoBertaForSequenceClassification from somosnlp-hackathon-2022 +author: John Snow Labs +name: readability_spanish_3class_paragraphs_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`readability_spanish_3class_paragraphs_pipeline` is a Castilian, Spanish model originally trained by somosnlp-hackathon-2022. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/readability_spanish_3class_paragraphs_pipeline_es_5.4.2_3.0_1725195389419.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/readability_spanish_3class_paragraphs_pipeline_es_5.4.2_3.0_1725195389419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("readability_spanish_3class_paragraphs_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("readability_spanish_3class_paragraphs_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|readability_spanish_3class_paragraphs_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|442.0 MB| + +## References + +https://huggingface.co/somosnlp-hackathon-2022/readability-es-3class-paragraphs + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-refpydst_1p_referredstates_split_v2_en.md b/docs/_posts/ahmedlone127/2024-09-01-refpydst_1p_referredstates_split_v2_en.md new file mode 100644 index 00000000000000..8feede455f3967 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-refpydst_1p_referredstates_split_v2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English refpydst_1p_referredstates_split_v2 MPNetEmbeddings from Brendan +author: John Snow Labs +name: refpydst_1p_referredstates_split_v2 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`refpydst_1p_referredstates_split_v2` is a English model originally trained by Brendan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/refpydst_1p_referredstates_split_v2_en_5.5.0_3.0_1725225341180.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/refpydst_1p_referredstates_split_v2_en_5.5.0_3.0_1725225341180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("refpydst_1p_referredstates_split_v2","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("refpydst_1p_referredstates_split_v2","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|refpydst_1p_referredstates_split_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/Brendan/refpydst-1p-referredstates-split-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-refpydst_1p_referredstates_split_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-refpydst_1p_referredstates_split_v2_pipeline_en.md new file mode 100644 index 00000000000000..e32d0c1181491f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-refpydst_1p_referredstates_split_v2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English refpydst_1p_referredstates_split_v2_pipeline pipeline MPNetEmbeddings from Brendan +author: John Snow Labs +name: refpydst_1p_referredstates_split_v2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`refpydst_1p_referredstates_split_v2_pipeline` is a English model originally trained by Brendan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/refpydst_1p_referredstates_split_v2_pipeline_en_5.5.0_3.0_1725225362562.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/refpydst_1p_referredstates_split_v2_pipeline_en_5.5.0_3.0_1725225362562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("refpydst_1p_referredstates_split_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("refpydst_1p_referredstates_split_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|refpydst_1p_referredstates_split_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/Brendan/refpydst-1p-referredstates-split-v2 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-reranker_en.md b/docs/_posts/ahmedlone127/2024-09-01-reranker_en.md new file mode 100644 index 00000000000000..8da79175087d54 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-reranker_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English reranker RoBertaForSequenceClassification from hadifar +author: John Snow Labs +name: reranker +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reranker` is a English model originally trained by hadifar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reranker_en_5.4.2_3.0_1725194493426.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reranker_en_5.4.2_3.0_1725194493426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("reranker","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("reranker", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reranker| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|445.0 MB| + +## References + +https://huggingface.co/hadifar/reranker \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-reranker_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-reranker_pipeline_en.md new file mode 100644 index 00000000000000..663d1283ea9ab6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-reranker_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English reranker_pipeline pipeline RoBertaForSequenceClassification from hadifar +author: John Snow Labs +name: reranker_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reranker_pipeline` is a English model originally trained by hadifar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reranker_pipeline_en_5.4.2_3.0_1725194528017.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reranker_pipeline_en_5.4.2_3.0_1725194528017.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("reranker_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("reranker_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reranker_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|445.0 MB| + +## References + +https://huggingface.co/hadifar/reranker + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-reward_deberta_v3_base_aspect_en.md b/docs/_posts/ahmedlone127/2024-09-01-reward_deberta_v3_base_aspect_en.md new file mode 100644 index 00000000000000..7fb25b3b1e7a04 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-reward_deberta_v3_base_aspect_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English reward_deberta_v3_base_aspect DeBertaForSequenceClassification from theblackcat102 +author: John Snow Labs +name: reward_deberta_v3_base_aspect +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reward_deberta_v3_base_aspect` is a English model originally trained by theblackcat102. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reward_deberta_v3_base_aspect_en_5.4.2_3.0_1725183838252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reward_deberta_v3_base_aspect_en_5.4.2_3.0_1725183838252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("reward_deberta_v3_base_aspect","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("reward_deberta_v3_base_aspect", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reward_deberta_v3_base_aspect| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|439.5 MB| + +## References + +https://huggingface.co/theblackcat102/reward-deberta-v3-base-aspect \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-reward_deberta_v3_base_aspect_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-reward_deberta_v3_base_aspect_pipeline_en.md new file mode 100644 index 00000000000000..7b14faf00a401d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-reward_deberta_v3_base_aspect_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English reward_deberta_v3_base_aspect_pipeline pipeline DeBertaForSequenceClassification from theblackcat102 +author: John Snow Labs +name: reward_deberta_v3_base_aspect_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reward_deberta_v3_base_aspect_pipeline` is a English model originally trained by theblackcat102. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reward_deberta_v3_base_aspect_pipeline_en_5.4.2_3.0_1725183968950.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reward_deberta_v3_base_aspect_pipeline_en_5.4.2_3.0_1725183968950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("reward_deberta_v3_base_aspect_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("reward_deberta_v3_base_aspect_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reward_deberta_v3_base_aspect_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|439.5 MB| + +## References + +https://huggingface.co/theblackcat102/reward-deberta-v3-base-aspect + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-robbert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-robbert_base_pipeline_en.md new file mode 100644 index 00000000000000..d94443b6affe33 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-robbert_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English robbert_base_pipeline pipeline RoBertaEmbeddings from pdelobelle +author: John Snow Labs +name: robbert_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_base_pipeline` is a English model originally trained by pdelobelle. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_base_pipeline_en_5.4.2_3.0_1725191921750.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_base_pipeline_en_5.4.2_3.0_1725191921750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("robbert_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("robbert_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|robbert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.3 MB| + +## References + +https://huggingface.co/pdelobelle/robBERT-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_ag_news_dasoteloro_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_ag_news_dasoteloro_en.md new file mode 100644 index 00000000000000..8ec43fef6be6e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_ag_news_dasoteloro_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_ag_news_dasoteloro RoBertaForSequenceClassification from dasoteloro +author: John Snow Labs +name: roberta_base_ag_news_dasoteloro +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ag_news_dasoteloro` is a English model originally trained by dasoteloro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ag_news_dasoteloro_en_5.4.2_3.0_1725167235095.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ag_news_dasoteloro_en_5.4.2_3.0_1725167235095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_ag_news_dasoteloro","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_ag_news_dasoteloro", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_ag_news_dasoteloro| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|439.8 MB| + +## References + +https://huggingface.co/dasoteloro/roberta-base_ag_news \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_biomedical_clinical_spanish_plantl_gob_es_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_biomedical_clinical_spanish_plantl_gob_es_pipeline_es.md new file mode 100644 index 00000000000000..3b2037045971ff --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_biomedical_clinical_spanish_plantl_gob_es_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish roberta_base_biomedical_clinical_spanish_plantl_gob_es_pipeline pipeline RoBertaEmbeddings from PlanTL-GOB-ES +author: John Snow Labs +name: roberta_base_biomedical_clinical_spanish_plantl_gob_es_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_biomedical_clinical_spanish_plantl_gob_es_pipeline` is a Castilian, Spanish model originally trained by PlanTL-GOB-ES. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_plantl_gob_es_pipeline_es_5.4.2_3.0_1725186434301.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_plantl_gob_es_pipeline_es_5.4.2_3.0_1725186434301.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_biomedical_clinical_spanish_plantl_gob_es_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_biomedical_clinical_spanish_plantl_gob_es_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_biomedical_clinical_spanish_plantl_gob_es_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|299.2 MB| + +## References + +https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-clinical-es + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bne_bsc_lt_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bne_bsc_lt_pipeline_es.md new file mode 100644 index 00000000000000..db7fc6db8cbb46 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bne_bsc_lt_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish roberta_base_bne_bsc_lt_pipeline pipeline RoBertaEmbeddings from BSC-LT +author: John Snow Labs +name: roberta_base_bne_bsc_lt_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_bsc_lt_pipeline` is a Castilian, Spanish model originally trained by BSC-LT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bne_bsc_lt_pipeline_es_5.4.2_3.0_1725186185482.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_bsc_lt_pipeline_es_5.4.2_3.0_1725186185482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_bne_bsc_lt_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_bne_bsc_lt_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_bne_bsc_lt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|295.1 MB| + +## References + +https://huggingface.co/BSC-LT/roberta-base-bne + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bne_sqac_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bne_sqac_es.md new file mode 100644 index 00000000000000..d46c3dc3971190 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bne_sqac_es.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Castilian, Spanish roberta_base_bne_sqac RoBertaForQuestionAnswering from BSC-LT +author: John Snow Labs +name: roberta_base_bne_sqac +date: 2024-09-01 +tags: [es, open_source, onnx, question_answering, roberta] +task: Question Answering +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_sqac` is a Castilian, Spanish model originally trained by BSC-LT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bne_sqac_es_5.4.2_3.0_1725200010512.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_sqac_es_5.4.2_3.0_1725200010512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_bne_sqac","es") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_bne_sqac", "es") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_bne_sqac| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|es| +|Size:|459.8 MB| + +## References + +https://huggingface.co/BSC-LT/roberta-base-bne-sqac \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bne_sqac_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bne_sqac_pipeline_es.md new file mode 100644 index 00000000000000..d213d32902aa49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bne_sqac_pipeline_es.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Castilian, Spanish roberta_base_bne_sqac_pipeline pipeline RoBertaForQuestionAnswering from BSC-LT +author: John Snow Labs +name: roberta_base_bne_sqac_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_sqac_pipeline` is a Castilian, Spanish model originally trained by BSC-LT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bne_sqac_pipeline_es_5.4.2_3.0_1725200036834.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_sqac_pipeline_es_5.4.2_3.0_1725200036834.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_bne_sqac_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_bne_sqac_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_bne_sqac_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|459.8 MB| + +## References + +https://huggingface.co/BSC-LT/roberta-base-bne-sqac + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bulgarian_bg.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bulgarian_bg.md new file mode 100644 index 00000000000000..4fefa7bccf19ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bulgarian_bg.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Bulgarian roberta_base_bulgarian RoBertaEmbeddings from iarfmoose +author: John Snow Labs +name: roberta_base_bulgarian +date: 2024-09-01 +tags: [bg, open_source, onnx, embeddings, roberta] +task: Embeddings +language: bg +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bulgarian` is a Bulgarian model originally trained by iarfmoose. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bulgarian_bg_5.4.2_3.0_1725192019952.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bulgarian_bg_5.4.2_3.0_1725192019952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("roberta_base_bulgarian","bg") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("roberta_base_bulgarian","bg") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_bulgarian| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|bg| +|Size:|471.1 MB| + +## References + +https://huggingface.co/iarfmoose/roberta-base-bulgarian \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bulgarian_pipeline_bg.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bulgarian_pipeline_bg.md new file mode 100644 index 00000000000000..5f255db0422fd0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_bulgarian_pipeline_bg.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Bulgarian roberta_base_bulgarian_pipeline pipeline RoBertaEmbeddings from iarfmoose +author: John Snow Labs +name: roberta_base_bulgarian_pipeline +date: 2024-09-01 +tags: [bg, open_source, pipeline, onnx] +task: Embeddings +language: bg +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bulgarian_pipeline` is a Bulgarian model originally trained by iarfmoose. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bulgarian_pipeline_bg_5.4.2_3.0_1725192044184.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bulgarian_pipeline_bg_5.4.2_3.0_1725192044184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_bulgarian_pipeline", lang = "bg") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_bulgarian_pipeline", lang = "bg") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_bulgarian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|bg| +|Size:|471.1 MB| + +## References + +https://huggingface.co/iarfmoose/roberta-base-bulgarian + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_nlp_letters_text_all_class_weighted_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_nlp_letters_text_all_class_weighted_en.md new file mode 100644 index 00000000000000..fd926d4704a358 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_nlp_letters_text_all_class_weighted_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_finetuned_nlp_letters_text_all_class_weighted RoBertaForSequenceClassification from ben-yu +author: John Snow Labs +name: roberta_base_finetuned_nlp_letters_text_all_class_weighted +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_nlp_letters_text_all_class_weighted` is a English model originally trained by ben-yu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_nlp_letters_text_all_class_weighted_en_5.5.0_3.0_1725212845028.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_nlp_letters_text_all_class_weighted_en_5.5.0_3.0_1725212845028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_finetuned_nlp_letters_text_all_class_weighted","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_finetuned_nlp_letters_text_all_class_weighted", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_finetuned_nlp_letters_text_all_class_weighted| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|443.2 MB| + +## References + +https://huggingface.co/ben-yu/roberta-base-finetuned-nlp-letters-TEXT-all-class-weighted \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_nlp_letters_text_all_class_weighted_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_nlp_letters_text_all_class_weighted_pipeline_en.md new file mode 100644 index 00000000000000..3f34b59de8038a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_nlp_letters_text_all_class_weighted_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_finetuned_nlp_letters_text_all_class_weighted_pipeline pipeline RoBertaForSequenceClassification from ben-yu +author: John Snow Labs +name: roberta_base_finetuned_nlp_letters_text_all_class_weighted_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_nlp_letters_text_all_class_weighted_pipeline` is a English model originally trained by ben-yu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_nlp_letters_text_all_class_weighted_pipeline_en_5.5.0_3.0_1725212873636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_nlp_letters_text_all_class_weighted_pipeline_en_5.5.0_3.0_1725212873636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_finetuned_nlp_letters_text_all_class_weighted_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_finetuned_nlp_letters_text_all_class_weighted_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_finetuned_nlp_letters_text_all_class_weighted_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|443.2 MB| + +## References + +https://huggingface.co/ben-yu/roberta-base-finetuned-nlp-letters-TEXT-all-class-weighted + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_squad_arrafmousa_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_squad_arrafmousa_en.md new file mode 100644 index 00000000000000..4dbebad65e4ae9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_squad_arrafmousa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_base_finetuned_squad_arrafmousa RoBertaForQuestionAnswering from arrafmousa +author: John Snow Labs +name: roberta_base_finetuned_squad_arrafmousa +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_squad_arrafmousa` is a English model originally trained by arrafmousa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squad_arrafmousa_en_5.4.2_3.0_1725207509682.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squad_arrafmousa_en_5.4.2_3.0_1725207509682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_finetuned_squad_arrafmousa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_finetuned_squad_arrafmousa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_finetuned_squad_arrafmousa| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|427.7 MB| + +## References + +https://huggingface.co/arrafmousa/roberta-base-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_squad_arrafmousa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_squad_arrafmousa_pipeline_en.md new file mode 100644 index 00000000000000..bdb45a97a25960 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_squad_arrafmousa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_base_finetuned_squad_arrafmousa_pipeline pipeline RoBertaForQuestionAnswering from arrafmousa +author: John Snow Labs +name: roberta_base_finetuned_squad_arrafmousa_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_squad_arrafmousa_pipeline` is a English model originally trained by arrafmousa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squad_arrafmousa_pipeline_en_5.4.2_3.0_1725207542145.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squad_arrafmousa_pipeline_en_5.4.2_3.0_1725207542145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_finetuned_squad_arrafmousa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_finetuned_squad_arrafmousa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_finetuned_squad_arrafmousa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|427.7 MB| + +## References + +https://huggingface.co/arrafmousa/roberta-base-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_squad_payoto_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_squad_payoto_en.md new file mode 100644 index 00000000000000..4b37b59b83830a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_squad_payoto_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_base_finetuned_squad_payoto RoBertaForQuestionAnswering from Payoto +author: John Snow Labs +name: roberta_base_finetuned_squad_payoto +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_squad_payoto` is a English model originally trained by Payoto. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squad_payoto_en_5.4.2_3.0_1725207567659.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squad_payoto_en_5.4.2_3.0_1725207567659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_finetuned_squad_payoto","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_finetuned_squad_payoto", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_finetuned_squad_payoto| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|298.4 MB| + +## References + +https://huggingface.co/Payoto/roberta-base-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_squad_payoto_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_squad_payoto_pipeline_en.md new file mode 100644 index 00000000000000..66f3ab9a23a490 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_finetuned_squad_payoto_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_base_finetuned_squad_payoto_pipeline pipeline RoBertaForQuestionAnswering from Payoto +author: John Snow Labs +name: roberta_base_finetuned_squad_payoto_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_squad_payoto_pipeline` is a English model originally trained by Payoto. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squad_payoto_pipeline_en_5.4.2_3.0_1725207655687.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squad_payoto_pipeline_en_5.4.2_3.0_1725207655687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_finetuned_squad_payoto_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_finetuned_squad_payoto_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_finetuned_squad_payoto_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|298.4 MB| + +## References + +https://huggingface.co/Payoto/roberta-base-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_indonesian_1_5g_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_indonesian_1_5g_en.md new file mode 100644 index 00000000000000..4386779e2caeac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_indonesian_1_5g_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_indonesian_1_5g RoBertaEmbeddings from cahya +author: John Snow Labs +name: roberta_base_indonesian_1_5g +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_indonesian_1_5g` is a English model originally trained by cahya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_indonesian_1_5g_en_5.4.2_3.0_1725186920152.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_indonesian_1_5g_en_5.4.2_3.0_1725186920152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("roberta_base_indonesian_1_5g","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("roberta_base_indonesian_1_5g","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_indonesian_1_5g| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|471.0 MB| + +## References + +https://huggingface.co/cahya/roberta-base-indonesian-1.5G \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_indonesian_1_5g_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_indonesian_1_5g_pipeline_en.md new file mode 100644 index 00000000000000..908c71923170d0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_indonesian_1_5g_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_indonesian_1_5g_pipeline pipeline RoBertaEmbeddings from cahya +author: John Snow Labs +name: roberta_base_indonesian_1_5g_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_indonesian_1_5g_pipeline` is a English model originally trained by cahya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_indonesian_1_5g_pipeline_en_5.4.2_3.0_1725186946333.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_indonesian_1_5g_pipeline_en_5.4.2_3.0_1725186946333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_indonesian_1_5g_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_indonesian_1_5g_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_indonesian_1_5g_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|471.0 MB| + +## References + +https://huggingface.co/cahya/roberta-base-indonesian-1.5G + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_isarcasm_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_isarcasm_en.md new file mode 100644 index 00000000000000..cc6926b1f74e00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_isarcasm_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_isarcasm RoBertaForSequenceClassification from w11wo +author: John Snow Labs +name: roberta_base_isarcasm +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_isarcasm` is a English model originally trained by w11wo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_isarcasm_en_5.5.0_3.0_1725212194542.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_isarcasm_en_5.5.0_3.0_1725212194542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_isarcasm","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_isarcasm", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_isarcasm| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|432.9 MB| + +## References + +https://huggingface.co/w11wo/roberta-base-isarcasm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_isarcasm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_isarcasm_pipeline_en.md new file mode 100644 index 00000000000000..e258af784f63bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_isarcasm_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_isarcasm_pipeline pipeline RoBertaForSequenceClassification from w11wo +author: John Snow Labs +name: roberta_base_isarcasm_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_isarcasm_pipeline` is a English model originally trained by w11wo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_isarcasm_pipeline_en_5.5.0_3.0_1725212231249.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_isarcasm_pipeline_en_5.5.0_3.0_1725212231249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_isarcasm_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_isarcasm_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_isarcasm_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|432.9 MB| + +## References + +https://huggingface.co/w11wo/roberta-base-isarcasm + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_model_attribution_challenge_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_model_attribution_challenge_pipeline_en.md new file mode 100644 index 00000000000000..9558c45bb6e218 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_model_attribution_challenge_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_model_attribution_challenge_pipeline pipeline RoBertaEmbeddings from model-attribution-challenge +author: John Snow Labs +name: roberta_base_model_attribution_challenge_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_model_attribution_challenge_pipeline` is a English model originally trained by model-attribution-challenge. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_model_attribution_challenge_pipeline_en_5.4.2_3.0_1725191670862.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_model_attribution_challenge_pipeline_en_5.4.2_3.0_1725191670862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_model_attribution_challenge_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_model_attribution_challenge_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_model_attribution_challenge_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|298.2 MB| + +## References + +https://huggingface.co/model-attribution-challenge/roberta-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_rotten_tomatoes_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_rotten_tomatoes_en.md new file mode 100644 index 00000000000000..4239d408305484 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_rotten_tomatoes_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English roberta_base_rotten_tomatoes RoBertaForSequenceClassification from textattack +author: John Snow Labs +name: roberta_base_rotten_tomatoes +date: 2024-09-01 +tags: [roberta, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_rotten_tomatoes` is a English model originally trained by textattack. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_rotten_tomatoes_en_5.4.2_3.0_1725191100513.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_rotten_tomatoes_en_5.4.2_3.0_1725191100513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_rotten_tomatoes","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_rotten_tomatoes","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_rotten_tomatoes| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|442.3 MB| + +## References + +References + +https://huggingface.co/textattack/roberta-base-rotten-tomatoes \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_rotten_tomatoes_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_rotten_tomatoes_pipeline_en.md new file mode 100644 index 00000000000000..f93fcba098434a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_rotten_tomatoes_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_rotten_tomatoes_pipeline pipeline RoBertaEmbeddings from textattack +author: John Snow Labs +name: roberta_base_rotten_tomatoes_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_rotten_tomatoes_pipeline` is a English model originally trained by textattack. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_rotten_tomatoes_pipeline_en_5.4.2_3.0_1725191126677.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_rotten_tomatoes_pipeline_en_5.4.2_3.0_1725191126677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_rotten_tomatoes_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_rotten_tomatoes_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_rotten_tomatoes_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|442.3 MB| + +## References + +https://huggingface.co/textattack/roberta-base-rotten_tomatoes + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad2_finetuned_ema_qa_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad2_finetuned_ema_qa_en.md new file mode 100644 index 00000000000000..e1c2a5bda6d7cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad2_finetuned_ema_qa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_base_squad2_finetuned_ema_qa RoBertaForQuestionAnswering from ngchuchi +author: John Snow Labs +name: roberta_base_squad2_finetuned_ema_qa +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad2_finetuned_ema_qa` is a English model originally trained by ngchuchi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_ema_qa_en_5.4.2_3.0_1725206590476.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_ema_qa_en_5.4.2_3.0_1725206590476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad2_finetuned_ema_qa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad2_finetuned_ema_qa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_squad2_finetuned_ema_qa| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/ngchuchi/roberta-base-squad2-finetuned-ema-qa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad2_finetuned_ema_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad2_finetuned_ema_qa_pipeline_en.md new file mode 100644 index 00000000000000..e7d8589ddd4c2b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad2_finetuned_ema_qa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_base_squad2_finetuned_ema_qa_pipeline pipeline RoBertaForQuestionAnswering from ngchuchi +author: John Snow Labs +name: roberta_base_squad2_finetuned_ema_qa_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad2_finetuned_ema_qa_pipeline` is a English model originally trained by ngchuchi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_ema_qa_pipeline_en_5.4.2_3.0_1725206620366.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_ema_qa_pipeline_en_5.4.2_3.0_1725206620366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_squad2_finetuned_ema_qa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_squad2_finetuned_ema_qa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_squad2_finetuned_ema_qa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/ngchuchi/roberta-base-squad2-finetuned-ema-qa + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad2_finetuned_newqa1_ericpeter_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad2_finetuned_newqa1_ericpeter_en.md new file mode 100644 index 00000000000000..4b5861fe1d70cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad2_finetuned_newqa1_ericpeter_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_base_squad2_finetuned_newqa1_ericpeter RoBertaForQuestionAnswering from EricPeter +author: John Snow Labs +name: roberta_base_squad2_finetuned_newqa1_ericpeter +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad2_finetuned_newqa1_ericpeter` is a English model originally trained by EricPeter. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_newqa1_ericpeter_en_5.4.2_3.0_1725206411447.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_newqa1_ericpeter_en_5.4.2_3.0_1725206411447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad2_finetuned_newqa1_ericpeter","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad2_finetuned_newqa1_ericpeter", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_squad2_finetuned_newqa1_ericpeter| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/EricPeter/roberta-base-squad2-finetuned-newqa1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad_i8_f32_p85_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad_i8_f32_p85_en.md new file mode 100644 index 00000000000000..a91326eb870e79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad_i8_f32_p85_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_base_squad_i8_f32_p85 RoBertaForQuestionAnswering from pminha +author: John Snow Labs +name: roberta_base_squad_i8_f32_p85 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad_i8_f32_p85` is a English model originally trained by pminha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_squad_i8_f32_p85_en_5.4.2_3.0_1725207285706.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad_i8_f32_p85_en_5.4.2_3.0_1725207285706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad_i8_f32_p85","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad_i8_f32_p85", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_squad_i8_f32_p85| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|180.5 MB| + +## References + +https://huggingface.co/pminha/roberta-base-squad-i8-f32-p85 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad_i8_f32_p85_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad_i8_f32_p85_pipeline_en.md new file mode 100644 index 00000000000000..f3efa56bc8904c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad_i8_f32_p85_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_base_squad_i8_f32_p85_pipeline pipeline RoBertaForQuestionAnswering from pminha +author: John Snow Labs +name: roberta_base_squad_i8_f32_p85_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad_i8_f32_p85_pipeline` is a English model originally trained by pminha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_squad_i8_f32_p85_pipeline_en_5.4.2_3.0_1725207302678.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad_i8_f32_p85_pipeline_en_5.4.2_3.0_1725207302678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_squad_i8_f32_p85_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_squad_i8_f32_p85_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_squad_i8_f32_p85_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|180.5 MB| + +## References + +https://huggingface.co/pminha/roberta-base-squad-i8-f32-p85 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_tweets_hate_speech_detection_saved_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_tweets_hate_speech_detection_saved_en.md new file mode 100644 index 00000000000000..60ca97017e197f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_tweets_hate_speech_detection_saved_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_tweets_hate_speech_detection_saved RoBertaForSequenceClassification from thaile +author: John Snow Labs +name: roberta_base_tweets_hate_speech_detection_saved +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_tweets_hate_speech_detection_saved` is a English model originally trained by thaile. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_tweets_hate_speech_detection_saved_en_5.5.0_3.0_1725212770843.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_tweets_hate_speech_detection_saved_en_5.5.0_3.0_1725212770843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_tweets_hate_speech_detection_saved","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_tweets_hate_speech_detection_saved", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_tweets_hate_speech_detection_saved| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|446.2 MB| + +## References + +https://huggingface.co/thaile/roberta-base-tweets_hate_speech_detection-saved \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_tweets_hate_speech_detection_saved_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_tweets_hate_speech_detection_saved_pipeline_en.md new file mode 100644 index 00000000000000..59218508b90f28 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_tweets_hate_speech_detection_saved_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_tweets_hate_speech_detection_saved_pipeline pipeline RoBertaForSequenceClassification from thaile +author: John Snow Labs +name: roberta_base_tweets_hate_speech_detection_saved_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_tweets_hate_speech_detection_saved_pipeline` is a English model originally trained by thaile. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_tweets_hate_speech_detection_saved_pipeline_en_5.5.0_3.0_1725212799620.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_tweets_hate_speech_detection_saved_pipeline_en_5.5.0_3.0_1725212799620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_tweets_hate_speech_detection_saved_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_tweets_hate_speech_detection_saved_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_tweets_hate_speech_detection_saved_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|446.2 MB| + +## References + +https://huggingface.co/thaile/roberta-base-tweets_hate_speech_detection-saved + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_wechsel_swahili_pipeline_sw.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_wechsel_swahili_pipeline_sw.md new file mode 100644 index 00000000000000..1cb4f90f2b10da --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_wechsel_swahili_pipeline_sw.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Swahili (macrolanguage) roberta_base_wechsel_swahili_pipeline pipeline RoBertaEmbeddings from benjamin +author: John Snow Labs +name: roberta_base_wechsel_swahili_pipeline +date: 2024-09-01 +tags: [sw, open_source, pipeline, onnx] +task: Embeddings +language: sw +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_wechsel_swahili_pipeline` is a Swahili (macrolanguage) model originally trained by benjamin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_wechsel_swahili_pipeline_sw_5.4.2_3.0_1725191244854.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_wechsel_swahili_pipeline_sw_5.4.2_3.0_1725191244854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_wechsel_swahili_pipeline", lang = "sw") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_wechsel_swahili_pipeline", lang = "sw") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_wechsel_swahili_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|sw| +|Size:|465.7 MB| + +## References + +https://huggingface.co/benjamin/roberta-base-wechsel-swahili + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_classifier_autonlp_large2_479012819_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_classifier_autonlp_large2_479012819_en.md new file mode 100644 index 00000000000000..222d60422a7c3c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_classifier_autonlp_large2_479012819_en.md @@ -0,0 +1,104 @@ +--- +layout: model +title: English RoBertaForSequenceClassification Large Cased model (from sam890914) +author: John Snow Labs +name: roberta_classifier_autonlp_large2_479012819 +date: 2024-09-01 +tags: [en, open_source, roberta, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-roberta-large2-479012819` is a English model originally trained by `sam890914`. + +## Predicted Entities + +`0`, `1` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_autonlp_large2_479012819_en_5.4.2_3.0_1725194490547.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_autonlp_large2_479012819_en_5.4.2_3.0_1725194490547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_autonlp_large2_479012819","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_autonlp_large2_479012819","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.roberta.large.by_sam890914").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_autonlp_large2_479012819| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +References + +- https://huggingface.co/sam890914/autonlp-roberta-large2-479012819 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_classifier_autonlp_large2_479012819_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_classifier_autonlp_large2_479012819_pipeline_en.md new file mode 100644 index 00000000000000..9fc63ada24333f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_classifier_autonlp_large2_479012819_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_classifier_autonlp_large2_479012819_pipeline pipeline RoBertaForSequenceClassification from sam890914 +author: John Snow Labs +name: roberta_classifier_autonlp_large2_479012819_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classifier_autonlp_large2_479012819_pipeline` is a English model originally trained by sam890914. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_autonlp_large2_479012819_pipeline_en_5.4.2_3.0_1725194569526.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_autonlp_large2_479012819_pipeline_en_5.4.2_3.0_1725194569526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_classifier_autonlp_large2_479012819_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_classifier_autonlp_large2_479012819_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_autonlp_large2_479012819_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/sam890914/autonlp-roberta-large2-479012819 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_classifier_emotion_english_distil_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_classifier_emotion_english_distil_base_pipeline_en.md new file mode 100644 index 00000000000000..787a1adee157b5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_classifier_emotion_english_distil_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_classifier_emotion_english_distil_base_pipeline pipeline RoBertaForSequenceClassification from j-hartmann +author: John Snow Labs +name: roberta_classifier_emotion_english_distil_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classifier_emotion_english_distil_base_pipeline` is a English model originally trained by j-hartmann. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_emotion_english_distil_base_pipeline_en_5.4.2_3.0_1725167920607.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_emotion_english_distil_base_pipeline_en_5.4.2_3.0_1725167920607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_classifier_emotion_english_distil_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_classifier_emotion_english_distil_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_emotion_english_distil_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|308.9 MB| + +## References + +https://huggingface.co/j-hartmann/emotion-english-distilroberta-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_country_neg_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_country_neg_en.md new file mode 100644 index 00000000000000..0fdf6841bc35bf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_country_neg_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_finetuned_country_neg RoBertaForQuestionAnswering from svo2 +author: John Snow Labs +name: roberta_finetuned_country_neg +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_country_neg` is a English model originally trained by svo2. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_country_neg_en_5.4.2_3.0_1725206549455.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_country_neg_en_5.4.2_3.0_1725206549455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_country_neg","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_country_neg", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_country_neg| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|464.4 MB| + +## References + +https://huggingface.co/svo2/roberta-finetuned-country-neg \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_country_neg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_country_neg_pipeline_en.md new file mode 100644 index 00000000000000..64ee46e3340bfc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_country_neg_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_finetuned_country_neg_pipeline pipeline RoBertaForQuestionAnswering from svo2 +author: John Snow Labs +name: roberta_finetuned_country_neg_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_country_neg_pipeline` is a English model originally trained by svo2. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_country_neg_pipeline_en_5.4.2_3.0_1725206579712.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_country_neg_pipeline_en_5.4.2_3.0_1725206579712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_finetuned_country_neg_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_finetuned_country_neg_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_country_neg_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|464.4 MB| + +## References + +https://huggingface.co/svo2/roberta-finetuned-country-neg + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_state2_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_state2_en.md new file mode 100644 index 00000000000000..6a63199ca022ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_state2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_finetuned_state2 RoBertaForQuestionAnswering from svo2 +author: John Snow Labs +name: roberta_finetuned_state2 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_state2` is a English model originally trained by svo2. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_state2_en_5.4.2_3.0_1725200102841.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_state2_en_5.4.2_3.0_1725200102841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_state2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_state2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_state2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.8 MB| + +## References + +https://huggingface.co/svo2/roberta-finetuned-state2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_state2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_state2_pipeline_en.md new file mode 100644 index 00000000000000..47cd426d648e9b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_state2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_finetuned_state2_pipeline pipeline RoBertaForQuestionAnswering from svo2 +author: John Snow Labs +name: roberta_finetuned_state2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_state2_pipeline` is a English model originally trained by svo2. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_state2_pipeline_en_5.4.2_3.0_1725200128413.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_state2_pipeline_en_5.4.2_3.0_1725200128413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_finetuned_state2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_finetuned_state2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_state2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.8 MB| + +## References + +https://huggingface.co/svo2/roberta-finetuned-state2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_chennaiqa_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_chennaiqa_en.md new file mode 100644 index 00000000000000..d8d2132a6df9cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_chennaiqa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_chennaiqa RoBertaForQuestionAnswering from aditi2212 +author: John Snow Labs +name: roberta_finetuned_subjqa_chennaiqa +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_chennaiqa` is a English model originally trained by aditi2212. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_chennaiqa_en_5.4.2_3.0_1725200449885.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_chennaiqa_en_5.4.2_3.0_1725200449885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_chennaiqa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_chennaiqa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_chennaiqa| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/aditi2212/roberta-finetuned-subjqa-ChennaiQA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_chennaiqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_chennaiqa_pipeline_en.md new file mode 100644 index 00000000000000..d37b457aff3982 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_chennaiqa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_chennaiqa_pipeline pipeline RoBertaForQuestionAnswering from aditi2212 +author: John Snow Labs +name: roberta_finetuned_subjqa_chennaiqa_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_chennaiqa_pipeline` is a English model originally trained by aditi2212. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_chennaiqa_pipeline_en_5.4.2_3.0_1725200477165.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_chennaiqa_pipeline_en_5.4.2_3.0_1725200477165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_finetuned_subjqa_chennaiqa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_chennaiqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_chennaiqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/aditi2212/roberta-finetuned-subjqa-ChennaiQA + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_abhijitstat_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_abhijitstat_en.md new file mode 100644 index 00000000000000..12e7047a175187 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_abhijitstat_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_abhijitstat RoBertaForQuestionAnswering from abhijitstat +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_abhijitstat +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_abhijitstat` is a English model originally trained by abhijitstat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_abhijitstat_en_5.4.2_3.0_1725206926625.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_abhijitstat_en_5.4.2_3.0_1725206926625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_abhijitstat","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_abhijitstat", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_abhijitstat| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/abhijitstat/roberta-finetuned-subjqa-movies_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_abhijitstat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_abhijitstat_pipeline_en.md new file mode 100644 index 00000000000000..a1459c11d2f7bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_abhijitstat_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_abhijitstat_pipeline pipeline RoBertaForQuestionAnswering from abhijitstat +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_abhijitstat_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_abhijitstat_pipeline` is a English model originally trained by abhijitstat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_abhijitstat_pipeline_en_5.4.2_3.0_1725206952615.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_abhijitstat_pipeline_en_5.4.2_3.0_1725206952615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_finetuned_subjqa_movies_2_abhijitstat_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_movies_2_abhijitstat_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_abhijitstat_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/abhijitstat/roberta-finetuned-subjqa-movies_2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_bharathkumarms_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_bharathkumarms_en.md new file mode 100644 index 00000000000000..44252dc8728da3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_bharathkumarms_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_bharathkumarms RoBertaForQuestionAnswering from bharathkumarms +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_bharathkumarms +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_bharathkumarms` is a English model originally trained by bharathkumarms. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_bharathkumarms_en_5.4.2_3.0_1725206737310.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_bharathkumarms_en_5.4.2_3.0_1725206737310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_bharathkumarms","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_bharathkumarms", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_bharathkumarms| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/bharathkumarms/roberta-finetuned-subjqa-movies_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_bharathkumarms_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_bharathkumarms_pipeline_en.md new file mode 100644 index 00000000000000..7a4a0b90d05f39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_bharathkumarms_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_bharathkumarms_pipeline pipeline RoBertaForQuestionAnswering from bharathkumarms +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_bharathkumarms_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_bharathkumarms_pipeline` is a English model originally trained by bharathkumarms. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_bharathkumarms_pipeline_en_5.4.2_3.0_1725206770104.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_bharathkumarms_pipeline_en_5.4.2_3.0_1725206770104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_finetuned_subjqa_movies_2_bharathkumarms_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_movies_2_bharathkumarms_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_bharathkumarms_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/bharathkumarms/roberta-finetuned-subjqa-movies_2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_chingoduc_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_chingoduc_en.md new file mode 100644 index 00000000000000..1b97b03edc12a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_chingoduc_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_chingoduc RoBertaForQuestionAnswering from chingoduc +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_chingoduc +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_chingoduc` is a English model originally trained by chingoduc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_chingoduc_en_5.4.2_3.0_1725206711506.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_chingoduc_en_5.4.2_3.0_1725206711506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_chingoduc","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_chingoduc", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_chingoduc| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/chingoduc/roberta-finetuned-subjqa-movies_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_chingoduc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_chingoduc_pipeline_en.md new file mode 100644 index 00000000000000..5c21f685736683 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_chingoduc_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_chingoduc_pipeline pipeline RoBertaForQuestionAnswering from chingoduc +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_chingoduc_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_chingoduc_pipeline` is a English model originally trained by chingoduc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_chingoduc_pipeline_en_5.4.2_3.0_1725206737269.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_chingoduc_pipeline_en_5.4.2_3.0_1725206737269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_finetuned_subjqa_movies_2_chingoduc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_movies_2_chingoduc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_chingoduc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/chingoduc/roberta-finetuned-subjqa-movies_2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_mustafa1923_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_mustafa1923_pipeline_en.md new file mode 100644 index 00000000000000..ab77f19e573851 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_finetuned_subjqa_movies_2_mustafa1923_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_mustafa1923_pipeline pipeline RoBertaForQuestionAnswering from mustafa1923 +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_mustafa1923_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_mustafa1923_pipeline` is a English model originally trained by mustafa1923. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_mustafa1923_pipeline_en_5.4.2_3.0_1725206898887.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_mustafa1923_pipeline_en_5.4.2_3.0_1725206898887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_finetuned_subjqa_movies_2_mustafa1923_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_movies_2_mustafa1923_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_mustafa1923_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/mustafa1923/roberta-finetuned-subjqa-movies_2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_1160k_pipeline_sv.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_1160k_pipeline_sv.md new file mode 100644 index 00000000000000..546cbf69377070 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_1160k_pipeline_sv.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Swedish roberta_large_1160k_pipeline pipeline RoBertaEmbeddings from AI-Sweden-Models +author: John Snow Labs +name: roberta_large_1160k_pipeline +date: 2024-09-01 +tags: [sv, open_source, pipeline, onnx] +task: Embeddings +language: sv +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_1160k_pipeline` is a Swedish model originally trained by AI-Sweden-Models. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_1160k_pipeline_sv_5.4.2_3.0_1725186923941.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_1160k_pipeline_sv_5.4.2_3.0_1725186923941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_1160k_pipeline", lang = "sv") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_1160k_pipeline", lang = "sv") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_1160k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|sv| +|Size:|1.3 GB| + +## References + +https://huggingface.co/AI-Sweden-Models/roberta-large-1160k + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_1160k_sv.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_1160k_sv.md new file mode 100644 index 00000000000000..18f0770956fff5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_1160k_sv.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Swedish roberta_large_1160k RoBertaEmbeddings from AI-Sweden-Models +author: John Snow Labs +name: roberta_large_1160k +date: 2024-09-01 +tags: [sv, open_source, onnx, embeddings, roberta] +task: Embeddings +language: sv +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_1160k` is a Swedish model originally trained by AI-Sweden-Models. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_1160k_sv_5.4.2_3.0_1725186856007.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_1160k_sv_5.4.2_3.0_1725186856007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("roberta_large_1160k","sv") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("roberta_large_1160k","sv") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_1160k| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|sv| +|Size:|1.3 GB| + +## References + +https://huggingface.co/AI-Sweden-Models/roberta-large-1160k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_bne_massive_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_bne_massive_pipeline_es.md new file mode 100644 index 00000000000000..1294a66075798e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_bne_massive_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish roberta_large_bne_massive_pipeline pipeline RoBertaForSequenceClassification from PlanTL-GOB-ES +author: John Snow Labs +name: roberta_large_bne_massive_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_bne_massive_pipeline` is a Castilian, Spanish model originally trained by PlanTL-GOB-ES. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_bne_massive_pipeline_es_5.4.2_3.0_1725167584740.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_bne_massive_pipeline_es_5.4.2_3.0_1725167584740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_bne_massive_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_bne_massive_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_bne_massive_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|1.3 GB| + +## References + +https://huggingface.co/PlanTL-GOB-ES/roberta-large-bne-massive + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_data_seed_2_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_data_seed_2_en.md new file mode 100644 index 00000000000000..14f28bd10a127c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_data_seed_2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_large_data_seed_2 RoBertaForQuestionAnswering from anas-awadalla +author: John Snow Labs +name: roberta_large_data_seed_2 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_data_seed_2` is a English model originally trained by anas-awadalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_data_seed_2_en_5.4.2_3.0_1725207077260.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_data_seed_2_en_5.4.2_3.0_1725207077260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_data_seed_2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_data_seed_2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_data_seed_2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/anas-awadalla/roberta-large-data-seed-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_data_seed_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_data_seed_2_pipeline_en.md new file mode 100644 index 00000000000000..1e3b745bdfd686 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_data_seed_2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_large_data_seed_2_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla +author: John Snow Labs +name: roberta_large_data_seed_2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_data_seed_2_pipeline` is a English model originally trained by anas-awadalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_data_seed_2_pipeline_en_5.4.2_3.0_1725207156144.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_data_seed_2_pipeline_en_5.4.2_3.0_1725207156144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_data_seed_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_data_seed_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_data_seed_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/anas-awadalla/roberta-large-data-seed-2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_1024_finetuned_squad_seed_0_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_1024_finetuned_squad_seed_0_en.md new file mode 100644 index 00000000000000..058fd2e25b9a56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_1024_finetuned_squad_seed_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_large_few_shot_k_1024_finetuned_squad_seed_0 RoBertaForQuestionAnswering from anas-awadalla +author: John Snow Labs +name: roberta_large_few_shot_k_1024_finetuned_squad_seed_0 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_few_shot_k_1024_finetuned_squad_seed_0` is a English model originally trained by anas-awadalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_1024_finetuned_squad_seed_0_en_5.4.2_3.0_1725207171625.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_1024_finetuned_squad_seed_0_en_5.4.2_3.0_1725207171625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_few_shot_k_1024_finetuned_squad_seed_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_few_shot_k_1024_finetuned_squad_seed_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_few_shot_k_1024_finetuned_squad_seed_0| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/anas-awadalla/roberta-large-few-shot-k-1024-finetuned-squad-seed-0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_1024_finetuned_squad_seed_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_1024_finetuned_squad_seed_0_pipeline_en.md new file mode 100644 index 00000000000000..8164b877b1adb1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_1024_finetuned_squad_seed_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_large_few_shot_k_1024_finetuned_squad_seed_0_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla +author: John Snow Labs +name: roberta_large_few_shot_k_1024_finetuned_squad_seed_0_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_few_shot_k_1024_finetuned_squad_seed_0_pipeline` is a English model originally trained by anas-awadalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_1024_finetuned_squad_seed_0_pipeline_en_5.4.2_3.0_1725207258369.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_1024_finetuned_squad_seed_0_pipeline_en_5.4.2_3.0_1725207258369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_few_shot_k_1024_finetuned_squad_seed_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_few_shot_k_1024_finetuned_squad_seed_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_few_shot_k_1024_finetuned_squad_seed_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/anas-awadalla/roberta-large-few-shot-k-1024-finetuned-squad-seed-0 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_16_finetuned_squad_seed_2_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_16_finetuned_squad_seed_2_en.md new file mode 100644 index 00000000000000..4b6dea30e5705c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_16_finetuned_squad_seed_2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_large_few_shot_k_16_finetuned_squad_seed_2 RoBertaForQuestionAnswering from anas-awadalla +author: John Snow Labs +name: roberta_large_few_shot_k_16_finetuned_squad_seed_2 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_few_shot_k_16_finetuned_squad_seed_2` is a English model originally trained by anas-awadalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_16_finetuned_squad_seed_2_en_5.4.2_3.0_1725200136242.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_16_finetuned_squad_seed_2_en_5.4.2_3.0_1725200136242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_few_shot_k_16_finetuned_squad_seed_2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_few_shot_k_16_finetuned_squad_seed_2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_few_shot_k_16_finetuned_squad_seed_2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/anas-awadalla/roberta-large-few-shot-k-16-finetuned-squad-seed-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_16_finetuned_squad_seed_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_16_finetuned_squad_seed_2_pipeline_en.md new file mode 100644 index 00000000000000..245d4c24cac731 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_16_finetuned_squad_seed_2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_large_few_shot_k_16_finetuned_squad_seed_2_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla +author: John Snow Labs +name: roberta_large_few_shot_k_16_finetuned_squad_seed_2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_few_shot_k_16_finetuned_squad_seed_2_pipeline` is a English model originally trained by anas-awadalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_16_finetuned_squad_seed_2_pipeline_en_5.4.2_3.0_1725200231510.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_16_finetuned_squad_seed_2_pipeline_en_5.4.2_3.0_1725200231510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_few_shot_k_16_finetuned_squad_seed_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_few_shot_k_16_finetuned_squad_seed_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_few_shot_k_16_finetuned_squad_seed_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/anas-awadalla/roberta-large-few-shot-k-16-finetuned-squad-seed-2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_64_finetuned_squad_seed_0_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_64_finetuned_squad_seed_0_en.md new file mode 100644 index 00000000000000..33ddf088c96a47 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_64_finetuned_squad_seed_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_large_few_shot_k_64_finetuned_squad_seed_0 RoBertaForQuestionAnswering from anas-awadalla +author: John Snow Labs +name: roberta_large_few_shot_k_64_finetuned_squad_seed_0 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_few_shot_k_64_finetuned_squad_seed_0` is a English model originally trained by anas-awadalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_64_finetuned_squad_seed_0_en_5.4.2_3.0_1725207323178.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_64_finetuned_squad_seed_0_en_5.4.2_3.0_1725207323178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_few_shot_k_64_finetuned_squad_seed_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_few_shot_k_64_finetuned_squad_seed_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_few_shot_k_64_finetuned_squad_seed_0| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/anas-awadalla/roberta-large-few-shot-k-64-finetuned-squad-seed-0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_64_finetuned_squad_seed_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_64_finetuned_squad_seed_0_pipeline_en.md new file mode 100644 index 00000000000000..71eb29d61b67bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_few_shot_k_64_finetuned_squad_seed_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_large_few_shot_k_64_finetuned_squad_seed_0_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla +author: John Snow Labs +name: roberta_large_few_shot_k_64_finetuned_squad_seed_0_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_few_shot_k_64_finetuned_squad_seed_0_pipeline` is a English model originally trained by anas-awadalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_64_finetuned_squad_seed_0_pipeline_en_5.4.2_3.0_1725207422058.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_64_finetuned_squad_seed_0_pipeline_en_5.4.2_3.0_1725207422058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_few_shot_k_64_finetuned_squad_seed_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_few_shot_k_64_finetuned_squad_seed_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_few_shot_k_64_finetuned_squad_seed_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/anas-awadalla/roberta-large-few-shot-k-64-finetuned-squad-seed-0 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_goemotions_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_goemotions_en.md new file mode 100644 index 00000000000000..db9cfa80ae3435 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_goemotions_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_large_goemotions RoBertaForSequenceClassification from IsaacZhy +author: John Snow Labs +name: roberta_large_goemotions +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_goemotions` is a English model originally trained by IsaacZhy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_goemotions_en_5.4.2_3.0_1725195137921.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_goemotions_en_5.4.2_3.0_1725195137921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_goemotions","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_goemotions", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_goemotions| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/IsaacZhy/roberta-large-goemotions \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_goemotions_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_goemotions_pipeline_en.md new file mode 100644 index 00000000000000..27423adb145b5b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_goemotions_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_large_goemotions_pipeline pipeline RoBertaForSequenceClassification from IsaacZhy +author: John Snow Labs +name: roberta_large_goemotions_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_goemotions_pipeline` is a English model originally trained by IsaacZhy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_goemotions_pipeline_en_5.4.2_3.0_1725195215100.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_goemotions_pipeline_en_5.4.2_3.0_1725195215100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_goemotions_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_goemotions_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_goemotions_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/IsaacZhy/roberta-large-goemotions + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_mnli_facebookai_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_mnli_facebookai_en.md new file mode 100644 index 00000000000000..0ff739c21aba2a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_mnli_facebookai_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_large_mnli_facebookai RoBertaForSequenceClassification from FacebookAI +author: John Snow Labs +name: roberta_large_mnli_facebookai +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_mnli_facebookai` is a English model originally trained by FacebookAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_mnli_facebookai_en_5.4.2_3.0_1725194398038.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_mnli_facebookai_en_5.4.2_3.0_1725194398038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_mnli_facebookai","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_mnli_facebookai", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_mnli_facebookai| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|845.5 MB| + +## References + +https://huggingface.co/FacebookAI/roberta-large-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_mnli_facebookai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_mnli_facebookai_pipeline_en.md new file mode 100644 index 00000000000000..3380eace990215 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_mnli_facebookai_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_large_mnli_facebookai_pipeline pipeline RoBertaForSequenceClassification from FacebookAI +author: John Snow Labs +name: roberta_large_mnli_facebookai_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_mnli_facebookai_pipeline` is a English model originally trained by FacebookAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_mnli_facebookai_pipeline_en_5.4.2_3.0_1725194657950.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_mnli_facebookai_pipeline_en_5.4.2_3.0_1725194657950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_mnli_facebookai_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_mnli_facebookai_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_mnli_facebookai_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|845.5 MB| + +## References + +https://huggingface.co/FacebookAI/roberta-large-mnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_snli_pepa_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_snli_pepa_en.md new file mode 100644 index 00000000000000..8477c34a0d0101 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_snli_pepa_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_large_snli_pepa RoBertaForSequenceClassification from pepa +author: John Snow Labs +name: roberta_large_snli_pepa +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_snli_pepa` is a English model originally trained by pepa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_snli_pepa_en_5.4.2_3.0_1725167983934.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_snli_pepa_en_5.4.2_3.0_1725167983934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_snli_pepa","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_snli_pepa", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_snli_pepa| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/pepa/roberta-large-snli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad1_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad1_en.md new file mode 100644 index 00000000000000..f70a6e581f9f6a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_large_squad1 RoBertaForQuestionAnswering from Dingyun-Huang +author: John Snow Labs +name: roberta_large_squad1 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squad1` is a English model originally trained by Dingyun-Huang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_squad1_en_5.4.2_3.0_1725207622130.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squad1_en_5.4.2_3.0_1725207622130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squad1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squad1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_squad1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Dingyun-Huang/roberta-large-squad1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad1_pipeline_en.md new file mode 100644 index 00000000000000..254f0b0f474d66 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_large_squad1_pipeline pipeline RoBertaForQuestionAnswering from Dingyun-Huang +author: John Snow Labs +name: roberta_large_squad1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squad1_pipeline` is a English model originally trained by Dingyun-Huang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_squad1_pipeline_en_5.4.2_3.0_1725207706944.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squad1_pipeline_en_5.4.2_3.0_1725207706944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_squad1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_squad1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_squad1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Dingyun-Huang/roberta-large-squad1 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad2_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad2_en.md new file mode 100644 index 00000000000000..d29f0b936717d5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_large_squad2 RoBertaForQuestionAnswering from deepset +author: John Snow Labs +name: roberta_large_squad2 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squad2` is a English model originally trained by deepset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_squad2_en_5.4.2_3.0_1725200929689.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squad2_en_5.4.2_3.0_1725200929689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squad2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squad2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_squad2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/deepset/roberta-large-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad2_fine_tuned_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad2_fine_tuned_en.md new file mode 100644 index 00000000000000..1bc7f3c0b4b91e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad2_fine_tuned_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_large_squad2_fine_tuned RoBertaForQuestionAnswering from marwanimroz18 +author: John Snow Labs +name: roberta_large_squad2_fine_tuned +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squad2_fine_tuned` is a English model originally trained by marwanimroz18. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_squad2_fine_tuned_en_5.4.2_3.0_1725206808915.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squad2_fine_tuned_en_5.4.2_3.0_1725206808915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squad2_fine_tuned","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squad2_fine_tuned", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_squad2_fine_tuned| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/marwanimroz18/roberta-large-squad2-fine-tuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad2_fine_tuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad2_fine_tuned_pipeline_en.md new file mode 100644 index 00000000000000..6bc7a70fabd51d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad2_fine_tuned_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_large_squad2_fine_tuned_pipeline pipeline RoBertaForQuestionAnswering from marwanimroz18 +author: John Snow Labs +name: roberta_large_squad2_fine_tuned_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squad2_fine_tuned_pipeline` is a English model originally trained by marwanimroz18. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_squad2_fine_tuned_pipeline_en_5.4.2_3.0_1725206890116.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squad2_fine_tuned_pipeline_en_5.4.2_3.0_1725206890116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_squad2_fine_tuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_squad2_fine_tuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_squad2_fine_tuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/marwanimroz18/roberta-large-squad2-fine-tuned + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad2_pipeline_en.md new file mode 100644 index 00000000000000..ecaf7fc2f14797 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_large_squad2_pipeline pipeline RoBertaForQuestionAnswering from deepset +author: John Snow Labs +name: roberta_large_squad2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squad2_pipeline` is a English model originally trained by deepset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_squad2_pipeline_en_5.4.2_3.0_1725201001974.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squad2_pipeline_en_5.4.2_3.0_1725201001974.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_squad2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_squad2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_squad2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/deepset/roberta-large-squad2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad_gaotianyu1350_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad_gaotianyu1350_en.md new file mode 100644 index 00000000000000..3aaad0e764f9db --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad_gaotianyu1350_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_large_squad_gaotianyu1350 RoBertaForQuestionAnswering from gaotianyu1350 +author: John Snow Labs +name: roberta_large_squad_gaotianyu1350 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squad_gaotianyu1350` is a English model originally trained by gaotianyu1350. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_squad_gaotianyu1350_en_5.4.2_3.0_1725201095323.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squad_gaotianyu1350_en_5.4.2_3.0_1725201095323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squad_gaotianyu1350","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squad_gaotianyu1350", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_squad_gaotianyu1350| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/gaotianyu1350/roberta-large-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad_gaotianyu1350_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad_gaotianyu1350_pipeline_en.md new file mode 100644 index 00000000000000..00bd87cdca45a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_large_squad_gaotianyu1350_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_large_squad_gaotianyu1350_pipeline pipeline RoBertaForQuestionAnswering from gaotianyu1350 +author: John Snow Labs +name: roberta_large_squad_gaotianyu1350_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squad_gaotianyu1350_pipeline` is a English model originally trained by gaotianyu1350. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_squad_gaotianyu1350_pipeline_en_5.4.2_3.0_1725201168633.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squad_gaotianyu1350_pipeline_en_5.4.2_3.0_1725201168633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_squad_gaotianyu1350_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_squad_gaotianyu1350_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_squad_gaotianyu1350_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/gaotianyu1350/roberta-large-squad + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_ltrc_telugu_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_ltrc_telugu_en.md new file mode 100644 index 00000000000000..266d783be38581 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_ltrc_telugu_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_ltrc_telugu RoBertaEmbeddings from ltrctelugu +author: John Snow Labs +name: roberta_ltrc_telugu +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ltrc_telugu` is a English model originally trained by ltrctelugu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ltrc_telugu_en_5.4.2_3.0_1725164798766.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ltrc_telugu_en_5.4.2_3.0_1725164798766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("roberta_ltrc_telugu","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("roberta_ltrc_telugu","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_ltrc_telugu| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|901.4 MB| + +## References + +https://huggingface.co/ltrctelugu/roberta_ltrc_telugu \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_becasincentivos1_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_becasincentivos1_es.md new file mode 100644 index 00000000000000..4dd4f2fff5a1ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_becasincentivos1_es.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Spanish RobertaForQuestionAnswering Base Cased model (from Evelyn18) +author: John Snow Labs +name: roberta_qa_base_spanish_squades_becasincentivos1 +date: 2024-09-01 +tags: [es, open_source, roberta, question_answering, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-spanish-squades-becasIncentivos1` is a Spanish model originally trained by `Evelyn18`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_becasincentivos1_es_5.4.2_3.0_1725201128522.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_becasincentivos1_es_5.4.2_3.0_1725201128522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_spanish_squades_becasincentivos1","es")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_spanish_squades_becasincentivos1","es") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_base_spanish_squades_becasincentivos1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|es| +|Size:|459.2 MB| + +## References + +References + +- https://huggingface.co/Evelyn18/roberta-base-spanish-squades-becasIncentivos1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_becasincentivos1_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_becasincentivos1_pipeline_es.md new file mode 100644 index 00000000000000..b61560be8f0d1f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_becasincentivos1_pipeline_es.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Castilian, Spanish roberta_qa_base_spanish_squades_becasincentivos1_pipeline pipeline RoBertaForQuestionAnswering from Evelyn18 +author: John Snow Labs +name: roberta_qa_base_spanish_squades_becasincentivos1_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_base_spanish_squades_becasincentivos1_pipeline` is a Castilian, Spanish model originally trained by Evelyn18. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_becasincentivos1_pipeline_es_5.4.2_3.0_1725201154703.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_becasincentivos1_pipeline_es_5.4.2_3.0_1725201154703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_base_spanish_squades_becasincentivos1_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_base_spanish_squades_becasincentivos1_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_base_spanish_squades_becasincentivos1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|459.2 MB| + +## References + +https://huggingface.co/Evelyn18/roberta-base-spanish-squades-becasIncentivos1 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_becasv3_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_becasv3_es.md new file mode 100644 index 00000000000000..8d198c9f33ebc4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_becasv3_es.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Spanish RobertaForQuestionAnswering Base Cased model (from Evelyn18) +author: John Snow Labs +name: roberta_qa_base_spanish_squades_becasv3 +date: 2024-09-01 +tags: [es, open_source, roberta, question_answering, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-spanish-squades-becasv3` is a Spanish model originally trained by `Evelyn18`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_becasv3_es_5.4.2_3.0_1725200418960.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_becasv3_es_5.4.2_3.0_1725200418960.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_spanish_squades_becasv3","es")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_spanish_squades_becasv3","es") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_base_spanish_squades_becasv3| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|es| +|Size:|459.1 MB| + +## References + +References + +- https://huggingface.co/Evelyn18/roberta-base-spanish-squades-becasv3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_becasv3_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_becasv3_pipeline_es.md new file mode 100644 index 00000000000000..9c220add22ece9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_becasv3_pipeline_es.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Castilian, Spanish roberta_qa_base_spanish_squades_becasv3_pipeline pipeline RoBertaForQuestionAnswering from Evelyn18 +author: John Snow Labs +name: roberta_qa_base_spanish_squades_becasv3_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_base_spanish_squades_becasv3_pipeline` is a Castilian, Spanish model originally trained by Evelyn18. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_becasv3_pipeline_es_5.4.2_3.0_1725200446177.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_becasv3_pipeline_es_5.4.2_3.0_1725200446177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_base_spanish_squades_becasv3_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_base_spanish_squades_becasv3_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_base_spanish_squades_becasv3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|459.1 MB| + +## References + +https://huggingface.co/Evelyn18/roberta-base-spanish-squades-becasv3 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_modelo_v1b3_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_modelo_v1b3_es.md new file mode 100644 index 00000000000000..d8e9450d709507 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_modelo_v1b3_es.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Spanish RobertaForQuestionAnswering Base Cased model (from Evelyn18) +author: John Snow Labs +name: roberta_qa_base_spanish_squades_modelo_v1b3 +date: 2024-09-01 +tags: [es, open_source, roberta, question_answering, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-spanish-squades-modelo-robertav1b3` is a Spanish model originally trained by `Evelyn18`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_modelo_v1b3_es_5.4.2_3.0_1725200549041.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_modelo_v1b3_es_5.4.2_3.0_1725200549041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_spanish_squades_modelo_v1b3","es")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_spanish_squades_modelo_v1b3","es") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_base_spanish_squades_modelo_v1b3| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|es| +|Size:|459.2 MB| + +## References + +References + +- https://huggingface.co/Evelyn18/roberta-base-spanish-squades-modelo-robertav1b3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_modelo_v1b3_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_modelo_v1b3_pipeline_es.md new file mode 100644 index 00000000000000..4acc3a5761562d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_base_spanish_squades_modelo_v1b3_pipeline_es.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Castilian, Spanish roberta_qa_base_spanish_squades_modelo_v1b3_pipeline pipeline RoBertaForQuestionAnswering from Evelyn18 +author: John Snow Labs +name: roberta_qa_base_spanish_squades_modelo_v1b3_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_base_spanish_squades_modelo_v1b3_pipeline` is a Castilian, Spanish model originally trained by Evelyn18. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_modelo_v1b3_pipeline_es_5.4.2_3.0_1725200574967.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_modelo_v1b3_pipeline_es_5.4.2_3.0_1725200574967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_base_spanish_squades_modelo_v1b3_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_base_spanish_squades_modelo_v1b3_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_base_spanish_squades_modelo_v1b3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|459.2 MB| + +## References + +https://huggingface.co/Evelyn18/roberta-base-spanish-squades-modelo-robertav1b3 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_declutr_techqa_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_declutr_techqa_en.md new file mode 100644 index 00000000000000..2b923146c4554a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_declutr_techqa_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English RobertaForQuestionAnswering (from AnonymousSub) +author: John Snow Labs +name: roberta_qa_declutr_techqa +date: 2024-09-01 +tags: [en, open_source, question_answering, roberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `declutr-techqa` is a English model originally trained by `AnonymousSub`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_declutr_techqa_en_5.4.2_3.0_1725200295917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_declutr_techqa_en_5.4.2_3.0_1725200295917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_declutr_techqa","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = RoBertaForQuestionAnswering +.pretrained("roberta_qa_declutr_techqa","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.roberta.techqa_declutr.by_AnonymousSub").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_declutr_techqa| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|306.8 MB| + +## References + +References + +- https://huggingface.co/AnonymousSub/declutr-techqa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_declutr_techqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_declutr_techqa_pipeline_en.md new file mode 100644 index 00000000000000..9e946eba01405f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_declutr_techqa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_declutr_techqa_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub +author: John Snow Labs +name: roberta_qa_declutr_techqa_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_declutr_techqa_pipeline` is a English model originally trained by AnonymousSub. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_declutr_techqa_pipeline_en_5.4.2_3.0_1725200312844.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_declutr_techqa_pipeline_en_5.4.2_3.0_1725200312844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_declutr_techqa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_declutr_techqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_declutr_techqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|306.9 MB| + +## References + +https://huggingface.co/AnonymousSub/declutr-techqa + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_deepset_base_squad2_orkg_how_1e_4_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_deepset_base_squad2_orkg_how_1e_4_en.md new file mode 100644 index 00000000000000..dfb6175de8c1a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_deepset_base_squad2_orkg_how_1e_4_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English RobertaForQuestionAnswering Base Cased model (from Moussab) +author: John Snow Labs +name: roberta_qa_deepset_base_squad2_orkg_how_1e_4 +date: 2024-09-01 +tags: [en, open_source, roberta, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `deepset-roberta-base-squad2-orkg-how-1e-4` is a English model originally trained by `Moussab`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_deepset_base_squad2_orkg_how_1e_4_en_5.4.2_3.0_1725200993238.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_deepset_base_squad2_orkg_how_1e_4_en_5.4.2_3.0_1725200993238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_deepset_base_squad2_orkg_how_1e_4","en")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_deepset_base_squad2_orkg_how_1e_4","en") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_deepset_base_squad2_orkg_how_1e_4| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|464.1 MB| + +## References + +References + +- https://huggingface.co/Moussab/deepset-roberta-base-squad2-orkg-how-1e-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_deepset_base_squad2_orkg_how_1e_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_deepset_base_squad2_orkg_how_1e_4_pipeline_en.md new file mode 100644 index 00000000000000..3ad6bcad1ad288 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_deepset_base_squad2_orkg_how_1e_4_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_deepset_base_squad2_orkg_how_1e_4_pipeline pipeline RoBertaForQuestionAnswering from Moussab +author: John Snow Labs +name: roberta_qa_deepset_base_squad2_orkg_how_1e_4_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_deepset_base_squad2_orkg_how_1e_4_pipeline` is a English model originally trained by Moussab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_deepset_base_squad2_orkg_how_1e_4_pipeline_en_5.4.2_3.0_1725201019111.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_deepset_base_squad2_orkg_how_1e_4_pipeline_en_5.4.2_3.0_1725201019111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_deepset_base_squad2_orkg_how_1e_4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_deepset_base_squad2_orkg_how_1e_4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_deepset_base_squad2_orkg_how_1e_4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/Moussab/deepset-roberta-base-squad2-orkg-how-1e-4 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_finetuned_location_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_finetuned_location_en.md new file mode 100644 index 00000000000000..c9210f5e259b4f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_finetuned_location_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English RobertaForQuestionAnswering Cased model (from skandaonsolve) +author: John Snow Labs +name: roberta_qa_finetuned_location +date: 2024-09-01 +tags: [en, open_source, roberta, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-finetuned-location` is a English model originally trained by `skandaonsolve`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_location_en_5.4.2_3.0_1725200017085.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_location_en_5.4.2_3.0_1725200017085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_finetuned_location","en")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_finetuned_location","en") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_finetuned_location| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|464.0 MB| + +## References + +References + +- https://huggingface.co/skandaonsolve/roberta-finetuned-location \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_finetuned_location_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_finetuned_location_pipeline_en.md new file mode 100644 index 00000000000000..b64f99ff275d2e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_finetuned_location_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_finetuned_location_pipeline pipeline RoBertaForQuestionAnswering from skandaonsolve +author: John Snow Labs +name: roberta_qa_finetuned_location_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_finetuned_location_pipeline` is a English model originally trained by skandaonsolve. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_location_pipeline_en_5.4.2_3.0_1725200042993.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_location_pipeline_en_5.4.2_3.0_1725200042993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_finetuned_location_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_finetuned_location_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_finetuned_location_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|464.0 MB| + +## References + +https://huggingface.co/skandaonsolve/roberta-finetuned-location + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_for_question_answering_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_for_question_answering_en.md new file mode 100644 index 00000000000000..514c2f20fb9f22 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_for_question_answering_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English RobertaForQuestionAnswering Cased model (from Zamachi) +author: John Snow Labs +name: roberta_qa_for_question_answering +date: 2024-09-01 +tags: [en, open_source, roberta, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-for-question-answering` is a English model originally trained by `Zamachi`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_for_question_answering_en_5.4.2_3.0_1725200305186.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_for_question_answering_en_5.4.2_3.0_1725200305186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_for_question_answering","en")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_for_question_answering","en") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_for_question_answering| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|465.4 MB| + +## References + +References + +- https://huggingface.co/Zamachi/roberta-for-question-answering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_for_question_answering_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_for_question_answering_pipeline_en.md new file mode 100644 index 00000000000000..a589fcc00ae7f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_for_question_answering_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_for_question_answering_pipeline pipeline RoBertaForQuestionAnswering from Zamachi +author: John Snow Labs +name: roberta_qa_for_question_answering_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_for_question_answering_pipeline` is a English model originally trained by Zamachi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_for_question_answering_pipeline_en_5.4.2_3.0_1725200331689.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_for_question_answering_pipeline_en_5.4.2_3.0_1725200331689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_for_question_answering_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_for_question_answering_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_for_question_answering_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.4 MB| + +## References + +https://huggingface.co/Zamachi/roberta-for-question-answering + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_huxxx657_roberta_base_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_huxxx657_roberta_base_finetuned_squad_en.md new file mode 100644 index 00000000000000..93e337041be64f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_huxxx657_roberta_base_finetuned_squad_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English RobertaForQuestionAnswering (from huxxx657) +author: John Snow Labs +name: roberta_qa_huxxx657_roberta_base_finetuned_squad +date: 2024-09-01 +tags: [en, open_source, question_answering, roberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-finetuned-squad` is a English model originally trained by `huxxx657`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_huxxx657_roberta_base_finetuned_squad_en_5.4.2_3.0_1725200166398.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_huxxx657_roberta_base_finetuned_squad_en_5.4.2_3.0_1725200166398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_huxxx657_roberta_base_finetuned_squad","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = RoBertaForQuestionAnswering +.pretrained("roberta_qa_huxxx657_roberta_base_finetuned_squad","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squad.roberta.base.by_huxxx657").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_huxxx657_roberta_base_finetuned_squad| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.5 MB| + +## References + +References + +- https://huggingface.co/huxxx657/roberta-base-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_huxxx657_roberta_base_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_huxxx657_roberta_base_finetuned_squad_pipeline_en.md new file mode 100644 index 00000000000000..54624375239d2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_huxxx657_roberta_base_finetuned_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_huxxx657_roberta_base_finetuned_squad_pipeline pipeline RoBertaForQuestionAnswering from huxxx657 +author: John Snow Labs +name: roberta_qa_huxxx657_roberta_base_finetuned_squad_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_huxxx657_roberta_base_finetuned_squad_pipeline` is a English model originally trained by huxxx657. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_huxxx657_roberta_base_finetuned_squad_pipeline_en_5.4.2_3.0_1725200192401.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_huxxx657_roberta_base_finetuned_squad_pipeline_en_5.4.2_3.0_1725200192401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_huxxx657_roberta_base_finetuned_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_huxxx657_roberta_base_finetuned_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_huxxx657_roberta_base_finetuned_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.5 MB| + +## References + +https://huggingface.co/huxxx657/roberta-base-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_priv_qna_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_priv_qna_en.md new file mode 100644 index 00000000000000..a8f06fa8c3566a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_priv_qna_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English RobertaForQuestionAnswering Cased model (from arjunth2001) +author: John Snow Labs +name: roberta_qa_priv_qna +date: 2024-09-01 +tags: [en, open_source, roberta, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `priv_qna` is a English model originally trained by `arjunth2001`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_priv_qna_en_5.4.2_3.0_1725200288120.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_priv_qna_en_5.4.2_3.0_1725200288120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_priv_qna","en")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_priv_qna","en") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.roberta.by_arjunth2001").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_priv_qna| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.8 MB| + +## References + +References + +- https://huggingface.co/arjunth2001/priv_qna \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_priv_qna_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_priv_qna_pipeline_en.md new file mode 100644 index 00000000000000..aecb8a5c779adc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_priv_qna_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_priv_qna_pipeline pipeline RoBertaForQuestionAnswering from arjunth2001 +author: John Snow Labs +name: roberta_qa_priv_qna_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_priv_qna_pipeline` is a English model originally trained by arjunth2001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_priv_qna_pipeline_en_5.4.2_3.0_1725200313086.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_priv_qna_pipeline_en_5.4.2_3.0_1725200313086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_priv_qna_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_priv_qna_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_priv_qna_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.8 MB| + +## References + +https://huggingface.co/arjunth2001/priv_qna + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_roberta_base_1B_1_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_roberta_base_1B_1_finetuned_squadv2_en.md new file mode 100644 index 00000000000000..65201a92435055 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_roberta_base_1B_1_finetuned_squadv2_en.md @@ -0,0 +1,109 @@ +--- +layout: model +title: English RobertaForQuestionAnswering (from mrm8488) +author: John Snow Labs +name: roberta_qa_roberta_base_1B_1_finetuned_squadv2 +date: 2024-09-01 +tags: [en, open_source, question_answering, roberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-1B-1-finetuned-squadv2` is a English model originally trained by `mrm8488`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_1B_1_finetuned_squadv2_en_5.4.2_3.0_1725200790712.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_1B_1_finetuned_squadv2_en_5.4.2_3.0_1725200790712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_1B_1_finetuned_squadv2","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = RoBertaForQuestionAnswering +.pretrained("roberta_qa_roberta_base_1B_1_finetuned_squadv2","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squadv2.roberta.base_v2").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_roberta_base_1B_1_finetuned_squadv2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|447.3 MB| + +## References + +References + +- https://huggingface.co/mrm8488/roberta-base-1B-1-finetuned-squadv2 +- https://rajpurkar.github.io/SQuAD-explorer/explore/v2.0/dev/ +- https://twitter.com/mrm8488 +- https://www.linkedin.com/in/manuel-romero-cs/ \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_roberta_base_1B_1_finetuned_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_roberta_base_1B_1_finetuned_squadv2_pipeline_en.md new file mode 100644 index 00000000000000..963737116fd7da --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_roberta_base_1B_1_finetuned_squadv2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_roberta_base_1B_1_finetuned_squadv2_pipeline pipeline RoBertaForQuestionAnswering from mrm8488 +author: John Snow Labs +name: roberta_qa_roberta_base_1B_1_finetuned_squadv2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_1B_1_finetuned_squadv2_pipeline` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_1B_1_finetuned_squadv2_pipeline_en_5.4.2_3.0_1725200820660.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_1B_1_finetuned_squadv2_pipeline_en_5.4.2_3.0_1725200820660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_roberta_base_1B_1_finetuned_squadv2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_1B_1_finetuned_squadv2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_roberta_base_1B_1_finetuned_squadv2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|447.3 MB| + +## References + +https://huggingface.co/mrm8488/roberta-base-1B-1-finetuned-squadv2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_roberta_large_squad2_hp_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_roberta_large_squad2_hp_en.md new file mode 100644 index 00000000000000..9adab330dbaf7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_roberta_large_squad2_hp_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English RobertaForQuestionAnswering (from deepset) +author: John Snow Labs +name: roberta_qa_roberta_large_squad2_hp +date: 2024-09-01 +tags: [en, open_source, question_answering, roberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-large-squad2-hp` is a English model originally trained by `deepset`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_squad2_hp_en_5.4.2_3.0_1725200808855.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_squad2_hp_en_5.4.2_3.0_1725200808855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_large_squad2_hp","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = RoBertaForQuestionAnswering +.pretrained("roberta_qa_roberta_large_squad2_hp","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squadv2.roberta.large.by_deepset").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_roberta_large_squad2_hp| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +References + +- https://huggingface.co/deepset/roberta-large-squad2-hp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_roberta_large_squad2_hp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_roberta_large_squad2_hp_pipeline_en.md new file mode 100644 index 00000000000000..aa2e92d291c327 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_qa_roberta_large_squad2_hp_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_roberta_large_squad2_hp_pipeline pipeline RoBertaForQuestionAnswering from deepset +author: John Snow Labs +name: roberta_qa_roberta_large_squad2_hp_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_large_squad2_hp_pipeline` is a English model originally trained by deepset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_squad2_hp_pipeline_en_5.4.2_3.0_1725200880857.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_squad2_hp_pipeline_en_5.4.2_3.0_1725200880857.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_roberta_large_squad2_hp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_roberta_large_squad2_hp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_roberta_large_squad2_hp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/deepset/roberta-large-squad2-hp + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_question_answer_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_question_answer_en.md new file mode 100644 index 00000000000000..98344b0cd33e79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_question_answer_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_question_answer RoBertaForSequenceClassification from Chillyblast +author: John Snow Labs +name: roberta_question_answer +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_question_answer` is a English model originally trained by Chillyblast. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_question_answer_en_5.4.2_3.0_1725195133109.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_question_answer_en_5.4.2_3.0_1725195133109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_question_answer","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_question_answer", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_question_answer| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|428.2 MB| + +## References + +https://huggingface.co/Chillyblast/Roberta_Question_Answer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_question_answer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_question_answer_pipeline_en.md new file mode 100644 index 00000000000000..1fb4f3aee54005 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_question_answer_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_question_answer_pipeline pipeline RoBertaForSequenceClassification from Chillyblast +author: John Snow Labs +name: roberta_question_answer_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_question_answer_pipeline` is a English model originally trained by Chillyblast. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_question_answer_pipeline_en_5.4.2_3.0_1725195164259.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_question_answer_pipeline_en_5.4.2_3.0_1725195164259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_question_answer_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_question_answer_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_question_answer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|428.2 MB| + +## References + +https://huggingface.co/Chillyblast/Roberta_Question_Answer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_sentimental_analysis_model_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_sentimental_analysis_model_en.md new file mode 100644 index 00000000000000..3c7c553568353c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_sentimental_analysis_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_sentimental_analysis_model RoBertaForSequenceClassification from syedkhalid076 +author: John Snow Labs +name: roberta_sentimental_analysis_model +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_sentimental_analysis_model` is a English model originally trained by syedkhalid076. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_sentimental_analysis_model_en_5.4.2_3.0_1725195261359.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_sentimental_analysis_model_en_5.4.2_3.0_1725195261359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_sentimental_analysis_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_sentimental_analysis_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_sentimental_analysis_model| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|443.6 MB| + +## References + +https://huggingface.co/syedkhalid076/RoBERTa-Sentimental-Analysis-Model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_sentimental_analysis_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_sentimental_analysis_model_pipeline_en.md new file mode 100644 index 00000000000000..0273750b8c4c8e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_sentimental_analysis_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_sentimental_analysis_model_pipeline pipeline RoBertaForSequenceClassification from syedkhalid076 +author: John Snow Labs +name: roberta_sentimental_analysis_model_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_sentimental_analysis_model_pipeline` is a English model originally trained by syedkhalid076. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_sentimental_analysis_model_pipeline_en_5.4.2_3.0_1725195289498.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_sentimental_analysis_model_pipeline_en_5.4.2_3.0_1725195289498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_sentimental_analysis_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_sentimental_analysis_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_sentimental_analysis_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|443.6 MB| + +## References + +https://huggingface.co/syedkhalid076/RoBERTa-Sentimental-Analysis-Model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_sequence_classifier_bsc_base_spanish_diagnostics_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_sequence_classifier_bsc_base_spanish_diagnostics_es.md new file mode 100644 index 00000000000000..8cce54c8ffe125 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_sequence_classifier_bsc_base_spanish_diagnostics_es.md @@ -0,0 +1,104 @@ +--- +layout: model +title: Spanish RobertaForSequenceClassification Base Cased model (from mrm8488) +author: John Snow Labs +name: roberta_sequence_classifier_bsc_base_spanish_diagnostics +date: 2024-09-01 +tags: [es, open_source, roberta, sequence_classification, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bsc-roberta-base-spanish-diagnostics` is a Spanish model originally trained by `mrm8488`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_sequence_classifier_bsc_base_spanish_diagnostics_es_5.4.2_3.0_1725195108949.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_sequence_classifier_bsc_base_spanish_diagnostics_es_5.4.2_3.0_1725195108949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +classifier = RoBertaForSequenceClassification.pretrained("roberta_sequence_classifier_bsc_base_spanish_diagnostics","es") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val classifer = RoBertaForSequenceClassification.pretrained("roberta_sequence_classifier_bsc_base_spanish_diagnostics","es") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("es.classify.roberta.base").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_sequence_classifier_bsc_base_spanish_diagnostics| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|441.6 MB| + +## References + +References + +- https://huggingface.co/mrm8488/bsc-roberta-base-spanish-diagnostics \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_sequence_classifier_bsc_base_spanish_diagnostics_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_sequence_classifier_bsc_base_spanish_diagnostics_pipeline_es.md new file mode 100644 index 00000000000000..4dfc4687894275 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_sequence_classifier_bsc_base_spanish_diagnostics_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish roberta_sequence_classifier_bsc_base_spanish_diagnostics_pipeline pipeline RoBertaForSequenceClassification from mrm8488 +author: John Snow Labs +name: roberta_sequence_classifier_bsc_base_spanish_diagnostics_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_sequence_classifier_bsc_base_spanish_diagnostics_pipeline` is a Castilian, Spanish model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_sequence_classifier_bsc_base_spanish_diagnostics_pipeline_es_5.4.2_3.0_1725195135113.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_sequence_classifier_bsc_base_spanish_diagnostics_pipeline_es_5.4.2_3.0_1725195135113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_sequence_classifier_bsc_base_spanish_diagnostics_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_sequence_classifier_bsc_base_spanish_diagnostics_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_sequence_classifier_bsc_base_spanish_diagnostics_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|441.6 MB| + +## References + +https://huggingface.co/mrm8488/bsc-roberta-base-spanish-diagnostics + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_tiny_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_tiny_pipeline_en.md new file mode 100644 index 00000000000000..df4b7d5d4cb2c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_tiny_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_tiny_pipeline pipeline RoBertaEmbeddings from arampacha +author: John Snow Labs +name: roberta_tiny_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_tiny_pipeline` is a English model originally trained by arampacha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_tiny_pipeline_en_5.4.2_3.0_1725165406254.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_tiny_pipeline_en_5.4.2_3.0_1725165406254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_tiny_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_tiny_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_tiny_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|64.5 MB| + +## References + +https://huggingface.co/arampacha/roberta-tiny + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_trustpilot_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_trustpilot_en.md new file mode 100644 index 00000000000000..2780ef7647b5c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_trustpilot_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_trustpilot RoBertaForSequenceClassification from riken01 +author: John Snow Labs +name: roberta_trustpilot +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_trustpilot` is a English model originally trained by riken01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_trustpilot_en_5.4.2_3.0_1725194981466.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_trustpilot_en_5.4.2_3.0_1725194981466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_trustpilot","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_trustpilot", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_trustpilot| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|452.6 MB| + +## References + +https://huggingface.co/riken01/roberta-trustpilot \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_trustpilot_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_trustpilot_pipeline_en.md new file mode 100644 index 00000000000000..9c6891c8cffda7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_trustpilot_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_trustpilot_pipeline pipeline RoBertaForSequenceClassification from riken01 +author: John Snow Labs +name: roberta_trustpilot_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_trustpilot_pipeline` is a English model originally trained by riken01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_trustpilot_pipeline_en_5.4.2_3.0_1725195012312.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_trustpilot_pipeline_en_5.4.2_3.0_1725195012312.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_trustpilot_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_trustpilot_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_trustpilot_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|452.7 MB| + +## References + +https://huggingface.co/riken01/roberta-trustpilot + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_ufsm_qa_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_ufsm_qa_en.md new file mode 100644 index 00000000000000..2eefe817932e43 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_ufsm_qa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_ufsm_qa RoBertaForQuestionAnswering from oGabrielFreitas +author: John Snow Labs +name: roberta_ufsm_qa +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ufsm_qa` is a English model originally trained by oGabrielFreitas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ufsm_qa_en_5.4.2_3.0_1725207385225.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ufsm_qa_en_5.4.2_3.0_1725207385225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_ufsm_qa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_ufsm_qa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_ufsm_qa| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/oGabrielFreitas/roberta-ufsm-qa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_ufsm_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_ufsm_qa_pipeline_en.md new file mode 100644 index 00000000000000..5f8869a8528348 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_ufsm_qa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_ufsm_qa_pipeline pipeline RoBertaForQuestionAnswering from oGabrielFreitas +author: John Snow Labs +name: roberta_ufsm_qa_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ufsm_qa_pipeline` is a English model originally trained by oGabrielFreitas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ufsm_qa_pipeline_en_5.4.2_3.0_1725207411853.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ufsm_qa_pipeline_en_5.4.2_3.0_1725207411853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_ufsm_qa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_ufsm_qa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_ufsm_qa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/oGabrielFreitas/roberta-ufsm-qa + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-robertacrawlpt_base_pt.md b/docs/_posts/ahmedlone127/2024-09-01-robertacrawlpt_base_pt.md new file mode 100644 index 00000000000000..c0962b3f14403c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-robertacrawlpt_base_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese robertacrawlpt_base RoBertaEmbeddings from eduagarcia +author: John Snow Labs +name: robertacrawlpt_base +date: 2024-09-01 +tags: [pt, open_source, onnx, embeddings, roberta] +task: Embeddings +language: pt +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robertacrawlpt_base` is a Portuguese model originally trained by eduagarcia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robertacrawlpt_base_pt_5.4.2_3.0_1725191770460.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robertacrawlpt_base_pt_5.4.2_3.0_1725191770460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("robertacrawlpt_base","pt") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("robertacrawlpt_base","pt") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|robertacrawlpt_base| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|pt| +|Size:|296.8 MB| + +## References + +https://huggingface.co/eduagarcia/RoBERTaCrawlPT-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-rta_en.md b/docs/_posts/ahmedlone127/2024-09-01-rta_en.md new file mode 100644 index 00000000000000..b0a0707ad770ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-rta_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English rta RoBertaForSequenceClassification from Colorful +author: John Snow Labs +name: rta +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rta` is a English model originally trained by Colorful. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rta_en_5.4.2_3.0_1725195010765.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rta_en_5.4.2_3.0_1725195010765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("rta","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("rta", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rta| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.2 MB| + +## References + +https://huggingface.co/Colorful/RTA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-rta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-rta_pipeline_en.md new file mode 100644 index 00000000000000..b9880cae425fcf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-rta_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English rta_pipeline pipeline RoBertaForSequenceClassification from Colorful +author: John Snow Labs +name: rta_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rta_pipeline` is a English model originally trained by Colorful. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rta_pipeline_en_5.4.2_3.0_1725195038814.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rta_pipeline_en_5.4.2_3.0_1725195038814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("rta_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("rta_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/Colorful/RTA + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-rtm_roberta_5e_en.md b/docs/_posts/ahmedlone127/2024-09-01-rtm_roberta_5e_en.md new file mode 100644 index 00000000000000..dfda6a2c8d54f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-rtm_roberta_5e_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English rtm_roberta_5e RoBertaForSequenceClassification from pig4431 +author: John Snow Labs +name: rtm_roberta_5e +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rtm_roberta_5e` is a English model originally trained by pig4431. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rtm_roberta_5e_en_5.5.0_3.0_1725212037203.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rtm_roberta_5e_en_5.5.0_3.0_1725212037203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("rtm_roberta_5e","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("rtm_roberta_5e", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rtm_roberta_5e| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|435.9 MB| + +## References + +https://huggingface.co/pig4431/rtm_roBERTa_5E \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-rtm_roberta_5e_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-rtm_roberta_5e_pipeline_en.md new file mode 100644 index 00000000000000..e5e8d81411fa84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-rtm_roberta_5e_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English rtm_roberta_5e_pipeline pipeline RoBertaForSequenceClassification from pig4431 +author: John Snow Labs +name: rtm_roberta_5e_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rtm_roberta_5e_pipeline` is a English model originally trained by pig4431. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rtm_roberta_5e_pipeline_en_5.5.0_3.0_1725212076810.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rtm_roberta_5e_pipeline_en_5.5.0_3.0_1725212076810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("rtm_roberta_5e_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("rtm_roberta_5e_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rtm_roberta_5e_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|436.0 MB| + +## References + +https://huggingface.co/pig4431/rtm_roBERTa_5E + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-rubert_base_cased_nli_threeway_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-01-rubert_base_cased_nli_threeway_pipeline_ru.md new file mode 100644 index 00000000000000..17575079bea94f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-rubert_base_cased_nli_threeway_pipeline_ru.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Russian rubert_base_cased_nli_threeway_pipeline pipeline BertForZeroShotClassification from cointegrated +author: John Snow Labs +name: rubert_base_cased_nli_threeway_pipeline +date: 2024-09-01 +tags: [ru, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: ru +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_cased_nli_threeway_pipeline` is a Russian model originally trained by cointegrated. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_cased_nli_threeway_pipeline_ru_5.4.2_3.0_1725202562146.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_cased_nli_threeway_pipeline_ru_5.4.2_3.0_1725202562146.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("rubert_base_cased_nli_threeway_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("rubert_base_cased_nli_threeway_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_base_cased_nli_threeway_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|664.3 MB| + +## References + +https://huggingface.co/cointegrated/rubert-base-cased-nli-threeway + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-rubert_base_cased_nli_threeway_ru.md b/docs/_posts/ahmedlone127/2024-09-01-rubert_base_cased_nli_threeway_ru.md new file mode 100644 index 00000000000000..7724a0b20833f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-rubert_base_cased_nli_threeway_ru.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Russian rubert_base_cased_nli_threeway BertForZeroShotClassification from cointegrated +author: John Snow Labs +name: rubert_base_cased_nli_threeway +date: 2024-09-01 +tags: [ru, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: ru +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_cased_nli_threeway` is a Russian model originally trained by cointegrated. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_cased_nli_threeway_ru_5.4.2_3.0_1725202519289.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_cased_nli_threeway_ru_5.4.2_3.0_1725202519289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("rubert_base_cased_nli_threeway","ru") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("rubert_base_cased_nli_threeway", "ru") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_base_cased_nli_threeway| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ru| +|Size:|664.3 MB| + +## References + +https://huggingface.co/cointegrated/rubert-base-cased-nli-threeway \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-rubert_large_squad_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-rubert_large_squad_2_pipeline_en.md new file mode 100644 index 00000000000000..b57a71e5bc984b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-rubert_large_squad_2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English rubert_large_squad_2_pipeline pipeline BertForQuestionAnswering from Den4ikAI +author: John Snow Labs +name: rubert_large_squad_2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_large_squad_2_pipeline` is a English model originally trained by Den4ikAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_large_squad_2_pipeline_en_5.4.2_3.0_1725185391339.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_large_squad_2_pipeline_en_5.4.2_3.0_1725185391339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("rubert_large_squad_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("rubert_large_squad_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_large_squad_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|667.1 MB| + +## References + +https://huggingface.co/Den4ikAI/rubert_large_squad_2 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-rured2_ner_mdeberta_v3_base_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-01-rured2_ner_mdeberta_v3_base_pipeline_ru.md new file mode 100644 index 00000000000000..cc20a28b4c2280 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-rured2_ner_mdeberta_v3_base_pipeline_ru.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Russian rured2_ner_mdeberta_v3_base_pipeline pipeline DeBertaForTokenClassification from Grpp +author: John Snow Labs +name: rured2_ner_mdeberta_v3_base_pipeline +date: 2024-09-01 +tags: [ru, open_source, pipeline, onnx] +task: Named Entity Recognition +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rured2_ner_mdeberta_v3_base_pipeline` is a Russian model originally trained by Grpp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rured2_ner_mdeberta_v3_base_pipeline_ru_5.5.0_3.0_1725233575999.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rured2_ner_mdeberta_v3_base_pipeline_ru_5.5.0_3.0_1725233575999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("rured2_ner_mdeberta_v3_base_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("rured2_ner_mdeberta_v3_base_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rured2_ner_mdeberta_v3_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|823.5 MB| + +## References + +https://huggingface.co/Grpp/rured2-ner-mdeberta-v3-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-rured2_ner_mdeberta_v3_base_ru.md b/docs/_posts/ahmedlone127/2024-09-01-rured2_ner_mdeberta_v3_base_ru.md new file mode 100644 index 00000000000000..789f5abbe401a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-rured2_ner_mdeberta_v3_base_ru.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Russian rured2_ner_mdeberta_v3_base DeBertaForTokenClassification from Grpp +author: John Snow Labs +name: rured2_ner_mdeberta_v3_base +date: 2024-09-01 +tags: [ru, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rured2_ner_mdeberta_v3_base` is a Russian model originally trained by Grpp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rured2_ner_mdeberta_v3_base_ru_5.5.0_3.0_1725233453359.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rured2_ner_mdeberta_v3_base_ru_5.5.0_3.0_1725233453359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DeBertaForTokenClassification.pretrained("rured2_ner_mdeberta_v3_base","ru") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("rured2_ner_mdeberta_v3_base", "ru") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rured2_ner_mdeberta_v3_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ru| +|Size:|823.5 MB| + +## References + +https://huggingface.co/Grpp/rured2-ner-mdeberta-v3-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ruscibert_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-01-ruscibert_pipeline_ru.md new file mode 100644 index 00000000000000..3851a4a981dbb5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ruscibert_pipeline_ru.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Russian ruscibert_pipeline pipeline RoBertaEmbeddings from ai-forever +author: John Snow Labs +name: ruscibert_pipeline +date: 2024-09-01 +tags: [ru, open_source, pipeline, onnx] +task: Embeddings +language: ru +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ruscibert_pipeline` is a Russian model originally trained by ai-forever. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ruscibert_pipeline_ru_5.4.2_3.0_1725186068091.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ruscibert_pipeline_ru_5.4.2_3.0_1725186068091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ruscibert_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ruscibert_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ruscibert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|463.7 MB| + +## References + +https://huggingface.co/ai-forever/ruSciBERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ruscibert_ru.md b/docs/_posts/ahmedlone127/2024-09-01-ruscibert_ru.md new file mode 100644 index 00000000000000..d249459754b354 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ruscibert_ru.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Russian ruscibert RoBertaEmbeddings from ai-forever +author: John Snow Labs +name: ruscibert +date: 2024-09-01 +tags: [ru, open_source, onnx, embeddings, roberta] +task: Embeddings +language: ru +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ruscibert` is a Russian model originally trained by ai-forever. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ruscibert_ru_5.4.2_3.0_1725186040845.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ruscibert_ru_5.4.2_3.0_1725186040845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("ruscibert","ru") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("ruscibert","ru") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ruscibert| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|ru| +|Size:|463.6 MB| + +## References + +https://huggingface.co/ai-forever/ruSciBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-scandi_nli_base_da.md b/docs/_posts/ahmedlone127/2024-09-01-scandi_nli_base_da.md new file mode 100644 index 00000000000000..100c4c7eb19d35 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-scandi_nli_base_da.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Danish scandi_nli_base BertForZeroShotClassification from alexandrainst +author: John Snow Labs +name: scandi_nli_base +date: 2024-09-01 +tags: [da, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: da +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scandi_nli_base` is a Danish model originally trained by alexandrainst. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scandi_nli_base_da_5.4.2_3.0_1725201635821.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scandi_nli_base_da_5.4.2_3.0_1725201635821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("scandi_nli_base","da") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("scandi_nli_base", "da") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scandi_nli_base| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|da| +|Size:|666.2 MB| + +## References + +https://huggingface.co/alexandrainst/scandi-nli-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-scandi_nli_base_pipeline_da.md b/docs/_posts/ahmedlone127/2024-09-01-scandi_nli_base_pipeline_da.md new file mode 100644 index 00000000000000..29f1bec9f439d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-scandi_nli_base_pipeline_da.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Danish scandi_nli_base_pipeline pipeline BertForZeroShotClassification from alexandrainst +author: John Snow Labs +name: scandi_nli_base_pipeline +date: 2024-09-01 +tags: [da, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: da +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scandi_nli_base_pipeline` is a Danish model originally trained by alexandrainst. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scandi_nli_base_pipeline_da_5.4.2_3.0_1725201672957.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scandi_nli_base_pipeline_da_5.4.2_3.0_1725201672957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("scandi_nli_base_pipeline", lang = "da") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("scandi_nli_base_pipeline", lang = "da") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scandi_nli_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|da| +|Size:|666.2 MB| + +## References + +https://huggingface.co/alexandrainst/scandi-nli-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-scandibert_ner_en.md b/docs/_posts/ahmedlone127/2024-09-01-scandibert_ner_en.md new file mode 100644 index 00000000000000..29fac88e7d5324 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-scandibert_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English scandibert_ner XlmRoBertaForTokenClassification from vesteinn +author: John Snow Labs +name: scandibert_ner +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scandibert_ner` is a English model originally trained by vesteinn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scandibert_ner_en_5.4.2_3.0_1725179315156.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scandibert_ner_en_5.4.2_3.0_1725179315156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("scandibert_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("scandibert_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scandibert_ner| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|450.7 MB| + +## References + +https://huggingface.co/vesteinn/ScandiBERT-NER \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-scandibert_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-01-scandibert_pipeline_xx.md new file mode 100644 index 00000000000000..7608ac42fda1a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-scandibert_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual scandibert_pipeline pipeline RoBertaEmbeddings from vesteinn +author: John Snow Labs +name: scandibert_pipeline +date: 2024-09-01 +tags: [xx, open_source, pipeline, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scandibert_pipeline` is a Multilingual model originally trained by vesteinn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scandibert_pipeline_xx_5.4.2_3.0_1725186929710.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scandibert_pipeline_xx_5.4.2_3.0_1725186929710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("scandibert_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("scandibert_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scandibert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|298.3 MB| + +## References + +https://huggingface.co/vesteinn/ScandiBERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-scandibert_xx.md b/docs/_posts/ahmedlone127/2024-09-01-scandibert_xx.md new file mode 100644 index 00000000000000..e35b27d64ef6de --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-scandibert_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual scandibert RoBertaEmbeddings from vesteinn +author: John Snow Labs +name: scandibert +date: 2024-09-01 +tags: [xx, open_source, onnx, embeddings, roberta] +task: Embeddings +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scandibert` is a Multilingual model originally trained by vesteinn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scandibert_xx_5.4.2_3.0_1725186842308.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scandibert_xx_5.4.2_3.0_1725186842308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("scandibert","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("scandibert","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scandibert| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|xx| +|Size:|298.3 MB| + +## References + +https://huggingface.co/vesteinn/ScandiBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-secureshellbert_en.md b/docs/_posts/ahmedlone127/2024-09-01-secureshellbert_en.md new file mode 100644 index 00000000000000..2c08394fe1fa97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-secureshellbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English secureshellbert RoBertaEmbeddings from SmartDataPolito +author: John Snow Labs +name: secureshellbert +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`secureshellbert` is a English model originally trained by SmartDataPolito. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/secureshellbert_en_5.4.2_3.0_1725191920325.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/secureshellbert_en_5.4.2_3.0_1725191920325.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("secureshellbert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("secureshellbert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|secureshellbert| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|466.1 MB| + +## References + +https://huggingface.co/SmartDataPolito/SecureShellBert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-sentareng_v0_en.md b/docs/_posts/ahmedlone127/2024-09-01-sentareng_v0_en.md new file mode 100644 index 00000000000000..7dd1ff9c6302c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-sentareng_v0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sentareng_v0 XlmRoBertaForSequenceClassification from Noor0 +author: John Snow Labs +name: sentareng_v0 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentareng_v0` is a English model originally trained by Noor0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentareng_v0_en_5.4.2_3.0_1725190458058.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentareng_v0_en_5.4.2_3.0_1725190458058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("sentareng_v0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("sentareng_v0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentareng_v0| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/Noor0/SentArEng_V0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-sentiment_hts5_xlm_roberta_hungarian_pipeline_hu.md b/docs/_posts/ahmedlone127/2024-09-01-sentiment_hts5_xlm_roberta_hungarian_pipeline_hu.md new file mode 100644 index 00000000000000..f892910d55fa4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-sentiment_hts5_xlm_roberta_hungarian_pipeline_hu.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Hungarian sentiment_hts5_xlm_roberta_hungarian_pipeline pipeline XlmRoBertaForSequenceClassification from NYTK +author: John Snow Labs +name: sentiment_hts5_xlm_roberta_hungarian_pipeline +date: 2024-09-01 +tags: [hu, open_source, pipeline, onnx] +task: Text Classification +language: hu +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_hts5_xlm_roberta_hungarian_pipeline` is a Hungarian model originally trained by NYTK. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_hts5_xlm_roberta_hungarian_pipeline_hu_5.4.2_3.0_1725189559163.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_hts5_xlm_roberta_hungarian_pipeline_hu_5.4.2_3.0_1725189559163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentiment_hts5_xlm_roberta_hungarian_pipeline", lang = "hu") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentiment_hts5_xlm_roberta_hungarian_pipeline", lang = "hu") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment_hts5_xlm_roberta_hungarian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|hu| +|Size:|794.2 MB| + +## References + +https://huggingface.co/NYTK/sentiment-hts5-xlm-roberta-hungarian + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-sentiment_travel_en.md b/docs/_posts/ahmedlone127/2024-09-01-sentiment_travel_en.md new file mode 100644 index 00000000000000..eb316da6a60ba3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-sentiment_travel_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sentiment_travel RoBertaForSequenceClassification from apriandito +author: John Snow Labs +name: sentiment_travel +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_travel` is a English model originally trained by apriandito. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_travel_en_5.5.0_3.0_1725212575573.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_travel_en_5.5.0_3.0_1725212575573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("sentiment_travel","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("sentiment_travel", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment_travel| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.1 MB| + +## References + +https://huggingface.co/apriandito/sentiment-travel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-sentiment_travel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-sentiment_travel_pipeline_en.md new file mode 100644 index 00000000000000..eaf7020c62b39a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-sentiment_travel_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sentiment_travel_pipeline pipeline RoBertaForSequenceClassification from apriandito +author: John Snow Labs +name: sentiment_travel_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_travel_pipeline` is a English model originally trained by apriandito. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_travel_pipeline_en_5.5.0_3.0_1725212600728.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_travel_pipeline_en_5.5.0_3.0_1725212600728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentiment_travel_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentiment_travel_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment_travel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.2 MB| + +## References + +https://huggingface.co/apriandito/sentiment-travel + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-serbian_roberta_base_sr.md b/docs/_posts/ahmedlone127/2024-09-01-serbian_roberta_base_sr.md new file mode 100644 index 00000000000000..91eeaaa1ed0518 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-serbian_roberta_base_sr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Serbian serbian_roberta_base RoBertaEmbeddings from macedonizer +author: John Snow Labs +name: serbian_roberta_base +date: 2024-09-01 +tags: [sr, open_source, onnx, embeddings, roberta] +task: Embeddings +language: sr +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`serbian_roberta_base` is a Serbian model originally trained by macedonizer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/serbian_roberta_base_sr_5.4.2_3.0_1725186055375.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/serbian_roberta_base_sr_5.4.2_3.0_1725186055375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("serbian_roberta_base","sr") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("serbian_roberta_base","sr") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|serbian_roberta_base| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|sr| +|Size:|311.1 MB| + +## References + +https://huggingface.co/macedonizer/sr-roberta-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-setfit_2class_model_en.md b/docs/_posts/ahmedlone127/2024-09-01-setfit_2class_model_en.md new file mode 100644 index 00000000000000..e645bd684f083e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-setfit_2class_model_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English setfit_2class_model MPNetEmbeddings from Bhuvana +author: John Snow Labs +name: setfit_2class_model +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_2class_model` is a English model originally trained by Bhuvana. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_2class_model_en_5.5.0_3.0_1725225256333.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_2class_model_en_5.5.0_3.0_1725225256333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("setfit_2class_model","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("setfit_2class_model","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_2class_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/Bhuvana/setfit_2class_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-setfit_2class_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-setfit_2class_model_pipeline_en.md new file mode 100644 index 00000000000000..1b68b61edb42b7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-setfit_2class_model_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English setfit_2class_model_pipeline pipeline MPNetEmbeddings from Bhuvana +author: John Snow Labs +name: setfit_2class_model_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_2class_model_pipeline` is a English model originally trained by Bhuvana. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_2class_model_pipeline_en_5.5.0_3.0_1725225277523.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_2class_model_pipeline_en_5.5.0_3.0_1725225277523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("setfit_2class_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("setfit_2class_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_2class_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/Bhuvana/setfit_2class_model + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-setfit_model_misinformation_on_mandates_public_health_en.md b/docs/_posts/ahmedlone127/2024-09-01-setfit_model_misinformation_on_mandates_public_health_en.md new file mode 100644 index 00000000000000..c5ea292d66d88a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-setfit_model_misinformation_on_mandates_public_health_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English setfit_model_misinformation_on_mandates_public_health MPNetEmbeddings from mitra-mir +author: John Snow Labs +name: setfit_model_misinformation_on_mandates_public_health +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_misinformation_on_mandates_public_health` is a English model originally trained by mitra-mir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_misinformation_on_mandates_public_health_en_5.5.0_3.0_1725224960868.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_misinformation_on_mandates_public_health_en_5.5.0_3.0_1725224960868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("setfit_model_misinformation_on_mandates_public_health","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("setfit_model_misinformation_on_mandates_public_health","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_model_misinformation_on_mandates_public_health| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/mitra-mir/setfit-model-Misinformation-on-Mandates-Public-Health \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-simple_test_model_en.md b/docs/_posts/ahmedlone127/2024-09-01-simple_test_model_en.md new file mode 100644 index 00000000000000..d8e2211be69787 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-simple_test_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English simple_test_model RoBertaForSequenceClassification from karalif +author: John Snow Labs +name: simple_test_model +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`simple_test_model` is a English model originally trained by karalif. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/simple_test_model_en_5.5.0_3.0_1725212596993.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/simple_test_model_en_5.5.0_3.0_1725212596993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("simple_test_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("simple_test_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|simple_test_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|428.1 MB| + +## References + +https://huggingface.co/karalif/simple-test-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-simple_test_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-simple_test_model_pipeline_en.md new file mode 100644 index 00000000000000..418e3de796c222 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-simple_test_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English simple_test_model_pipeline pipeline RoBertaForSequenceClassification from karalif +author: John Snow Labs +name: simple_test_model_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`simple_test_model_pipeline` is a English model originally trained by karalif. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/simple_test_model_pipeline_en_5.5.0_3.0_1725212636443.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/simple_test_model_pipeline_en_5.5.0_3.0_1725212636443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("simple_test_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("simple_test_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|simple_test_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|428.1 MB| + +## References + +https://huggingface.co/karalif/simple-test-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-sinhalaberto_si.md b/docs/_posts/ahmedlone127/2024-09-01-sinhalaberto_si.md new file mode 100644 index 00000000000000..b43a2d261feff8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-sinhalaberto_si.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Sinhala, Sinhalese sinhalaberto RoBertaEmbeddings from keshan +author: John Snow Labs +name: sinhalaberto +date: 2024-09-01 +tags: [si, open_source, onnx, embeddings, roberta] +task: Embeddings +language: si +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sinhalaberto` is a Sinhala, Sinhalese model originally trained by keshan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sinhalaberto_si_5.4.2_3.0_1725165065999.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sinhalaberto_si_5.4.2_3.0_1725165065999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("sinhalaberto","si") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("sinhalaberto","si") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sinhalaberto| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|si| +|Size:|311.7 MB| + +## References + +https://huggingface.co/keshan/SinhalaBERTo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-sle_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-sle_base_en.md new file mode 100644 index 00000000000000..ad7180acef29e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-sle_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sle_base RoBertaForSequenceClassification from liamcripwell +author: John Snow Labs +name: sle_base +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sle_base` is a English model originally trained by liamcripwell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sle_base_en_5.4.2_3.0_1725194523847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sle_base_en_5.4.2_3.0_1725194523847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("sle_base","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("sle_base", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sle_base| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|458.3 MB| + +## References + +https://huggingface.co/liamcripwell/sle-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-sle_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-sle_base_pipeline_en.md new file mode 100644 index 00000000000000..458c94fa5d2efe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-sle_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sle_base_pipeline pipeline RoBertaForSequenceClassification from liamcripwell +author: John Snow Labs +name: sle_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sle_base_pipeline` is a English model originally trained by liamcripwell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sle_base_pipeline_en_5.4.2_3.0_1725194552145.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sle_base_pipeline_en_5.4.2_3.0_1725194552145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sle_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sle_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sle_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|458.3 MB| + +## References + +https://huggingface.co/liamcripwell/sle-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-slovene_law_roberta_20_en.md b/docs/_posts/ahmedlone127/2024-09-01-slovene_law_roberta_20_en.md new file mode 100644 index 00000000000000..f597aa082c3468 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-slovene_law_roberta_20_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English slovene_law_roberta_20 RoBertaForQuestionAnswering from aseljayasooriya +author: John Snow Labs +name: slovene_law_roberta_20 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slovene_law_roberta_20` is a English model originally trained by aseljayasooriya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slovene_law_roberta_20_en_5.4.2_3.0_1725200465289.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slovene_law_roberta_20_en_5.4.2_3.0_1725200465289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("slovene_law_roberta_20","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("slovene_law_roberta_20", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|slovene_law_roberta_20| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.5 MB| + +## References + +https://huggingface.co/aseljayasooriya/sl-law-roberta-20 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-slovene_law_roberta_20_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-slovene_law_roberta_20_pipeline_en.md new file mode 100644 index 00000000000000..3fb9e35be17e4d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-slovene_law_roberta_20_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English slovene_law_roberta_20_pipeline pipeline RoBertaForQuestionAnswering from aseljayasooriya +author: John Snow Labs +name: slovene_law_roberta_20_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slovene_law_roberta_20_pipeline` is a English model originally trained by aseljayasooriya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slovene_law_roberta_20_pipeline_en_5.4.2_3.0_1725200491015.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slovene_law_roberta_20_pipeline_en_5.4.2_3.0_1725200491015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("slovene_law_roberta_20_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("slovene_law_roberta_20_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|slovene_law_roberta_20_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.5 MB| + +## References + +https://huggingface.co/aseljayasooriya/sl-law-roberta-20 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-smiles_bpe_pubchem_250k_en.md b/docs/_posts/ahmedlone127/2024-09-01-smiles_bpe_pubchem_250k_en.md new file mode 100644 index 00000000000000..d61c2665d8f41f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-smiles_bpe_pubchem_250k_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English smiles_bpe_pubchem_250k RoBertaEmbeddings from seyonec +author: John Snow Labs +name: smiles_bpe_pubchem_250k +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smiles_bpe_pubchem_250k` is a English model originally trained by seyonec. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smiles_bpe_pubchem_250k_en_5.4.2_3.0_1725191502207.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smiles_bpe_pubchem_250k_en_5.4.2_3.0_1725191502207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("smiles_bpe_pubchem_250k","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("smiles_bpe_pubchem_250k","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|smiles_bpe_pubchem_250k| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|310.0 MB| + +## References + +https://huggingface.co/seyonec/SMILES_BPE_PubChem_250k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-smiles_bpe_pubchem_250k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-smiles_bpe_pubchem_250k_pipeline_en.md new file mode 100644 index 00000000000000..637a2e94f518ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-smiles_bpe_pubchem_250k_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English smiles_bpe_pubchem_250k_pipeline pipeline RoBertaEmbeddings from seyonec +author: John Snow Labs +name: smiles_bpe_pubchem_250k_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smiles_bpe_pubchem_250k_pipeline` is a English model originally trained by seyonec. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smiles_bpe_pubchem_250k_pipeline_en_5.4.2_3.0_1725191518185.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smiles_bpe_pubchem_250k_pipeline_en_5.4.2_3.0_1725191518185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("smiles_bpe_pubchem_250k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("smiles_bpe_pubchem_250k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|smiles_bpe_pubchem_250k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|310.0 MB| + +## References + +https://huggingface.co/seyonec/SMILES_BPE_PubChem_250k + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-snli_microsoft_deberta_v3_base_seed_1_en.md b/docs/_posts/ahmedlone127/2024-09-01-snli_microsoft_deberta_v3_base_seed_1_en.md new file mode 100644 index 00000000000000..1873a0ca0d1c30 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-snli_microsoft_deberta_v3_base_seed_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English snli_microsoft_deberta_v3_base_seed_1 DeBertaForSequenceClassification from utahnlp +author: John Snow Labs +name: snli_microsoft_deberta_v3_base_seed_1 +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`snli_microsoft_deberta_v3_base_seed_1` is a English model originally trained by utahnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/snli_microsoft_deberta_v3_base_seed_1_en_5.5.0_3.0_1725223638024.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/snli_microsoft_deberta_v3_base_seed_1_en_5.5.0_3.0_1725223638024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("snli_microsoft_deberta_v3_base_seed_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("snli_microsoft_deberta_v3_base_seed_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|snli_microsoft_deberta_v3_base_seed_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|600.0 MB| + +## References + +https://huggingface.co/utahnlp/snli_microsoft_deberta-v3-base_seed-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-snli_microsoft_deberta_v3_base_seed_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-snli_microsoft_deberta_v3_base_seed_1_pipeline_en.md new file mode 100644 index 00000000000000..6afdebf110d2b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-snli_microsoft_deberta_v3_base_seed_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English snli_microsoft_deberta_v3_base_seed_1_pipeline pipeline DeBertaForSequenceClassification from utahnlp +author: John Snow Labs +name: snli_microsoft_deberta_v3_base_seed_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`snli_microsoft_deberta_v3_base_seed_1_pipeline` is a English model originally trained by utahnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/snli_microsoft_deberta_v3_base_seed_1_pipeline_en_5.5.0_3.0_1725223708304.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/snli_microsoft_deberta_v3_base_seed_1_pipeline_en_5.5.0_3.0_1725223708304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("snli_microsoft_deberta_v3_base_seed_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("snli_microsoft_deberta_v3_base_seed_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|snli_microsoft_deberta_v3_base_seed_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|600.0 MB| + +## References + +https://huggingface.co/utahnlp/snli_microsoft_deberta-v3-base_seed-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-snm_demo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-snm_demo_pipeline_en.md new file mode 100644 index 00000000000000..50141eda7828a3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-snm_demo_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English snm_demo_pipeline pipeline CamemBertForTokenClassification from Tippawan +author: John Snow Labs +name: snm_demo_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`snm_demo_pipeline` is a English model originally trained by Tippawan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/snm_demo_pipeline_en_5.4.2_3.0_1725175543871.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/snm_demo_pipeline_en_5.4.2_3.0_1725175543871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("snm_demo_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("snm_demo_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|snm_demo_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|392.2 MB| + +## References + +https://huggingface.co/Tippawan/SNM_demo + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-social_movement_stance_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-social_movement_stance_pipeline_en.md new file mode 100644 index 00000000000000..a115b7e1a333c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-social_movement_stance_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English social_movement_stance_pipeline pipeline RoBertaForSequenceClassification from juliamendelsohn +author: John Snow Labs +name: social_movement_stance_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`social_movement_stance_pipeline` is a English model originally trained by juliamendelsohn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/social_movement_stance_pipeline_en_5.4.2_3.0_1725166952927.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/social_movement_stance_pipeline_en_5.4.2_3.0_1725166952927.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("social_movement_stance_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("social_movement_stance_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|social_movement_stance_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.2 MB| + +## References + +https://huggingface.co/juliamendelsohn/social-movement-stance + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-spbert_mlm_wso_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-spbert_mlm_wso_base_en.md new file mode 100644 index 00000000000000..ebddda7f560a9e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-spbert_mlm_wso_base_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English spbert_mlm_wso_base BertEmbeddings from razent +author: John Snow Labs +name: spbert_mlm_wso_base +date: 2024-09-01 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spbert_mlm_wso_base` is a English model originally trained by razent. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spbert_mlm_wso_base_en_5.4.2_3.0_1725185753099.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spbert_mlm_wso_base_en_5.4.2_3.0_1725185753099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("spbert_mlm_wso_base","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("spbert_mlm_wso_base", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spbert_mlm_wso_base| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|403.5 MB| + +## References + +References + +https://huggingface.co/razent/spbert-mlm-wso-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-spbert_mlm_wso_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-spbert_mlm_wso_base_pipeline_en.md new file mode 100644 index 00000000000000..f93fa3abd82038 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-spbert_mlm_wso_base_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English spbert_mlm_wso_base_pipeline pipeline BertForQuestionAnswering from razent +author: John Snow Labs +name: spbert_mlm_wso_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spbert_mlm_wso_base_pipeline` is a English model originally trained by razent. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spbert_mlm_wso_base_pipeline_en_5.4.2_3.0_1725185773655.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spbert_mlm_wso_base_pipeline_en_5.4.2_3.0_1725185773655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("spbert_mlm_wso_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("spbert_mlm_wso_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spbert_mlm_wso_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.5 MB| + +## References + +https://huggingface.co/razent/spbert-mlm-wso-base + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-spm_vietnamese_deberta_en.md b/docs/_posts/ahmedlone127/2024-09-01-spm_vietnamese_deberta_en.md new file mode 100644 index 00000000000000..c79c41f9fc45fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-spm_vietnamese_deberta_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English spm_vietnamese_deberta DeBertaEmbeddings from hieule +author: John Snow Labs +name: spm_vietnamese_deberta +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spm_vietnamese_deberta` is a English model originally trained by hieule. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spm_vietnamese_deberta_en_5.5.0_3.0_1725217480366.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spm_vietnamese_deberta_en_5.5.0_3.0_1725217480366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("spm_vietnamese_deberta","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("spm_vietnamese_deberta","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spm_vietnamese_deberta| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|289.7 MB| + +## References + +https://huggingface.co/hieule/spm-vie-deberta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-spm_vietnamese_deberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-spm_vietnamese_deberta_pipeline_en.md new file mode 100644 index 00000000000000..cb8ccf89ad783c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-spm_vietnamese_deberta_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English spm_vietnamese_deberta_pipeline pipeline DeBertaEmbeddings from hieule +author: John Snow Labs +name: spm_vietnamese_deberta_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spm_vietnamese_deberta_pipeline` is a English model originally trained by hieule. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spm_vietnamese_deberta_pipeline_en_5.5.0_3.0_1725217496278.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spm_vietnamese_deberta_pipeline_en_5.5.0_3.0_1725217496278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("spm_vietnamese_deberta_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("spm_vietnamese_deberta_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spm_vietnamese_deberta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|289.7 MB| + +## References + +https://huggingface.co/hieule/spm-vie-deberta + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-sports_klue_finetuned_korquad_nosplit_nsp_batch32_en.md b/docs/_posts/ahmedlone127/2024-09-01-sports_klue_finetuned_korquad_nosplit_nsp_batch32_en.md new file mode 100644 index 00000000000000..1f9cdaa259ff88 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-sports_klue_finetuned_korquad_nosplit_nsp_batch32_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English sports_klue_finetuned_korquad_nosplit_nsp_batch32 BertForQuestionAnswering from Kdogs +author: John Snow Labs +name: sports_klue_finetuned_korquad_nosplit_nsp_batch32 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sports_klue_finetuned_korquad_nosplit_nsp_batch32` is a English model originally trained by Kdogs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sports_klue_finetuned_korquad_nosplit_nsp_batch32_en_5.5.0_3.0_1725215368397.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sports_klue_finetuned_korquad_nosplit_nsp_batch32_en_5.5.0_3.0_1725215368397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("sports_klue_finetuned_korquad_nosplit_nsp_batch32","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("sports_klue_finetuned_korquad_nosplit_nsp_batch32", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sports_klue_finetuned_korquad_nosplit_nsp_batch32| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|412.4 MB| + +## References + +https://huggingface.co/Kdogs/sports_klue_finetuned_korquad_noSplit_NSP_batch32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-sports_klue_finetuned_korquad_nosplit_nsp_batch32_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-sports_klue_finetuned_korquad_nosplit_nsp_batch32_pipeline_en.md new file mode 100644 index 00000000000000..be738d00fd87ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-sports_klue_finetuned_korquad_nosplit_nsp_batch32_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English sports_klue_finetuned_korquad_nosplit_nsp_batch32_pipeline pipeline BertForQuestionAnswering from Kdogs +author: John Snow Labs +name: sports_klue_finetuned_korquad_nosplit_nsp_batch32_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sports_klue_finetuned_korquad_nosplit_nsp_batch32_pipeline` is a English model originally trained by Kdogs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sports_klue_finetuned_korquad_nosplit_nsp_batch32_pipeline_en_5.5.0_3.0_1725215390546.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sports_klue_finetuned_korquad_nosplit_nsp_batch32_pipeline_en_5.5.0_3.0_1725215390546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sports_klue_finetuned_korquad_nosplit_nsp_batch32_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sports_klue_finetuned_korquad_nosplit_nsp_batch32_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sports_klue_finetuned_korquad_nosplit_nsp_batch32_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.4 MB| + +## References + +https://huggingface.co/Kdogs/sports_klue_finetuned_korquad_noSplit_NSP_batch32 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-squeezebert_mnli_en.md b/docs/_posts/ahmedlone127/2024-09-01-squeezebert_mnli_en.md new file mode 100644 index 00000000000000..9e0794a1bddb03 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-squeezebert_mnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English squeezebert_mnli BertForZeroShotClassification from typeform +author: John Snow Labs +name: squeezebert_mnli +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, bert] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`squeezebert_mnli` is a English model originally trained by typeform. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/squeezebert_mnli_en_5.4.2_3.0_1725208077350.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squeezebert_mnli_en_5.4.2_3.0_1725208077350.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +zeroShotClassifier = BertForZeroShotClassification.pretrained("squeezebert_mnli","en") \ + .setInputCols(["document","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val zeroShotClassifier = BertForZeroShotClassification.pretrained("squeezebert_mnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|squeezebert_mnli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|185.0 MB| + +## References + +https://huggingface.co/typeform/squeezebert-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-squeezebert_mnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-squeezebert_mnli_pipeline_en.md new file mode 100644 index 00000000000000..97ba26ef6ccdf8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-squeezebert_mnli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English squeezebert_mnli_pipeline pipeline BertForZeroShotClassification from typeform +author: John Snow Labs +name: squeezebert_mnli_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`squeezebert_mnli_pipeline` is a English model originally trained by typeform. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/squeezebert_mnli_pipeline_en_5.4.2_3.0_1725208088871.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squeezebert_mnli_pipeline_en_5.4.2_3.0_1725208088871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("squeezebert_mnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("squeezebert_mnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|squeezebert_mnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|185.0 MB| + +## References + +https://huggingface.co/typeform/squeezebert-mnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-student_reasoning_en.md b/docs/_posts/ahmedlone127/2024-09-01-student_reasoning_en.md new file mode 100644 index 00000000000000..4804f0da6df409 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-student_reasoning_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English student_reasoning BertForSequenceClassification from ddemszky +author: John Snow Labs +name: student_reasoning +date: 2024-09-01 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`student_reasoning` is a English model originally trained by ddemszky. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/student_reasoning_en_5.4.2_3.0_1725204968115.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/student_reasoning_en_5.4.2_3.0_1725204968115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("student_reasoning","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("student_reasoning","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|student_reasoning| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +References + +https://huggingface.co/ddemszky/student-reasoning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-student_reasoning_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-student_reasoning_pipeline_en.md new file mode 100644 index 00000000000000..020d1efae16bad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-student_reasoning_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English student_reasoning_pipeline pipeline BertForSequenceClassification from stanford-nlpxed +author: John Snow Labs +name: student_reasoning_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`student_reasoning_pipeline` is a English model originally trained by stanford-nlpxed. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/student_reasoning_pipeline_en_5.4.2_3.0_1725204990348.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/student_reasoning_pipeline_en_5.4.2_3.0_1725204990348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("student_reasoning_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("student_reasoning_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|student_reasoning_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/stanford-nlpxed/student-reasoning + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-subreddit_description_topic_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-01-subreddit_description_topic_classifier_en.md new file mode 100644 index 00000000000000..8e11cd96bee93c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-subreddit_description_topic_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English subreddit_description_topic_classifier DistilBertForSequenceClassification from gulnuravci +author: John Snow Labs +name: subreddit_description_topic_classifier +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`subreddit_description_topic_classifier` is a English model originally trained by gulnuravci. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/subreddit_description_topic_classifier_en_5.5.0_3.0_1725213650710.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/subreddit_description_topic_classifier_en_5.5.0_3.0_1725213650710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("subreddit_description_topic_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("subreddit_description_topic_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|subreddit_description_topic_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/gulnuravci/subreddit_description_topic_classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-takalane_xho_roberta_en.md b/docs/_posts/ahmedlone127/2024-09-01-takalane_xho_roberta_en.md new file mode 100644 index 00000000000000..f1f2e03fd98e73 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-takalane_xho_roberta_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English takalane_xho_roberta RoBertaEmbeddings from jannesg +author: John Snow Labs +name: takalane_xho_roberta +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`takalane_xho_roberta` is a English model originally trained by jannesg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/takalane_xho_roberta_en_5.4.2_3.0_1725191240125.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/takalane_xho_roberta_en_5.4.2_3.0_1725191240125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("takalane_xho_roberta","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("takalane_xho_roberta","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|takalane_xho_roberta| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|311.4 MB| + +## References + +https://huggingface.co/jannesg/takalane_xho_roberta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-takalane_xho_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-takalane_xho_roberta_pipeline_en.md new file mode 100644 index 00000000000000..85885c8d2850c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-takalane_xho_roberta_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English takalane_xho_roberta_pipeline pipeline RoBertaEmbeddings from jannesg +author: John Snow Labs +name: takalane_xho_roberta_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`takalane_xho_roberta_pipeline` is a English model originally trained by jannesg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/takalane_xho_roberta_pipeline_en_5.4.2_3.0_1725191258517.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/takalane_xho_roberta_pipeline_en_5.4.2_3.0_1725191258517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("takalane_xho_roberta_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("takalane_xho_roberta_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|takalane_xho_roberta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|311.4 MB| + +## References + +https://huggingface.co/jannesg/takalane_xho_roberta + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-tamilner_en.md b/docs/_posts/ahmedlone127/2024-09-01-tamilner_en.md new file mode 100644 index 00000000000000..fab240d15f1911 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-tamilner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tamilner AlbertForTokenClassification from Rishihesaan +author: John Snow Labs +name: tamilner +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, albert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tamilner` is a English model originally trained by Rishihesaan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tamilner_en_5.4.2_3.0_1725203378787.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tamilner_en_5.4.2_3.0_1725203378787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = AlbertForTokenClassification.pretrained("tamilner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = AlbertForTokenClassification.pretrained("tamilner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tamilner| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|125.6 MB| + +## References + +https://huggingface.co/Rishihesaan/TamilNER \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-tamilner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-tamilner_pipeline_en.md new file mode 100644 index 00000000000000..9d6d93ea544ee8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-tamilner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tamilner_pipeline pipeline AlbertForTokenClassification from Rishihesaan +author: John Snow Labs +name: tamilner_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tamilner_pipeline` is a English model originally trained by Rishihesaan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tamilner_pipeline_en_5.4.2_3.0_1725203385172.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tamilner_pipeline_en_5.4.2_3.0_1725203385172.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tamilner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tamilner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tamilner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|125.6 MB| + +## References + +https://huggingface.co/Rishihesaan/TamilNER + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-tapt_nbme_deberta_v3_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-tapt_nbme_deberta_v3_base_en.md new file mode 100644 index 00000000000000..5acd1ece8a2df7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-tapt_nbme_deberta_v3_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tapt_nbme_deberta_v3_base DeBertaEmbeddings from ZZ99 +author: John Snow Labs +name: tapt_nbme_deberta_v3_base +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tapt_nbme_deberta_v3_base` is a English model originally trained by ZZ99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tapt_nbme_deberta_v3_base_en_5.5.0_3.0_1725217771940.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tapt_nbme_deberta_v3_base_en_5.5.0_3.0_1725217771940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("tapt_nbme_deberta_v3_base","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("tapt_nbme_deberta_v3_base","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tapt_nbme_deberta_v3_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|687.5 MB| + +## References + +https://huggingface.co/ZZ99/tapt_nbme_deberta_v3_base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-tapt_nbme_deberta_v3_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-tapt_nbme_deberta_v3_base_pipeline_en.md new file mode 100644 index 00000000000000..d311b59235e86c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-tapt_nbme_deberta_v3_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tapt_nbme_deberta_v3_base_pipeline pipeline DeBertaEmbeddings from ZZ99 +author: John Snow Labs +name: tapt_nbme_deberta_v3_base_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tapt_nbme_deberta_v3_base_pipeline` is a English model originally trained by ZZ99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tapt_nbme_deberta_v3_base_pipeline_en_5.5.0_3.0_1725217808580.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tapt_nbme_deberta_v3_base_pipeline_en_5.5.0_3.0_1725217808580.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tapt_nbme_deberta_v3_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tapt_nbme_deberta_v3_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tapt_nbme_deberta_v3_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|687.5 MB| + +## References + +https://huggingface.co/ZZ99/tapt_nbme_deberta_v3_base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-task_subtle_task__model_deberta__aug_method_none_en.md b/docs/_posts/ahmedlone127/2024-09-01-task_subtle_task__model_deberta__aug_method_none_en.md new file mode 100644 index 00000000000000..2d10a582f00abd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-task_subtle_task__model_deberta__aug_method_none_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English task_subtle_task__model_deberta__aug_method_none DeBertaForSequenceClassification from BenjaminOcampo +author: John Snow Labs +name: task_subtle_task__model_deberta__aug_method_none +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_subtle_task__model_deberta__aug_method_none` is a English model originally trained by BenjaminOcampo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_deberta__aug_method_none_en_5.5.0_3.0_1725209492701.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_deberta__aug_method_none_en_5.5.0_3.0_1725209492701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("task_subtle_task__model_deberta__aug_method_none","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("task_subtle_task__model_deberta__aug_method_none", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|task_subtle_task__model_deberta__aug_method_none| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|607.3 MB| + +## References + +https://huggingface.co/BenjaminOcampo/task-subtle_task__model-deberta__aug_method-None \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-task_subtle_task__model_deberta__aug_method_none_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-task_subtle_task__model_deberta__aug_method_none_pipeline_en.md new file mode 100644 index 00000000000000..60b7226595a65e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-task_subtle_task__model_deberta__aug_method_none_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English task_subtle_task__model_deberta__aug_method_none_pipeline pipeline DeBertaForSequenceClassification from BenjaminOcampo +author: John Snow Labs +name: task_subtle_task__model_deberta__aug_method_none_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_subtle_task__model_deberta__aug_method_none_pipeline` is a English model originally trained by BenjaminOcampo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_deberta__aug_method_none_pipeline_en_5.5.0_3.0_1725209541030.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_deberta__aug_method_none_pipeline_en_5.5.0_3.0_1725209541030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("task_subtle_task__model_deberta__aug_method_none_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("task_subtle_task__model_deberta__aug_method_none_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|task_subtle_task__model_deberta__aug_method_none_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|607.3 MB| + +## References + +https://huggingface.co/BenjaminOcampo/task-subtle_task__model-deberta__aug_method-None + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-task_subtle_task__model_deberta__aug_method_rne_en.md b/docs/_posts/ahmedlone127/2024-09-01-task_subtle_task__model_deberta__aug_method_rne_en.md new file mode 100644 index 00000000000000..c9532fa291900b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-task_subtle_task__model_deberta__aug_method_rne_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English task_subtle_task__model_deberta__aug_method_rne DeBertaForSequenceClassification from BenjaminOcampo +author: John Snow Labs +name: task_subtle_task__model_deberta__aug_method_rne +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_subtle_task__model_deberta__aug_method_rne` is a English model originally trained by BenjaminOcampo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_deberta__aug_method_rne_en_5.5.0_3.0_1725223370234.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_deberta__aug_method_rne_en_5.5.0_3.0_1725223370234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("task_subtle_task__model_deberta__aug_method_rne","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("task_subtle_task__model_deberta__aug_method_rne", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|task_subtle_task__model_deberta__aug_method_rne| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|607.4 MB| + +## References + +https://huggingface.co/BenjaminOcampo/task-subtle_task__model-deberta__aug_method-rne \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-task_subtle_task__model_deberta__aug_method_rne_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-task_subtle_task__model_deberta__aug_method_rne_pipeline_en.md new file mode 100644 index 00000000000000..7ee9e6c0eb9d90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-task_subtle_task__model_deberta__aug_method_rne_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English task_subtle_task__model_deberta__aug_method_rne_pipeline pipeline DeBertaForSequenceClassification from BenjaminOcampo +author: John Snow Labs +name: task_subtle_task__model_deberta__aug_method_rne_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_subtle_task__model_deberta__aug_method_rne_pipeline` is a English model originally trained by BenjaminOcampo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_deberta__aug_method_rne_pipeline_en_5.5.0_3.0_1725223414043.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_deberta__aug_method_rne_pipeline_en_5.5.0_3.0_1725223414043.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("task_subtle_task__model_deberta__aug_method_rne_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("task_subtle_task__model_deberta__aug_method_rne_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|task_subtle_task__model_deberta__aug_method_rne_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|607.4 MB| + +## References + +https://huggingface.co/BenjaminOcampo/task-subtle_task__model-deberta__aug_method-rne + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-test_model2_en.md b/docs/_posts/ahmedlone127/2024-09-01-test_model2_en.md new file mode 100644 index 00000000000000..923b9ef0fd45b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-test_model2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English test_model2 AlbertEmbeddings from yzhou992 +author: John Snow Labs +name: test_model2 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, albert] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model2` is a English model originally trained by yzhou992. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model2_en_5.4.2_3.0_1725205738527.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model2_en_5.4.2_3.0_1725205738527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = AlbertEmbeddings.pretrained("test_model2","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = AlbertEmbeddings.pretrained("test_model2","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_model2| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[albert]| +|Language:|en| +|Size:|62.7 MB| + +## References + +https://huggingface.co/yzhou992/test_model2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-test_model2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-test_model2_pipeline_en.md new file mode 100644 index 00000000000000..21336fe11e73a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-test_model2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English test_model2_pipeline pipeline AlbertEmbeddings from yzhou992 +author: John Snow Labs +name: test_model2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model2_pipeline` is a English model originally trained by yzhou992. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model2_pipeline_en_5.4.2_3.0_1725205741978.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model2_pipeline_en_5.4.2_3.0_1725205741978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("test_model2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("test_model2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_model2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|62.7 MB| + +## References + +https://huggingface.co/yzhou992/test_model2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-test_pipeline_en.md new file mode 100644 index 00000000000000..154ab442726bb0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-test_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English test_pipeline pipeline DistilBertForTokenClassification from yam1ke +author: John Snow Labs +name: test_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_pipeline` is a English model originally trained by yam1ke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_pipeline_en_5.4.2_3.0_1725171287200.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_pipeline_en_5.4.2_3.0_1725171287200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("test_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("test_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/yam1ke/test + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-testing_destilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-testing_destilbert_pipeline_en.md new file mode 100644 index 00000000000000..15d4067f91b4ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-testing_destilbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English testing_destilbert_pipeline pipeline DistilBertForTokenClassification from andrembcosta +author: John Snow Labs +name: testing_destilbert_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testing_destilbert_pipeline` is a English model originally trained by andrembcosta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testing_destilbert_pipeline_en_5.4.2_3.0_1725160588884.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testing_destilbert_pipeline_en_5.4.2_3.0_1725160588884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("testing_destilbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("testing_destilbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|testing_destilbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/andrembcosta/testing-destilbert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-testing_en.md b/docs/_posts/ahmedlone127/2024-09-01-testing_en.md new file mode 100644 index 00000000000000..c9b1091946bc87 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-testing_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English testing AlbertForQuestionAnswering from saburbutt +author: John Snow Labs +name: testing +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testing` is a English model originally trained by saburbutt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testing_en_5.4.2_3.0_1725193475328.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testing_en_5.4.2_3.0_1725193475328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("testing","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("testing", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|testing| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|771.0 MB| + +## References + +https://huggingface.co/saburbutt/testing \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-testing_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-testing_pipeline_en.md new file mode 100644 index 00000000000000..aa1ca45d9d85a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-testing_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English testing_pipeline pipeline AlbertForQuestionAnswering from saburbutt +author: John Snow Labs +name: testing_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testing_pipeline` is a English model originally trained by saburbutt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testing_pipeline_en_5.4.2_3.0_1725193515044.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testing_pipeline_en_5.4.2_3.0_1725193515044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("testing_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("testing_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|testing_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|771.0 MB| + +## References + +https://huggingface.co/saburbutt/testing + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-tiny_random_albertformaskedlm_hf_tiny_model_private_en.md b/docs/_posts/ahmedlone127/2024-09-01-tiny_random_albertformaskedlm_hf_tiny_model_private_en.md new file mode 100644 index 00000000000000..9805a088e49d52 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-tiny_random_albertformaskedlm_hf_tiny_model_private_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tiny_random_albertformaskedlm_hf_tiny_model_private AlbertEmbeddings from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_albertformaskedlm_hf_tiny_model_private +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, albert] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_albertformaskedlm_hf_tiny_model_private` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_albertformaskedlm_hf_tiny_model_private_en_5.4.2_3.0_1725205737820.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_albertformaskedlm_hf_tiny_model_private_en_5.4.2_3.0_1725205737820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = AlbertEmbeddings.pretrained("tiny_random_albertformaskedlm_hf_tiny_model_private","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = AlbertEmbeddings.pretrained("tiny_random_albertformaskedlm_hf_tiny_model_private","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_albertformaskedlm_hf_tiny_model_private| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[albert]| +|Language:|en| +|Size:|15.2 MB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-AlbertForMaskedLM \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-tiny_random_albertformaskedlm_hf_tiny_model_private_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-tiny_random_albertformaskedlm_hf_tiny_model_private_pipeline_en.md new file mode 100644 index 00000000000000..9472194949953e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-tiny_random_albertformaskedlm_hf_tiny_model_private_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tiny_random_albertformaskedlm_hf_tiny_model_private_pipeline pipeline AlbertEmbeddings from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_albertformaskedlm_hf_tiny_model_private_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_albertformaskedlm_hf_tiny_model_private_pipeline` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_albertformaskedlm_hf_tiny_model_private_pipeline_en_5.4.2_3.0_1725205738997.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_albertformaskedlm_hf_tiny_model_private_pipeline_en_5.4.2_3.0_1725205738997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tiny_random_albertformaskedlm_hf_tiny_model_private_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tiny_random_albertformaskedlm_hf_tiny_model_private_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_albertformaskedlm_hf_tiny_model_private_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|15.2 MB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-AlbertForMaskedLM + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_finetuned_squad_en.md new file mode 100644 index 00000000000000..74dbc8b1efea33 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_finetuned_squad_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English tinyroberta_squad2_finetuned_squad RoBertaForQuestionAnswering from ahujaniharika95 +author: John Snow Labs +name: tinyroberta_squad2_finetuned_squad +date: 2024-09-01 +tags: [roberta, en, open_source, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinyroberta_squad2_finetuned_squad` is a English model originally trained by ahujaniharika95. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_finetuned_squad_en_5.4.2_3.0_1725206400056.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_finetuned_squad_en_5.4.2_3.0_1725206400056.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + + +spanClassifier = RoBertaForQuestionAnswering.pretrained("tinyroberta_squad2_finetuned_squad","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([document_assembler, spanClassifier]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) +``` +```scala +val document_assembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering + .pretrained("tinyroberta_squad2_finetuned_squad", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tinyroberta_squad2_finetuned_squad| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|306.9 MB| + +## References + +References + +https://huggingface.co/ahujaniharika95/tinyroberta-squad2-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_finetuned_squad_pipeline_en.md new file mode 100644 index 00000000000000..e9b782d92a607d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_finetuned_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English tinyroberta_squad2_finetuned_squad_pipeline pipeline RoBertaForQuestionAnswering from JohnDoe70 +author: John Snow Labs +name: tinyroberta_squad2_finetuned_squad_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinyroberta_squad2_finetuned_squad_pipeline` is a English model originally trained by JohnDoe70. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_finetuned_squad_pipeline_en_5.4.2_3.0_1725206416462.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_finetuned_squad_pipeline_en_5.4.2_3.0_1725206416462.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tinyroberta_squad2_finetuned_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tinyroberta_squad2_finetuned_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tinyroberta_squad2_finetuned_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|306.9 MB| + +## References + +https://huggingface.co/JohnDoe70/tinyroberta-squad2-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_mary8_en.md b/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_mary8_en.md new file mode 100644 index 00000000000000..00091ffdaedb86 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_mary8_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English tinyroberta_squad2_mary8 RoBertaForQuestionAnswering from Mary8 +author: John Snow Labs +name: tinyroberta_squad2_mary8 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinyroberta_squad2_mary8` is a English model originally trained by Mary8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_mary8_en_5.4.2_3.0_1725200654821.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_mary8_en_5.4.2_3.0_1725200654821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("tinyroberta_squad2_mary8","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("tinyroberta_squad2_mary8", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tinyroberta_squad2_mary8| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|306.9 MB| + +## References + +https://huggingface.co/Mary8/tinyroberta-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_mary8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_mary8_pipeline_en.md new file mode 100644 index 00000000000000..34d1419a5194f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_mary8_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English tinyroberta_squad2_mary8_pipeline pipeline RoBertaForQuestionAnswering from Mary8 +author: John Snow Labs +name: tinyroberta_squad2_mary8_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinyroberta_squad2_mary8_pipeline` is a English model originally trained by Mary8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_mary8_pipeline_en_5.4.2_3.0_1725200677881.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_mary8_pipeline_en_5.4.2_3.0_1725200677881.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tinyroberta_squad2_mary8_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tinyroberta_squad2_mary8_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tinyroberta_squad2_mary8_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|306.9 MB| + +## References + +https://huggingface.co/Mary8/tinyroberta-squad2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_step1_en.md b/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_step1_en.md new file mode 100644 index 00000000000000..0ffabe06d0316e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_step1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English tinyroberta_squad2_step1 RoBertaForQuestionAnswering from Mary8 +author: John Snow Labs +name: tinyroberta_squad2_step1 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinyroberta_squad2_step1` is a English model originally trained by Mary8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_step1_en_5.4.2_3.0_1725206604645.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_step1_en_5.4.2_3.0_1725206604645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("tinyroberta_squad2_step1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("tinyroberta_squad2_step1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tinyroberta_squad2_step1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|306.9 MB| + +## References + +https://huggingface.co/Mary8/tinyroberta-squad2-step1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_step1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_step1_pipeline_en.md new file mode 100644 index 00000000000000..e677a561b3bab0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-tinyroberta_squad2_step1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English tinyroberta_squad2_step1_pipeline pipeline RoBertaForQuestionAnswering from Mary8 +author: John Snow Labs +name: tinyroberta_squad2_step1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinyroberta_squad2_step1_pipeline` is a English model originally trained by Mary8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_step1_pipeline_en_5.4.2_3.0_1725206621553.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_step1_pipeline_en_5.4.2_3.0_1725206621553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tinyroberta_squad2_step1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tinyroberta_squad2_step1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tinyroberta_squad2_step1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|306.9 MB| + +## References + +https://huggingface.co/Mary8/tinyroberta-squad2-step1 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-token_classification_66m_v0_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-token_classification_66m_v0_1_pipeline_en.md new file mode 100644 index 00000000000000..a82e2ccca7bbaa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-token_classification_66m_v0_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English token_classification_66m_v0_1_pipeline pipeline DistilBertForTokenClassification from jwt2706 +author: John Snow Labs +name: token_classification_66m_v0_1_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`token_classification_66m_v0_1_pipeline` is a English model originally trained by jwt2706. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/token_classification_66m_v0_1_pipeline_en_5.4.2_3.0_1725171268731.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/token_classification_66m_v0_1_pipeline_en_5.4.2_3.0_1725171268731.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("token_classification_66m_v0_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("token_classification_66m_v0_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|token_classification_66m_v0_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/jwt2706/token-classification-66M-v0.1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-topic_govt_regulation_en.md b/docs/_posts/ahmedlone127/2024-09-01-topic_govt_regulation_en.md new file mode 100644 index 00000000000000..e50c1f5ec34591 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-topic_govt_regulation_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English topic_govt_regulation RoBertaForSequenceClassification from dell-research-harvard +author: John Snow Labs +name: topic_govt_regulation +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_govt_regulation` is a English model originally trained by dell-research-harvard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/topic_govt_regulation_en_5.5.0_3.0_1725211816924.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_govt_regulation_en_5.5.0_3.0_1725211816924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("topic_govt_regulation","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("topic_govt_regulation", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|topic_govt_regulation| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/dell-research-harvard/topic-govt_regulation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-topic_govt_regulation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-topic_govt_regulation_pipeline_en.md new file mode 100644 index 00000000000000..c8d09ed7823bcf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-topic_govt_regulation_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English topic_govt_regulation_pipeline pipeline RoBertaForSequenceClassification from dell-research-harvard +author: John Snow Labs +name: topic_govt_regulation_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_govt_regulation_pipeline` is a English model originally trained by dell-research-harvard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/topic_govt_regulation_pipeline_en_5.5.0_3.0_1725211901265.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_govt_regulation_pipeline_en_5.5.0_3.0_1725211901265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("topic_govt_regulation_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("topic_govt_regulation_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|topic_govt_regulation_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/dell-research-harvard/topic-govt_regulation + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-topic_labor_movement_en.md b/docs/_posts/ahmedlone127/2024-09-01-topic_labor_movement_en.md new file mode 100644 index 00000000000000..97734a56b602cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-topic_labor_movement_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English topic_labor_movement RoBertaForSequenceClassification from dell-research-harvard +author: John Snow Labs +name: topic_labor_movement +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_labor_movement` is a English model originally trained by dell-research-harvard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/topic_labor_movement_en_5.4.2_3.0_1725194740558.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_labor_movement_en_5.4.2_3.0_1725194740558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("topic_labor_movement","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("topic_labor_movement", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|topic_labor_movement| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|309.0 MB| + +## References + +https://huggingface.co/dell-research-harvard/topic-labor_movement \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-topicawarestallmpnetbasev2wiki_en.md b/docs/_posts/ahmedlone127/2024-09-01-topicawarestallmpnetbasev2wiki_en.md new file mode 100644 index 00000000000000..5a32a1c6d64597 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-topicawarestallmpnetbasev2wiki_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English topicawarestallmpnetbasev2wiki MPNetEmbeddings from textgain +author: John Snow Labs +name: topicawarestallmpnetbasev2wiki +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topicawarestallmpnetbasev2wiki` is a English model originally trained by textgain. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/topicawarestallmpnetbasev2wiki_en_5.5.0_3.0_1725224592867.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topicawarestallmpnetbasev2wiki_en_5.5.0_3.0_1725224592867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("topicawarestallmpnetbasev2wiki","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("topicawarestallmpnetbasev2wiki","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|topicawarestallmpnetbasev2wiki| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/textgain/TopicAwareSTallmpnetbasev2Wiki \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-topicawarestallmpnetbasev2wiki_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-topicawarestallmpnetbasev2wiki_pipeline_en.md new file mode 100644 index 00000000000000..cd3de87f98a5fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-topicawarestallmpnetbasev2wiki_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English topicawarestallmpnetbasev2wiki_pipeline pipeline MPNetEmbeddings from textgain +author: John Snow Labs +name: topicawarestallmpnetbasev2wiki_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topicawarestallmpnetbasev2wiki_pipeline` is a English model originally trained by textgain. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/topicawarestallmpnetbasev2wiki_pipeline_en_5.5.0_3.0_1725224620658.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topicawarestallmpnetbasev2wiki_pipeline_en_5.5.0_3.0_1725224620658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("topicawarestallmpnetbasev2wiki_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("topicawarestallmpnetbasev2wiki_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|topicawarestallmpnetbasev2wiki_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/textgain/TopicAwareSTallmpnetbasev2Wiki + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-trained_polish_en.md b/docs/_posts/ahmedlone127/2024-09-01-trained_polish_en.md new file mode 100644 index 00000000000000..7a1a5296b93a9a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-trained_polish_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English trained_polish DistilBertForTokenClassification from annamariagnat +author: John Snow Labs +name: trained_polish +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_polish` is a English model originally trained by annamariagnat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trained_polish_en_5.4.2_3.0_1725171019814.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_polish_en_5.4.2_3.0_1725171019814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("trained_polish","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("trained_polish", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|trained_polish| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|505.4 MB| + +## References + +https://huggingface.co/annamariagnat/trained_polish \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-training_with_callbacks_en.md b/docs/_posts/ahmedlone127/2024-09-01-training_with_callbacks_en.md new file mode 100644 index 00000000000000..309601650076e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-training_with_callbacks_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English training_with_callbacks DistilBertForTokenClassification from cria111 +author: John Snow Labs +name: training_with_callbacks +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`training_with_callbacks` is a English model originally trained by cria111. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/training_with_callbacks_en_5.4.2_3.0_1725170614537.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/training_with_callbacks_en_5.4.2_3.0_1725170614537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("training_with_callbacks","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("training_with_callbacks", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|training_with_callbacks| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/cria111/training_with_callbacks \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-training_with_callbacks_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-training_with_callbacks_pipeline_en.md new file mode 100644 index 00000000000000..c0851fa15ce691 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-training_with_callbacks_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English training_with_callbacks_pipeline pipeline DistilBertForTokenClassification from cria111 +author: John Snow Labs +name: training_with_callbacks_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`training_with_callbacks_pipeline` is a English model originally trained by cria111. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/training_with_callbacks_pipeline_en_5.4.2_3.0_1725170628449.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/training_with_callbacks_pipeline_en_5.4.2_3.0_1725170628449.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("training_with_callbacks_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("training_with_callbacks_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|training_with_callbacks_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/cria111/training_with_callbacks + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-trans_encoder_cross_simcse_roberta_large_en.md b/docs/_posts/ahmedlone127/2024-09-01-trans_encoder_cross_simcse_roberta_large_en.md new file mode 100644 index 00000000000000..c1127df2875168 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-trans_encoder_cross_simcse_roberta_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English trans_encoder_cross_simcse_roberta_large RoBertaForSequenceClassification from cambridgeltl +author: John Snow Labs +name: trans_encoder_cross_simcse_roberta_large +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trans_encoder_cross_simcse_roberta_large` is a English model originally trained by cambridgeltl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trans_encoder_cross_simcse_roberta_large_en_5.5.0_3.0_1725212844530.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trans_encoder_cross_simcse_roberta_large_en_5.5.0_3.0_1725212844530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("trans_encoder_cross_simcse_roberta_large","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("trans_encoder_cross_simcse_roberta_large", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|trans_encoder_cross_simcse_roberta_large| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/cambridgeltl/trans-encoder-cross-simcse-roberta-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-trans_encoder_cross_simcse_roberta_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-trans_encoder_cross_simcse_roberta_large_pipeline_en.md new file mode 100644 index 00000000000000..09a204f942ce7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-trans_encoder_cross_simcse_roberta_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English trans_encoder_cross_simcse_roberta_large_pipeline pipeline RoBertaForSequenceClassification from cambridgeltl +author: John Snow Labs +name: trans_encoder_cross_simcse_roberta_large_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trans_encoder_cross_simcse_roberta_large_pipeline` is a English model originally trained by cambridgeltl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trans_encoder_cross_simcse_roberta_large_pipeline_en_5.5.0_3.0_1725212916170.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trans_encoder_cross_simcse_roberta_large_pipeline_en_5.5.0_3.0_1725212916170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("trans_encoder_cross_simcse_roberta_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("trans_encoder_cross_simcse_roberta_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|trans_encoder_cross_simcse_roberta_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/cambridgeltl/trans-encoder-cross-simcse-roberta-large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_emoji_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_emoji_en.md new file mode 100644 index 00000000000000..bcc3c2c6bdaf29 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_emoji_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English twitter_roberta_base_emoji RoBertaForSequenceClassification from cardiffnlp +author: John Snow Labs +name: twitter_roberta_base_emoji +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_emoji` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emoji_en_5.4.2_3.0_1725194900775.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emoji_en_5.4.2_3.0_1725194900775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_emoji","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_emoji", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_roberta_base_emoji| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.2 MB| + +## References + +https://huggingface.co/cardiffnlp/twitter-roberta-base-emoji \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_emoji_latest_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_emoji_latest_en.md new file mode 100644 index 00000000000000..0595d3bfffc416 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_emoji_latest_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English twitter_roberta_base_emoji_latest RoBertaForSequenceClassification from cardiffnlp +author: John Snow Labs +name: twitter_roberta_base_emoji_latest +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_emoji_latest` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emoji_latest_en_5.4.2_3.0_1725195278717.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emoji_latest_en_5.4.2_3.0_1725195278717.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_emoji_latest","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_emoji_latest", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_roberta_base_emoji_latest| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.5 MB| + +## References + +https://huggingface.co/cardiffnlp/twitter-roberta-base-emoji-latest \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_emoji_latest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_emoji_latest_pipeline_en.md new file mode 100644 index 00000000000000..8f856e45cfac75 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_emoji_latest_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English twitter_roberta_base_emoji_latest_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp +author: John Snow Labs +name: twitter_roberta_base_emoji_latest_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_emoji_latest_pipeline` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emoji_latest_pipeline_en_5.4.2_3.0_1725195303495.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emoji_latest_pipeline_en_5.4.2_3.0_1725195303495.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("twitter_roberta_base_emoji_latest_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("twitter_roberta_base_emoji_latest_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_roberta_base_emoji_latest_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.6 MB| + +## References + +https://huggingface.co/cardiffnlp/twitter-roberta-base-emoji-latest + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_emoji_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_emoji_pipeline_en.md new file mode 100644 index 00000000000000..f7c7eb2904489e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_emoji_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English twitter_roberta_base_emoji_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp +author: John Snow Labs +name: twitter_roberta_base_emoji_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_emoji_pipeline` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emoji_pipeline_en_5.4.2_3.0_1725194926230.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emoji_pipeline_en_5.4.2_3.0_1725194926230.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("twitter_roberta_base_emoji_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("twitter_roberta_base_emoji_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_roberta_base_emoji_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.2 MB| + +## References + +https://huggingface.co/cardiffnlp/twitter-roberta-base-emoji + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_sep2022_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_sep2022_en.md new file mode 100644 index 00000000000000..d16011e5c7325a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_sep2022_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English twitter_roberta_base_sep2022 RoBertaEmbeddings from cardiffnlp +author: John Snow Labs +name: twitter_roberta_base_sep2022 +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_sep2022` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_sep2022_en_5.4.2_3.0_1725191375557.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_sep2022_en_5.4.2_3.0_1725191375557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("twitter_roberta_base_sep2022","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("twitter_roberta_base_sep2022","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_roberta_base_sep2022| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|466.1 MB| + +## References + +https://huggingface.co/cardiffnlp/twitter-roberta-base-sep2022 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_similarity_latest_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_similarity_latest_en.md new file mode 100644 index 00000000000000..5812b1d5da073b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_similarity_latest_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English twitter_roberta_large_similarity_latest RoBertaForSequenceClassification from cardiffnlp +author: John Snow Labs +name: twitter_roberta_large_similarity_latest +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_large_similarity_latest` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_similarity_latest_en_5.5.0_3.0_1725212297817.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_similarity_latest_en_5.5.0_3.0_1725212297817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_large_similarity_latest","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_large_similarity_latest", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_roberta_large_similarity_latest| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/cardiffnlp/twitter-roberta-large-similarity-latest \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_similarity_latest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_similarity_latest_pipeline_en.md new file mode 100644 index 00000000000000..dcb1a6352fe9f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_similarity_latest_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English twitter_roberta_large_similarity_latest_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp +author: John Snow Labs +name: twitter_roberta_large_similarity_latest_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_large_similarity_latest_pipeline` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_similarity_latest_pipeline_en_5.5.0_3.0_1725212367093.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_similarity_latest_pipeline_en_5.5.0_3.0_1725212367093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("twitter_roberta_large_similarity_latest_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("twitter_roberta_large_similarity_latest_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_roberta_large_similarity_latest_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/cardiffnlp/twitter-roberta-large-similarity-latest + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_topic_latest_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_topic_latest_en.md new file mode 100644 index 00000000000000..2fddf934f8b9de --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_topic_latest_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English twitter_roberta_large_topic_latest RoBertaForSequenceClassification from cardiffnlp +author: John Snow Labs +name: twitter_roberta_large_topic_latest +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_large_topic_latest` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_topic_latest_en_5.5.0_3.0_1725212137090.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_topic_latest_en_5.5.0_3.0_1725212137090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_large_topic_latest","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_large_topic_latest", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_roberta_large_topic_latest| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/cardiffnlp/twitter-roberta-large-topic-latest \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_topic_sentiment_latest_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_topic_sentiment_latest_en.md new file mode 100644 index 00000000000000..203931337c2085 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_topic_sentiment_latest_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English twitter_roberta_large_topic_sentiment_latest RoBertaForSequenceClassification from cardiffnlp +author: John Snow Labs +name: twitter_roberta_large_topic_sentiment_latest +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_large_topic_sentiment_latest` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_topic_sentiment_latest_en_5.4.2_3.0_1725194102990.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_topic_sentiment_latest_en_5.4.2_3.0_1725194102990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_large_topic_sentiment_latest","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_large_topic_sentiment_latest", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_roberta_large_topic_sentiment_latest| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/cardiffnlp/twitter-roberta-large-topic-sentiment-latest \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_topic_sentiment_latest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_topic_sentiment_latest_pipeline_en.md new file mode 100644 index 00000000000000..3c6a6c9cfc0d20 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_topic_sentiment_latest_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English twitter_roberta_large_topic_sentiment_latest_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp +author: John Snow Labs +name: twitter_roberta_large_topic_sentiment_latest_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_large_topic_sentiment_latest_pipeline` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_topic_sentiment_latest_pipeline_en_5.4.2_3.0_1725194176195.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_topic_sentiment_latest_pipeline_en_5.4.2_3.0_1725194176195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("twitter_roberta_large_topic_sentiment_latest_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("twitter_roberta_large_topic_sentiment_latest_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_roberta_large_topic_sentiment_latest_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/cardiffnlp/twitter-roberta-large-topic-sentiment-latest + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_xlm_roberta_crypto_spam_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_xlm_roberta_crypto_spam_en.md new file mode 100644 index 00000000000000..43cf76f6cf3514 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_xlm_roberta_crypto_spam_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English twitter_xlm_roberta_crypto_spam XlmRoBertaForSequenceClassification from svalabs +author: John Snow Labs +name: twitter_xlm_roberta_crypto_spam +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_crypto_spam` is a English model originally trained by svalabs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_crypto_spam_en_5.4.2_3.0_1725188948186.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_crypto_spam_en_5.4.2_3.0_1725188948186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_crypto_spam","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_crypto_spam", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_xlm_roberta_crypto_spam| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/svalabs/twitter-xlm-roberta-crypto-spam \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_xlm_roberta_crypto_spam_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_xlm_roberta_crypto_spam_pipeline_en.md new file mode 100644 index 00000000000000..93093c23474ffb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_xlm_roberta_crypto_spam_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English twitter_xlm_roberta_crypto_spam_pipeline pipeline XlmRoBertaForSequenceClassification from svalabs +author: John Snow Labs +name: twitter_xlm_roberta_crypto_spam_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_crypto_spam_pipeline` is a English model originally trained by svalabs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_crypto_spam_pipeline_en_5.4.2_3.0_1725189001595.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_crypto_spam_pipeline_en_5.4.2_3.0_1725189001595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("twitter_xlm_roberta_crypto_spam_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("twitter_xlm_roberta_crypto_spam_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_xlm_roberta_crypto_spam_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/svalabs/twitter-xlm-roberta-crypto-spam + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-ukrainian_punctcase_pipeline_uk.md b/docs/_posts/ahmedlone127/2024-09-01-ukrainian_punctcase_pipeline_uk.md new file mode 100644 index 00000000000000..78e902c204de61 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-ukrainian_punctcase_pipeline_uk.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Ukrainian ukrainian_punctcase_pipeline pipeline XlmRoBertaForTokenClassification from ukr-models +author: John Snow Labs +name: ukrainian_punctcase_pipeline +date: 2024-09-01 +tags: [uk, open_source, pipeline, onnx] +task: Named Entity Recognition +language: uk +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ukrainian_punctcase_pipeline` is a Ukrainian model originally trained by ukr-models. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ukrainian_punctcase_pipeline_uk_5.4.2_3.0_1725179269115.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ukrainian_punctcase_pipeline_uk_5.4.2_3.0_1725179269115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ukrainian_punctcase_pipeline", lang = "uk") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ukrainian_punctcase_pipeline", lang = "uk") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ukrainian_punctcase_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|uk| +|Size:|396.9 MB| + +## References + +https://huggingface.co/ukr-models/uk-punctcase + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-unified_skill_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-unified_skill_ner_pipeline_en.md new file mode 100644 index 00000000000000..c14ef06cc88343 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-unified_skill_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English unified_skill_ner_pipeline pipeline BertForTokenClassification from ledigajobb +author: John Snow Labs +name: unified_skill_ner_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unified_skill_ner_pipeline` is a English model originally trained by ledigajobb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unified_skill_ner_pipeline_en_5.4.2_3.0_1725163649168.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unified_skill_ner_pipeline_en_5.4.2_3.0_1725163649168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("unified_skill_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("unified_skill_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|unified_skill_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.3 MB| + +## References + +https://huggingface.co/ledigajobb/unified_skill_ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-video_llava_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-video_llava_pipeline_en.md new file mode 100644 index 00000000000000..ff86107616f3c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-video_llava_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English video_llava_pipeline pipeline CLIPForZeroShotClassification from AnasMohamed +author: John Snow Labs +name: video_llava_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`video_llava_pipeline` is a English model originally trained by AnasMohamed. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/video_llava_pipeline_en_5.5.0_3.0_1725226963253.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/video_llava_pipeline_en_5.5.0_3.0_1725226963253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("video_llava_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("video_llava_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|video_llava_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/AnasMohamed/video-llava + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-wangchanberta_thai_qa_th.md b/docs/_posts/ahmedlone127/2024-09-01-wangchanberta_thai_qa_th.md new file mode 100644 index 00000000000000..a1b68046f5bf54 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-wangchanberta_thai_qa_th.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Thai wangchanberta_thai_qa CamemBertForQuestionAnswering from Thanakrit +author: John Snow Labs +name: wangchanberta_thai_qa +date: 2024-09-01 +tags: [th, open_source, onnx, question_answering, camembert] +task: Question Answering +language: th +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wangchanberta_thai_qa` is a Thai model originally trained by Thanakrit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wangchanberta_thai_qa_th_5.4.2_3.0_1725161960689.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wangchanberta_thai_qa_th_5.4.2_3.0_1725161960689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = CamemBertForQuestionAnswering.pretrained("wangchanberta_thai_qa","th") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = CamemBertForQuestionAnswering.pretrained("wangchanberta_thai_qa", "th") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wangchanberta_thai_qa| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|th| +|Size:|392.1 MB| + +## References + +https://huggingface.co/Thanakrit/wangchanberta-th-QA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-wangchanberta_xet_hyp_params_en.md b/docs/_posts/ahmedlone127/2024-09-01-wangchanberta_xet_hyp_params_en.md new file mode 100644 index 00000000000000..bebd86d25d3557 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-wangchanberta_xet_hyp_params_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English wangchanberta_xet_hyp_params CamemBertForQuestionAnswering from powerpuf-bot +author: John Snow Labs +name: wangchanberta_xet_hyp_params +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, camembert] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wangchanberta_xet_hyp_params` is a English model originally trained by powerpuf-bot. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wangchanberta_xet_hyp_params_en_5.4.2_3.0_1725161795749.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wangchanberta_xet_hyp_params_en_5.4.2_3.0_1725161795749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = CamemBertForQuestionAnswering.pretrained("wangchanberta_xet_hyp_params","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = CamemBertForQuestionAnswering.pretrained("wangchanberta_xet_hyp_params", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wangchanberta_xet_hyp_params| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|392.1 MB| + +## References + +https://huggingface.co/powerpuf-bot/wangchanberta-xet_hyp-params \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_ance_warmup_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_ance_warmup_pipeline_en.md new file mode 100644 index 00000000000000..ab40d35a24fdaa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_ance_warmup_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_ance_warmup_pipeline pipeline XlmRoBertaEmbeddings from k-ush +author: John Snow Labs +name: xlm_roberta_base_ance_warmup_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ance_warmup_pipeline` is a English model originally trained by k-ush. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ance_warmup_pipeline_en_5.4.2_3.0_1725177833837.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ance_warmup_pipeline_en_5.4.2_3.0_1725177833837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_ance_warmup_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_ance_warmup_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_ance_warmup_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|830.6 MB| + +## References + +https://huggingface.co/k-ush/xlm-roberta-base-ance-warmup + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_4_pipeline_en.md new file mode 100644 index 00000000000000..67eb609f776885 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_4_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_4_pipeline pipeline XlmRoBertaForQuestionAnswering from jluckyboyj +author: John Snow Labs +name: xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_4_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_4_pipeline` is a English model originally trained by jluckyboyj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_4_pipeline_en_5.4.2_3.0_1725173598592.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_4_pipeline_en_5.4.2_3.0_1725173598592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.0 MB| + +## References + +https://huggingface.co/jluckyboyj/xlm-roberta-base-finetuned-augument-visquad2-15-3-2023-4 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_marc_english_krassy_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_marc_english_krassy_en.md new file mode 100644 index 00000000000000..c51a93dc046c1c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_marc_english_krassy_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_marc_english_krassy XlmRoBertaForSequenceClassification from Krassy +author: John Snow Labs +name: xlm_roberta_base_finetuned_marc_english_krassy +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_marc_english_krassy` is a English model originally trained by Krassy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_krassy_en_5.4.2_3.0_1725189866396.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_krassy_en_5.4.2_3.0_1725189866396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_marc_english_krassy","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_marc_english_krassy", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_marc_english_krassy| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|833.5 MB| + +## References + +https://huggingface.co/Krassy/xlm-roberta-base-finetuned-marc-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_marc_english_pratibha_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_marc_english_pratibha_en.md new file mode 100644 index 00000000000000..dacf3faee95fcc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_marc_english_pratibha_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_marc_english_pratibha XlmRoBertaForSequenceClassification from Pratibha +author: John Snow Labs +name: xlm_roberta_base_finetuned_marc_english_pratibha +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_marc_english_pratibha` is a English model originally trained by Pratibha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_pratibha_en_5.4.2_3.0_1725189385086.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_pratibha_en_5.4.2_3.0_1725189385086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_marc_english_pratibha","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_marc_english_pratibha", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_marc_english_pratibha| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|833.5 MB| + +## References + +https://huggingface.co/Pratibha/xlm-roberta-base-finetuned-marc-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_panx_german_french_iis2009002_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_panx_german_french_iis2009002_en.md new file mode 100644 index 00000000000000..83bedc898d29d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_panx_german_french_iis2009002_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_french_iis2009002 XlmRoBertaForTokenClassification from iis2009002 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_french_iis2009002 +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_iis2009002` is a English model originally trained by iis2009002. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_iis2009002_en_5.4.2_3.0_1725179344243.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_iis2009002_en_5.4.2_3.0_1725179344243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_iis2009002","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_iis2009002", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_french_iis2009002| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|858.2 MB| + +## References + +https://huggingface.co/iis2009002/xlm-roberta-base-finetuned-panx-de-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_panx_german_munsu_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_panx_german_munsu_en.md new file mode 100644 index 00000000000000..51240f3fdae701 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_panx_german_munsu_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_munsu XlmRoBertaForTokenClassification from MunSu +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_munsu +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_munsu` is a English model originally trained by MunSu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_munsu_en_5.4.2_3.0_1725179831280.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_munsu_en_5.4.2_3.0_1725179831280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_munsu","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_munsu", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_munsu| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|858.1 MB| + +## References + +https://huggingface.co/MunSu/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_squad_1_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_squad_1_en.md new file mode 100644 index 00000000000000..cdc37d243d9fb3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_squad_1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_squad_1 XlmRoBertaForQuestionAnswering from keeyansh +author: John Snow Labs +name: xlm_roberta_base_finetuned_squad_1 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_squad_1` is a English model originally trained by keeyansh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_squad_1_en_5.4.2_3.0_1725156378585.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_squad_1_en_5.4.2_3.0_1725156378585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_squad_1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_squad_1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_squad_1| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|812.2 MB| + +## References + +https://huggingface.co/keeyansh/xlm-roberta-base-finetuned-squad-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_squad_warrior1127_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_squad_warrior1127_en.md new file mode 100644 index 00000000000000..054fda6dc38706 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_finetuned_squad_warrior1127_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_squad_warrior1127 XlmRoBertaForQuestionAnswering from warrior1127 +author: John Snow Labs +name: xlm_roberta_base_finetuned_squad_warrior1127 +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_squad_warrior1127` is a English model originally trained by warrior1127. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_squad_warrior1127_en_5.4.2_3.0_1725173042979.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_squad_warrior1127_en_5.4.2_3.0_1725173042979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_squad_warrior1127","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_squad_warrior1127", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_squad_warrior1127| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|872.8 MB| + +## References + +https://huggingface.co/warrior1127/xlm-roberta-base-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_fire_classification_silvanus_xx.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_fire_classification_silvanus_xx.md new file mode 100644 index 00000000000000..ce84d524671f05 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_fire_classification_silvanus_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual xlm_roberta_base_fire_classification_silvanus XlmRoBertaForSequenceClassification from rollerhafeezh-amikom +author: John Snow Labs +name: xlm_roberta_base_fire_classification_silvanus +date: 2024-09-01 +tags: [xx, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_fire_classification_silvanus` is a Multilingual model originally trained by rollerhafeezh-amikom. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_fire_classification_silvanus_xx_5.4.2_3.0_1725188716439.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_fire_classification_silvanus_xx_5.4.2_3.0_1725188716439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_fire_classification_silvanus","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_fire_classification_silvanus", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_fire_classification_silvanus| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|821.3 MB| + +## References + +https://huggingface.co/rollerhafeezh-amikom/xlm-roberta-base-fire-classification-silvanus \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_language_detection_brenomatos_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_language_detection_brenomatos_en.md new file mode 100644 index 00000000000000..6cf1c8f302dd99 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_language_detection_brenomatos_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_language_detection_brenomatos XlmRoBertaForSequenceClassification from brenomatos +author: John Snow Labs +name: xlm_roberta_base_language_detection_brenomatos +date: 2024-09-01 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_language_detection_brenomatos` is a English model originally trained by brenomatos. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_language_detection_brenomatos_en_5.4.2_3.0_1725170020776.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_language_detection_brenomatos_en_5.4.2_3.0_1725170020776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_language_detection_brenomatos","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_language_detection_brenomatos", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_language_detection_brenomatos| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|887.9 MB| + +## References + +https://huggingface.co/brenomatos/xlm-roberta-base-language-detection \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_language_detection_silvanus_xx.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_language_detection_silvanus_xx.md new file mode 100644 index 00000000000000..d7f63177ae23c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_language_detection_silvanus_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual xlm_roberta_base_language_detection_silvanus XlmRoBertaForSequenceClassification from rollerhafeezh-amikom +author: John Snow Labs +name: xlm_roberta_base_language_detection_silvanus +date: 2024-09-01 +tags: [xx, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_language_detection_silvanus` is a Multilingual model originally trained by rollerhafeezh-amikom. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_language_detection_silvanus_xx_5.4.2_3.0_1725190408114.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_language_detection_silvanus_xx_5.4.2_3.0_1725190408114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_language_detection_silvanus","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_language_detection_silvanus", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_language_detection_silvanus| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|882.4 MB| + +## References + +https://huggingface.co/rollerhafeezh-amikom/xlm-roberta-base-language-detection-silvanus \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_multilingual_toxicity_classifier_plus_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_multilingual_toxicity_classifier_plus_pipeline_xx.md new file mode 100644 index 00000000000000..1af3f66c212646 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_multilingual_toxicity_classifier_plus_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual xlm_roberta_base_multilingual_toxicity_classifier_plus_pipeline pipeline XlmRoBertaForSequenceClassification from EIStakovskii +author: John Snow Labs +name: xlm_roberta_base_multilingual_toxicity_classifier_plus_pipeline +date: 2024-09-01 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_multilingual_toxicity_classifier_plus_pipeline` is a Multilingual model originally trained by EIStakovskii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_multilingual_toxicity_classifier_plus_pipeline_xx_5.4.2_3.0_1725189273511.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_multilingual_toxicity_classifier_plus_pipeline_xx_5.4.2_3.0_1725189273511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_multilingual_toxicity_classifier_plus_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_multilingual_toxicity_classifier_plus_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_multilingual_toxicity_classifier_plus_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|836.2 MB| + +## References + +https://huggingface.co/EIStakovskii/xlm_roberta_base_multilingual_toxicity_classifier_plus + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_multilingual_toxicity_classifier_plus_xx.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_multilingual_toxicity_classifier_plus_xx.md new file mode 100644 index 00000000000000..83def4a95aa401 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_multilingual_toxicity_classifier_plus_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual xlm_roberta_base_multilingual_toxicity_classifier_plus XlmRoBertaForSequenceClassification from EIStakovskii +author: John Snow Labs +name: xlm_roberta_base_multilingual_toxicity_classifier_plus +date: 2024-09-01 +tags: [xx, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_multilingual_toxicity_classifier_plus` is a Multilingual model originally trained by EIStakovskii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_multilingual_toxicity_classifier_plus_xx_5.4.2_3.0_1725189158203.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_multilingual_toxicity_classifier_plus_xx_5.4.2_3.0_1725189158203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_multilingual_toxicity_classifier_plus","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_multilingual_toxicity_classifier_plus", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_multilingual_toxicity_classifier_plus| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|836.2 MB| + +## References + +https://huggingface.co/EIStakovskii/xlm_roberta_base_multilingual_toxicity_classifier_plus \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_panx_dataset_english_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_panx_dataset_english_en.md new file mode 100644 index 00000000000000..5e56298f8ba8ce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_panx_dataset_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_panx_dataset_english XlmRoBertaForTokenClassification from tner +author: John Snow Labs +name: xlm_roberta_base_panx_dataset_english +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_panx_dataset_english` is a English model originally trained by tner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_panx_dataset_english_en_5.4.2_3.0_1725179821376.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_panx_dataset_english_en_5.4.2_3.0_1725179821376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_panx_dataset_english","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_panx_dataset_english", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_panx_dataset_english| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|797.4 MB| + +## References + +https://huggingface.co/tner/xlm-roberta-base-panx-dataset-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_qa_norquad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_qa_norquad_pipeline_en.md new file mode 100644 index 00000000000000..7404d0cad7be7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_qa_norquad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_base_qa_norquad_pipeline pipeline XlmRoBertaForQuestionAnswering from eanderson +author: John Snow Labs +name: xlm_roberta_base_qa_norquad_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_qa_norquad_pipeline` is a English model originally trained by eanderson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qa_norquad_pipeline_en_5.4.2_3.0_1725174431671.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qa_norquad_pipeline_en_5.4.2_3.0_1725174431671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_qa_norquad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_qa_norquad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_qa_norquad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|854.5 MB| + +## References + +https://huggingface.co/eanderson/xlm-roberta-base-qa_norquad + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_qa_squad2_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_qa_squad2_en.md new file mode 100644 index 00000000000000..b56f81f23296c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_qa_squad2_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering model (from deepset) +author: John Snow Labs +name: xlm_roberta_base_qa_squad2 +date: 2024-09-01 +tags: [open_source, xlmroberta, question_answering, en, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-squad2` is a English model originally trained by `deepset`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qa_squad2_en_5.5.0_3.0_1725235082867.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qa_squad2_en_5.5.0_3.0_1725235082867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_qa_squad2","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer")\ +.setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, spanClassifier]) + +data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifer = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_qa_squad2","en") +.setInputCols(Array("document", "token")) +.setOutputCol("answer") +.setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) + +val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squadv2.xlm_roberta.base").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_qa_squad2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|874.5 MB| + +## References + +References + +https://huggingface.co/deepset/xlm-roberta-base-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_qa_squad2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_qa_squad2_pipeline_en.md new file mode 100644 index 00000000000000..c48199a62161c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_qa_squad2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_base_qa_squad2_pipeline pipeline XlmRoBertaForQuestionAnswering from deepset +author: John Snow Labs +name: xlm_roberta_base_qa_squad2_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_qa_squad2_pipeline` is a English model originally trained by deepset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qa_squad2_pipeline_en_5.5.0_3.0_1725235156058.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qa_squad2_pipeline_en_5.5.0_3.0_1725235156058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_qa_squad2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_qa_squad2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_qa_squad2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|874.5 MB| + +## References + +https://huggingface.co/deepset/xlm-roberta-base-squad2 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_sanskrit_saskta_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_sanskrit_saskta_spanish_es.md new file mode 100644 index 00000000000000..06ebd714d00fc4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_sanskrit_saskta_spanish_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish xlm_roberta_base_sanskrit_saskta_spanish XlmRoBertaForSequenceClassification from MMG +author: John Snow Labs +name: xlm_roberta_base_sanskrit_saskta_spanish +date: 2024-09-01 +tags: [es, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_sanskrit_saskta_spanish` is a Castilian, Spanish model originally trained by MMG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_sanskrit_saskta_spanish_es_5.4.2_3.0_1725170325969.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_sanskrit_saskta_spanish_es_5.4.2_3.0_1725170325969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_sanskrit_saskta_spanish","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_sanskrit_saskta_spanish", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_sanskrit_saskta_spanish| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|836.0 MB| + +## References + +https://huggingface.co/MMG/xlm-roberta-base-sa-spanish \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_sanskrit_saskta_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_sanskrit_saskta_spanish_pipeline_es.md new file mode 100644 index 00000000000000..bd11fcef61095f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_sanskrit_saskta_spanish_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish xlm_roberta_base_sanskrit_saskta_spanish_pipeline pipeline XlmRoBertaForSequenceClassification from MMG +author: John Snow Labs +name: xlm_roberta_base_sanskrit_saskta_spanish_pipeline +date: 2024-09-01 +tags: [es, open_source, pipeline, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_sanskrit_saskta_spanish_pipeline` is a Castilian, Spanish model originally trained by MMG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_sanskrit_saskta_spanish_pipeline_es_5.4.2_3.0_1725170412823.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_sanskrit_saskta_spanish_pipeline_es_5.4.2_3.0_1725170412823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_sanskrit_saskta_spanish_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_sanskrit_saskta_spanish_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_sanskrit_saskta_spanish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|836.0 MB| + +## References + +https://huggingface.co/MMG/xlm-roberta-base-sa-spanish + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_squad2_pretrained_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_squad2_pretrained_pipeline_en.md new file mode 100644 index 00000000000000..768ef2812a0e67 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_squad2_pretrained_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_base_squad2_pretrained_pipeline pipeline XlmRoBertaForQuestionAnswering from agdatacy +author: John Snow Labs +name: xlm_roberta_base_squad2_pretrained_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_squad2_pretrained_pipeline` is a English model originally trained by agdatacy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad2_pretrained_pipeline_en_5.4.2_3.0_1725173625050.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad2_pretrained_pipeline_en_5.4.2_3.0_1725173625050.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_squad2_pretrained_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_squad2_pretrained_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_squad2_pretrained_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/agdatacy/xlm-roberta-base-squad2-pretrained + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_toxicity_es.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_toxicity_es.md new file mode 100644 index 00000000000000..8413ffcdf39427 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_base_toxicity_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish xlm_roberta_base_toxicity XlmRoBertaForSequenceClassification from jjmcarrascosa +author: John Snow Labs +name: xlm_roberta_base_toxicity +date: 2024-09-01 +tags: [es, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: es +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_toxicity` is a Castilian, Spanish model originally trained by jjmcarrascosa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_toxicity_es_5.4.2_3.0_1725188916975.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_toxicity_es_5.4.2_3.0_1725188916975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_toxicity","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_toxicity", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_toxicity| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|799.2 MB| + +## References + +https://huggingface.co/jjmcarrascosa/xlm-roberta-base-toxicity \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_en.md new file mode 100644 index 00000000000000..f75126a3569274 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from teacookies) +author: John Snow Labs +name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898 +date: 2024-09-01 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-more_fine_tune_24465520-26265898` is a English model originally trained by `teacookies`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_en_5.5.0_3.0_1725234908585.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_en_5.5.0_3.0_1725234908585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.xlm_roberta.fine_tune_24465520_26265898").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|888.2 MB| + +## References + +References + +- https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265898 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_pipeline_en.md new file mode 100644 index 00000000000000..0035eed92bf9f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies +author: John Snow Labs +name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_pipeline` is a English model originally trained by teacookies. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_pipeline_en_5.5.0_3.0_1725234981038.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_pipeline_en_5.5.0_3.0_1725234981038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265898_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|888.2 MB| + +## References + +https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265898 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_en.md new file mode 100644 index 00000000000000..8714b831efc4a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from teacookies) +author: John Snow Labs +name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901 +date: 2024-09-01 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-more_fine_tune_24465520-26265901` is a English model originally trained by `teacookies`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_en_5.5.0_3.0_1725234960462.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_en_5.5.0_3.0_1725234960462.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.xlm_roberta.fine_tune_24465520_26265901").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|888.2 MB| + +## References + +References + +- https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265901 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_pipeline_en.md new file mode 100644 index 00000000000000..ac8877bb1f4cf9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies +author: John Snow Labs +name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_pipeline` is a English model originally trained by teacookies. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_pipeline_en_5.5.0_3.0_1725235032173.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_pipeline_en_5.5.0_3.0_1725235032173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265901_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|888.2 MB| + +## References + +https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265901 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265907_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265907_en.md new file mode 100644 index 00000000000000..57922c53a13314 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265907_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from teacookies) +author: John Snow Labs +name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265907 +date: 2024-09-01 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-more_fine_tune_24465520-26265907` is a English model originally trained by `teacookies`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265907_en_5.4.2_3.0_1725156795450.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265907_en_5.4.2_3.0_1725156795450.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265907","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265907","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.xlm_roberta.fine_tune_24465520_26265907").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265907| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|888.2 MB| + +## References + +References + +- https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265907 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_en.md new file mode 100644 index 00000000000000..3f5b05cade8f79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from teacookies) +author: John Snow Labs +name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465523 +date: 2024-09-01 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-roberta-base-squad2-24465523` is a English model originally trained by `teacookies`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_en_5.5.0_3.0_1725234495659.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_en_5.5.0_3.0_1725234495659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465523","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465523","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squadv2.xlm_roberta.base_24465523.by_teacookies").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465523| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|887.2 MB| + +## References + +References + +- https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465523 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_pipeline_en.md new file mode 100644 index 00000000000000..953873a33e0da7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies +author: John Snow Labs +name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_pipeline` is a English model originally trained by teacookies. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_pipeline_en_5.5.0_3.0_1725234568603.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_pipeline_en_5.5.0_3.0_1725234568603.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465523_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|887.2 MB| + +## References + +https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465523 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_klue_mrc_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_klue_mrc_roberta_base_en.md new file mode 100644 index 00000000000000..83b77a2897ed00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_klue_mrc_roberta_base_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from seongju) +author: John Snow Labs +name: xlm_roberta_qa_klue_mrc_roberta_base +date: 2024-09-01 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `klue-mrc-roberta-base` is a English model originally trained by `seongju`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_klue_mrc_roberta_base_en_5.4.2_3.0_1725156262490.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_klue_mrc_roberta_base_en_5.4.2_3.0_1725156262490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_klue_mrc_roberta_base","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_klue_mrc_roberta_base","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.klue.xlm_roberta.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_klue_mrc_roberta_base| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|854.6 MB| + +## References + +References + +- https://huggingface.co/seongju/klue-mrc-roberta-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlm_3lang_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlm_3lang_en.md new file mode 100644 index 00000000000000..b0a540b54d927f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlm_3lang_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from krinal214) +author: John Snow Labs +name: xlm_roberta_qa_xlm_3lang +date: 2024-09-01 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-3lang` is a English model originally trained by `krinal214`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_3lang_en_5.4.2_3.0_1725157968347.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_3lang_en_5.4.2_3.0_1725157968347.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_3lang","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_xlm_3lang","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.tydiqa.xlm_roberta.3lang").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlm_3lang| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|863.5 MB| + +## References + +References + +- https://huggingface.co/krinal214/xlm-3lang \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlm_roberta_qa_chaii_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlm_roberta_qa_chaii_pipeline_xx.md new file mode 100644 index 00000000000000..d3ee9b09848b64 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlm_roberta_qa_chaii_pipeline_xx.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Multilingual xlm_roberta_qa_xlm_roberta_qa_chaii_pipeline pipeline XlmRoBertaForQuestionAnswering from gokulkarthik +author: John Snow Labs +name: xlm_roberta_qa_xlm_roberta_qa_chaii_pipeline +date: 2024-09-01 +tags: [xx, open_source, pipeline, onnx] +task: Question Answering +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_qa_chaii_pipeline` is a Multilingual model originally trained by gokulkarthik. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_qa_chaii_pipeline_xx_5.5.0_3.0_1725234546260.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_qa_chaii_pipeline_xx_5.5.0_3.0_1725234546260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_qa_chaii_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_qa_chaii_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlm_roberta_qa_chaii_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|885.2 MB| + +## References + +https://huggingface.co/gokulkarthik/xlm-roberta-qa-chaii + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlm_roberta_qa_chaii_xx.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlm_roberta_qa_chaii_xx.md new file mode 100644 index 00000000000000..00ae9ce6885815 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlm_roberta_qa_chaii_xx.md @@ -0,0 +1,106 @@ +--- +layout: model +title: Multilingual XlmRoBertaForQuestionAnswering (from gokulkarthik) +author: John Snow Labs +name: xlm_roberta_qa_xlm_roberta_qa_chaii +date: 2024-09-01 +tags: [en, hi, ta, open_source, question_answering, xlmroberta, xx, onnx] +task: Question Answering +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-qa-chaii` is a multilingual model originally trained by `gokulkarthik`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_qa_chaii_xx_5.5.0_3.0_1725234467003.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_qa_chaii_xx_5.5.0_3.0_1725234467003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_qa_chaii","xx") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_xlm_roberta_qa_chaii","xx") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("xx.answer_question.chaii.xlm_roberta").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlm_roberta_qa_chaii| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|xx| +|Size:|885.2 MB| + +## References + +References + +- https://huggingface.co/gokulkarthik/xlm-roberta-qa-chaii \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_de.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_de.md new file mode 100644 index 00000000000000..4546ce0102c715 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_de.md @@ -0,0 +1,86 @@ +--- +layout: model +title: German xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan XlmRoBertaForQuestionAnswering from saattrupdan +author: John Snow Labs +name: xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan +date: 2024-09-01 +tags: [de, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan` is a German model originally trained by saattrupdan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_de_5.5.0_3.0_1725234824476.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_de_5.5.0_3.0_1725234824476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan","de") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan", "de") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|de| +|Size:|874.2 MB| + +## References + +https://huggingface.co/saattrupdan/xlmr-base-texas-squad-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_pipeline_de.md new file mode 100644 index 00000000000000..938089b58b1011 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_pipeline_de.md @@ -0,0 +1,69 @@ +--- +layout: model +title: German xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_pipeline pipeline XlmRoBertaForQuestionAnswering from saattrupdan +author: John Snow Labs +name: xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_pipeline +date: 2024-09-01 +tags: [de, open_source, pipeline, onnx] +task: Question Answering +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_pipeline` is a German model originally trained by saattrupdan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_pipeline_de_5.5.0_3.0_1725234890830.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_pipeline_de_5.5.0_3.0_1725234890830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlmr_base_texas_squad_german_german_saattrupdan_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|874.2 MB| + +## References + +https://huggingface.co/saattrupdan/xlmr-base-texas-squad-de + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmr_quoref_webis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlmr_quoref_webis_pipeline_en.md new file mode 100644 index 00000000000000..90bf357c013138 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmr_quoref_webis_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlmr_quoref_webis_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm +author: John Snow Labs +name: xlmr_quoref_webis_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_quoref_webis_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_quoref_webis_pipeline_en_5.4.2_3.0_1725174582066.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_quoref_webis_pipeline_en_5.4.2_3.0_1725174582066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmr_quoref_webis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmr_quoref_webis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmr_quoref_webis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|834.2 MB| + +## References + +https://huggingface.co/intanm/xlmr-quoref-webis + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_classifier_base_snli_mnli_anli_xnli_xx.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_classifier_base_snli_mnli_anli_xnli_xx.md new file mode 100644 index 00000000000000..37fd3fe227d718 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_classifier_base_snli_mnli_anli_xnli_xx.md @@ -0,0 +1,108 @@ +--- +layout: model +title: Multilingual XlmRobertaForSequenceClassification Base Cased model (from symanto) +author: John Snow Labs +name: xlmroberta_classifier_base_snli_mnli_anli_xnli +date: 2024-09-01 +tags: [en, de, fr, es, ru, ar, tr, zh, el, th, bg, ur, open_source, xlm_roberta, sequence_classification, classification, xx, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRobertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-snli-mnli-anli-xnli` is a Multilingual model originally trained by `symanto`. + +## Predicted Entities + +`ENTAILMENT`, `NEUTRAL`, `CONTRADICTION` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_classifier_base_snli_mnli_anli_xnli_xx_5.4.2_3.0_1725169264769.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_classifier_base_snli_mnli_anli_xnli_xx_5.4.2_3.0_1725169264769.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = XlmRoBertaForSequenceClassification.pretrained("xlmroberta_classifier_base_snli_mnli_anli_xnli","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = XlmRoBertaForSequenceClassification.pretrained("xlmroberta_classifier_base_snli_mnli_anli_xnli","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("xx.classify.xlmr_roberta.xnli.base").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_classifier_base_snli_mnli_anli_xnli| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|899.7 MB| + +## References + +References + +- https://huggingface.co/symanto/xlm-roberta-base-snli-mnli-anli-xnli +- https://nlp.stanford.edu/projects/snli/ +- https://cims.nyu.edu/~sbowman/multinli/ +- https://github.com/facebookresearch/anli +- https://github.com/facebookresearch/XNLI \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_finetuned_tydiqa_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_finetuned_tydiqa_en.md new file mode 100644 index 00000000000000..2e7c6a2e3a0710 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_finetuned_tydiqa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English xlmroberta_finetuned_tydiqa XlmRoBertaForQuestionAnswering from Auracle7 +author: John Snow Labs +name: xlmroberta_finetuned_tydiqa +date: 2024-09-01 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_finetuned_tydiqa` is a English model originally trained by Auracle7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_finetuned_tydiqa_en_5.4.2_3.0_1725173155718.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_finetuned_tydiqa_en_5.4.2_3.0_1725173155718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlmroberta_finetuned_tydiqa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlmroberta_finetuned_tydiqa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_finetuned_tydiqa| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|848.9 MB| + +## References + +https://huggingface.co/Auracle7/XLMRoberta-finetuned-TyDIQA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_finetuned_tydiqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_finetuned_tydiqa_pipeline_en.md new file mode 100644 index 00000000000000..73392c54580cd6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_finetuned_tydiqa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlmroberta_finetuned_tydiqa_pipeline pipeline XlmRoBertaForQuestionAnswering from Auracle7 +author: John Snow Labs +name: xlmroberta_finetuned_tydiqa_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_finetuned_tydiqa_pipeline` is a English model originally trained by Auracle7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_finetuned_tydiqa_pipeline_en_5.4.2_3.0_1725173229851.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_finetuned_tydiqa_pipeline_en_5.4.2_3.0_1725173229851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_finetuned_tydiqa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_finetuned_tydiqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_finetuned_tydiqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|848.9 MB| + +## References + +https://huggingface.co/Auracle7/XLMRoberta-finetuned-TyDIQA + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_lg.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_lg.md new file mode 100644 index 00000000000000..cc09eedc7bf6dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_lg.md @@ -0,0 +1,120 @@ +--- +layout: model +title: Ganda XLMRobertaForTokenClassification Base Cased model (from mbeukman) +author: John Snow Labs +name: xlmroberta_ner_base_finetuned_luganda_finetuned_luganda +date: 2024-09-01 +tags: [lg, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: lg +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-luganda-finetuned-ner-luganda` is a Ganda model originally trained by `mbeukman`. + +## Predicted Entities + +`ORG`, `LOC`, `PER`, `DATE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_lg_5.4.2_3.0_1725179693292.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_lg_5.4.2_3.0_1725179693292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_luganda_finetuned_luganda","lg") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_luganda_finetuned_luganda","lg") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("lg.ner.xlmr_roberta.base_finetuned_luganda.by_mbeukman").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_finetuned_luganda_finetuned_luganda| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|lg| +|Size:|1.0 GB| + +## References + +References + +- https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-luganda-finetuned-ner-luganda +- https://arxiv.org/abs/2103.11811 +- https://github.com/Michael-Beukman/NERTransfer +- https://www.apache.org/licenses/LICENSE-2.0 +- https://github.com/Michael-Beukman/NERTransfer +- https://github.com/masakhane-io/masakhane-ner +- https://arxiv.org/pdf/2103.11811.pdf +- https://arxiv.org/abs/2103.11811 +- https://arxiv.org/abs/2103.11811 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_pipeline_lg.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_pipeline_lg.md new file mode 100644 index 00000000000000..23ae0a2474e3ea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_pipeline_lg.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Ganda xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_pipeline pipeline XlmRoBertaForTokenClassification from mbeukman +author: John Snow Labs +name: xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_pipeline +date: 2024-09-01 +tags: [lg, open_source, pipeline, onnx] +task: Named Entity Recognition +language: lg +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_pipeline` is a Ganda model originally trained by mbeukman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_pipeline_lg_5.4.2_3.0_1725179748722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_pipeline_lg_5.4.2_3.0_1725179748722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_pipeline", lang = "lg") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_pipeline", lang = "lg") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_finetuned_luganda_finetuned_luganda_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|lg| +|Size:|1.0 GB| + +## References + +https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-luganda-finetuned-ner-luganda + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_base_finetuned_panx_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_base_finetuned_panx_pipeline_xx.md new file mode 100644 index 00000000000000..7e7f61afc84ed6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_base_finetuned_panx_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual xlmroberta_ner_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from moghis +author: John Snow Labs +name: xlmroberta_ner_base_finetuned_panx_pipeline +date: 2024-09-01 +tags: [xx, open_source, pipeline, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_finetuned_panx_pipeline` is a Multilingual model originally trained by moghis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_panx_pipeline_xx_5.4.2_3.0_1725181255745.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_panx_pipeline_xx_5.4.2_3.0_1725181255745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_base_finetuned_panx_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_base_finetuned_panx_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|858.2 MB| + +## References + +https://huggingface.co/moghis/xlm-roberta-base-finetuned-panx-fr-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_base_finetuned_panx_xx.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_base_finetuned_panx_xx.md new file mode 100644 index 00000000000000..81747bb5015cd1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_base_finetuned_panx_xx.md @@ -0,0 +1,112 @@ +--- +layout: model +title: Multilingual XLMRobertaForTokenClassification Base Cased model (from moghis) +author: John Snow Labs +name: xlmroberta_ner_base_finetuned_panx +date: 2024-09-01 +tags: [de, fr, open_source, xlm_roberta, ner, xx, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-fr-de` is a Multilingual model originally trained by `moghis`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_panx_xx_5.4.2_3.0_1725181187052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_panx_xx_5.4.2_3.0_1725181187052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_panx","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_panx","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("xx.ner.xlmr_roberta.base_finetuned.by_moghis").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_finetuned_panx| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|xx| +|Size:|858.2 MB| + +## References + +References + +- https://huggingface.co/moghis/xlm-roberta-base-finetuned-panx-fr-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_be4rr_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_be4rr_base_finetuned_panx_de.md new file mode 100644 index 00000000000000..9f0d442037f647 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_be4rr_base_finetuned_panx_de.md @@ -0,0 +1,113 @@ +--- +layout: model +title: German XLMRobertaForTokenClassification Base Cased model (from be4rr) +author: John Snow Labs +name: xlmroberta_ner_be4rr_base_finetuned_panx +date: 2024-09-01 +tags: [de, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `be4rr`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_be4rr_base_finetuned_panx_de_5.4.2_3.0_1725179799621.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_be4rr_base_finetuned_panx_de_5.4.2_3.0_1725179799621.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_be4rr_base_finetuned_panx","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_be4rr_base_finetuned_panx","de") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_be4rr").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_be4rr_base_finetuned_panx| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|853.8 MB| + +## References + +References + +- https://huggingface.co/be4rr/xlm-roberta-base-finetuned-panx-de +- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_be4rr_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_be4rr_base_finetuned_panx_pipeline_de.md new file mode 100644 index 00000000000000..b4cd6cb95ae5ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_be4rr_base_finetuned_panx_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German xlmroberta_ner_be4rr_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from be4rr +author: John Snow Labs +name: xlmroberta_ner_be4rr_base_finetuned_panx_pipeline +date: 2024-09-01 +tags: [de, open_source, pipeline, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_be4rr_base_finetuned_panx_pipeline` is a German model originally trained by be4rr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_be4rr_base_finetuned_panx_pipeline_de_5.4.2_3.0_1725179871899.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_be4rr_base_finetuned_panx_pipeline_de_5.4.2_3.0_1725179871899.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_be4rr_base_finetuned_panx_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_be4rr_base_finetuned_panx_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_be4rr_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|853.8 MB| + +## References + +https://huggingface.co/be4rr/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_ericklerouge123_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_ericklerouge123_base_finetuned_panx_pipeline_de.md new file mode 100644 index 00000000000000..0a249898a2e37a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_ericklerouge123_base_finetuned_panx_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German xlmroberta_ner_ericklerouge123_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from ericklerouge123 +author: John Snow Labs +name: xlmroberta_ner_ericklerouge123_base_finetuned_panx_pipeline +date: 2024-09-01 +tags: [de, open_source, pipeline, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_ericklerouge123_base_finetuned_panx_pipeline` is a German model originally trained by ericklerouge123. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_ericklerouge123_base_finetuned_panx_pipeline_de_5.4.2_3.0_1725180158632.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_ericklerouge123_base_finetuned_panx_pipeline_de_5.4.2_3.0_1725180158632.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_ericklerouge123_base_finetuned_panx_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_ericklerouge123_base_finetuned_panx_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_ericklerouge123_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|853.8 MB| + +## References + +https://huggingface.co/ericklerouge123/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_haesun_base_finetuned_panx_all_xx.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_haesun_base_finetuned_panx_all_xx.md new file mode 100644 index 00000000000000..b0169a98e38dac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_haesun_base_finetuned_panx_all_xx.md @@ -0,0 +1,112 @@ +--- +layout: model +title: Multilingual XLMRobertaForTokenClassification Base Cased model (from haesun) +author: John Snow Labs +name: xlmroberta_ner_haesun_base_finetuned_panx_all +date: 2024-09-01 +tags: [xx, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-all` is a Multilingual model originally trained by `haesun`. + +## Predicted Entities + +`ORG`, `LOC`, `PER` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_haesun_base_finetuned_panx_all_xx_5.4.2_3.0_1725181117254.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_haesun_base_finetuned_panx_all_xx_5.4.2_3.0_1725181117254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_haesun_base_finetuned_panx_all","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_haesun_base_finetuned_panx_all","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("xx.ner.xlmr_roberta.base_finetuned_panx_all.by_haesun").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_haesun_base_finetuned_panx_all| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|xx| +|Size:|848.0 MB| + +## References + +References + +- https://huggingface.co/haesun/xlm-roberta-base-finetuned-panx-all \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_iis2009002_base_finetuned_panx_all_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_iis2009002_base_finetuned_panx_all_pipeline_xx.md new file mode 100644 index 00000000000000..8ea8772433426b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_iis2009002_base_finetuned_panx_all_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual xlmroberta_ner_iis2009002_base_finetuned_panx_all_pipeline pipeline XlmRoBertaForTokenClassification from iis2009002 +author: John Snow Labs +name: xlmroberta_ner_iis2009002_base_finetuned_panx_all_pipeline +date: 2024-09-01 +tags: [xx, open_source, pipeline, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_iis2009002_base_finetuned_panx_all_pipeline` is a Multilingual model originally trained by iis2009002. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_iis2009002_base_finetuned_panx_all_pipeline_xx_5.4.2_3.0_1725179270271.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_iis2009002_base_finetuned_panx_all_pipeline_xx_5.4.2_3.0_1725179270271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_iis2009002_base_finetuned_panx_all_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_iis2009002_base_finetuned_panx_all_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_iis2009002_base_finetuned_panx_all_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|861.0 MB| + +## References + +https://huggingface.co/iis2009002/xlm-roberta-base-finetuned-panx-all + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_iis2009002_base_finetuned_panx_all_xx.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_iis2009002_base_finetuned_panx_all_xx.md new file mode 100644 index 00000000000000..4cb20520c3cbb3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_iis2009002_base_finetuned_panx_all_xx.md @@ -0,0 +1,112 @@ +--- +layout: model +title: Multilingual XLMRobertaForTokenClassification Base Cased model (from iis2009002) +author: John Snow Labs +name: xlmroberta_ner_iis2009002_base_finetuned_panx_all +date: 2024-09-01 +tags: [xx, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-all` is a Multilingual model originally trained by `iis2009002`. + +## Predicted Entities + +`ORG`, `LOC`, `PER` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_iis2009002_base_finetuned_panx_all_xx_5.4.2_3.0_1725179201067.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_iis2009002_base_finetuned_panx_all_xx_5.4.2_3.0_1725179201067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_iis2009002_base_finetuned_panx_all","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_iis2009002_base_finetuned_panx_all","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("xx.ner.xlmr_roberta.base_finetuned_panx_all.by_iis2009002").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_iis2009002_base_finetuned_panx_all| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|xx| +|Size:|861.0 MB| + +## References + +References + +- https://huggingface.co/iis2009002/xlm-roberta-base-finetuned-panx-all \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_jgriffi_base_finetuned_panx_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_jgriffi_base_finetuned_panx_pipeline_en.md new file mode 100644 index 00000000000000..8ff13aa213b56b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_jgriffi_base_finetuned_panx_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlmroberta_ner_jgriffi_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from jgriffi +author: John Snow Labs +name: xlmroberta_ner_jgriffi_base_finetuned_panx_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_jgriffi_base_finetuned_panx_pipeline` is a English model originally trained by jgriffi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jgriffi_base_finetuned_panx_pipeline_en_5.4.2_3.0_1725179279948.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jgriffi_base_finetuned_panx_pipeline_en_5.4.2_3.0_1725179279948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_jgriffi_base_finetuned_panx_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_jgriffi_base_finetuned_panx_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_jgriffi_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|828.4 MB| + +## References + +https://huggingface.co/jgriffi/xlm-roberta-base-finetuned-panx-en + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_mubikan_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_mubikan_base_finetuned_panx_de.md new file mode 100644 index 00000000000000..4a49411acbebad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_mubikan_base_finetuned_panx_de.md @@ -0,0 +1,113 @@ +--- +layout: model +title: German XLMRobertaForTokenClassification Base Cased model (from mubikan) +author: John Snow Labs +name: xlmroberta_ner_mubikan_base_finetuned_panx +date: 2024-09-01 +tags: [de, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `mubikan`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_mubikan_base_finetuned_panx_de_5.4.2_3.0_1725180565314.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_mubikan_base_finetuned_panx_de_5.4.2_3.0_1725180565314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_mubikan_base_finetuned_panx","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_mubikan_base_finetuned_panx","de") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_mubikan").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_mubikan_base_finetuned_panx| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|853.8 MB| + +## References + +References + +- https://huggingface.co/mubikan/xlm-roberta-base-finetuned-panx-de +- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_mubikan_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_mubikan_base_finetuned_panx_pipeline_de.md new file mode 100644 index 00000000000000..595d8236f6342b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_mubikan_base_finetuned_panx_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German xlmroberta_ner_mubikan_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from mubikan +author: John Snow Labs +name: xlmroberta_ner_mubikan_base_finetuned_panx_pipeline +date: 2024-09-01 +tags: [de, open_source, pipeline, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_mubikan_base_finetuned_panx_pipeline` is a German model originally trained by mubikan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_mubikan_base_finetuned_panx_pipeline_de_5.4.2_3.0_1725180636799.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_mubikan_base_finetuned_panx_pipeline_de_5.4.2_3.0_1725180636799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_mubikan_base_finetuned_panx_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_mubikan_base_finetuned_panx_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_mubikan_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|853.8 MB| + +## References + +https://huggingface.co/mubikan/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_shopee_pipeline_id.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_shopee_pipeline_id.md new file mode 100644 index 00000000000000..59a0ecbc31b581 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_shopee_pipeline_id.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Indonesian xlmroberta_ner_shopee_pipeline pipeline XlmRoBertaForTokenClassification from vkhangpham +author: John Snow Labs +name: xlmroberta_ner_shopee_pipeline +date: 2024-09-01 +tags: [id, open_source, pipeline, onnx] +task: Named Entity Recognition +language: id +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_shopee_pipeline` is a Indonesian model originally trained by vkhangpham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_shopee_pipeline_id_5.4.2_3.0_1725180524459.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_shopee_pipeline_id_5.4.2_3.0_1725180524459.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_shopee_pipeline", lang = "id") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_shopee_pipeline", lang = "id") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_shopee_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|id| +|Size:|864.7 MB| + +## References + +https://huggingface.co/vkhangpham/shopee-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_igbo_ig.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_igbo_ig.md new file mode 100644 index 00000000000000..fa7a7c91f95e00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_igbo_ig.md @@ -0,0 +1,110 @@ +--- +layout: model +title: Igbo Named Entity Recognition (from mbeukman) +author: John Snow Labs +name: xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_igbo +date: 2024-09-01 +tags: [xlm_roberta, ner, token_classification, ig, open_source, onnx] +task: Named Entity Recognition +language: ig +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Named Entity Recognition model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-swahili-finetuned-ner-igbo` is a Igbo model orginally trained by `mbeukman`. + +## Predicted Entities + +`PER`, `ORG`, `LOC`, `DATE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_igbo_ig_5.4.2_3.0_1725180705208.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_igbo_ig_5.4.2_3.0_1725180705208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\ + .setInputCols(["document"])\ + .setOutputCol("sentence") + +tokenizer = Tokenizer() \ + .setInputCols("sentence") \ + .setOutputCol("token") + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_igbo","ig") \ + .setInputCols(["sentence", "token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier]) + +data = spark.createDataFrame([["Ahụrụ m n'anya na-atọ m ụtọ"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val tokenizer = new Tokenizer() + .setInputCols(Array("sentence")) + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_igbo","ig") + .setInputCols(Array("sentence", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier)) + +val data = Seq("Ahụrụ m n'anya na-atọ m ụtọ").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_igbo| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ig| +|Size:|1.0 GB| + +## References + +References + +- https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-swahili-finetuned-ner-igbo +- https://arxiv.org/abs/2103.11811 +- https://github.com/Michael-Beukman/NERTransfer +- https://www.apache.org/licenses/LICENSE-2.0 +- https://github.com/Michael-Beukman/ \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_yaxin_base_conll2003_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_yaxin_base_conll2003_pipeline_en.md new file mode 100644 index 00000000000000..5d4fae71bfcc5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmroberta_ner_yaxin_base_conll2003_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlmroberta_ner_yaxin_base_conll2003_pipeline pipeline XlmRoBertaForTokenClassification from Yaxin +author: John Snow Labs +name: xlmroberta_ner_yaxin_base_conll2003_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_yaxin_base_conll2003_pipeline` is a English model originally trained by Yaxin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_yaxin_base_conll2003_pipeline_en_5.4.2_3.0_1725180427148.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_yaxin_base_conll2003_pipeline_en_5.4.2_3.0_1725180427148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_yaxin_base_conll2003_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_yaxin_base_conll2003_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_yaxin_base_conll2003_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|792.3 MB| + +## References + +https://huggingface.co/Yaxin/xlm-roberta-base-conll2003-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmrobertabaseforxnli_english_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlmrobertabaseforxnli_english_en.md new file mode 100644 index 00000000000000..48f096e27db2df --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmrobertabaseforxnli_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlmrobertabaseforxnli_english XlmRoBertaEmbeddings from ziqingyang +author: John Snow Labs +name: xlmrobertabaseforxnli_english +date: 2024-09-01 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmrobertabaseforxnli_english` is a English model originally trained by ziqingyang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmrobertabaseforxnli_english_en_5.4.2_3.0_1725176785376.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmrobertabaseforxnli_english_en_5.4.2_3.0_1725176785376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("xlmrobertabaseforxnli_english","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("xlmrobertabaseforxnli_english","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmrobertabaseforxnli_english| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|867.2 MB| + +## References + +https://huggingface.co/ziqingyang/XLMRobertaBaseForXNLI-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-xlmrobertabaseforxnli_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-xlmrobertabaseforxnli_english_pipeline_en.md new file mode 100644 index 00000000000000..0eb6741da1bc53 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-xlmrobertabaseforxnli_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlmrobertabaseforxnli_english_pipeline pipeline XlmRoBertaEmbeddings from ziqingyang +author: John Snow Labs +name: xlmrobertabaseforxnli_english_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmrobertabaseforxnli_english_pipeline` is a English model originally trained by ziqingyang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmrobertabaseforxnli_english_pipeline_en_5.4.2_3.0_1725176850436.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmrobertabaseforxnli_english_pipeline_en_5.4.2_3.0_1725176850436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmrobertabaseforxnli_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmrobertabaseforxnli_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmrobertabaseforxnli_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|867.2 MB| + +## References + +https://huggingface.co/ziqingyang/XLMRobertaBaseForXNLI-en + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-your_model_name_en.md b/docs/_posts/ahmedlone127/2024-09-01-your_model_name_en.md new file mode 100644 index 00000000000000..952b1616bced38 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-your_model_name_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English your_model_name DistilBertForTokenClassification from ArshiaKarimian +author: John Snow Labs +name: your_model_name +date: 2024-09-01 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.4.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`your_model_name` is a English model originally trained by ArshiaKarimian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/your_model_name_en_5.4.2_3.0_1725170997744.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/your_model_name_en_5.4.2_3.0_1725170997744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("your_model_name","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("your_model_name", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|your_model_name| +|Compatibility:|Spark NLP 5.4.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/ArshiaKarimian/your-model-name \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-youtube_clip_lora_simcse_en.md b/docs/_posts/ahmedlone127/2024-09-01-youtube_clip_lora_simcse_en.md new file mode 100644 index 00000000000000..adcf16100a7126 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-youtube_clip_lora_simcse_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English youtube_clip_lora_simcse CLIPForZeroShotClassification from Soran +author: John Snow Labs +name: youtube_clip_lora_simcse +date: 2024-09-01 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`youtube_clip_lora_simcse` is a English model originally trained by Soran. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/youtube_clip_lora_simcse_en_5.5.0_3.0_1725226222964.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/youtube_clip_lora_simcse_en_5.5.0_3.0_1725226222964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("youtube_clip_lora_simcse","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("youtube_clip_lora_simcse","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|youtube_clip_lora_simcse| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.7 MB| + +## References + +https://huggingface.co/Soran/youtube_CLIP_LoRA_SimCSE \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-01-youtube_clip_lora_simcse_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-youtube_clip_lora_simcse_pipeline_en.md new file mode 100644 index 00000000000000..c51d82d7646e7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-01-youtube_clip_lora_simcse_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English youtube_clip_lora_simcse_pipeline pipeline CLIPForZeroShotClassification from Soran +author: John Snow Labs +name: youtube_clip_lora_simcse_pipeline +date: 2024-09-01 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`youtube_clip_lora_simcse_pipeline` is a English model originally trained by Soran. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/youtube_clip_lora_simcse_pipeline_en_5.5.0_3.0_1725226321497.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/youtube_clip_lora_simcse_pipeline_en_5.5.0_3.0_1725226321497.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("youtube_clip_lora_simcse_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("youtube_clip_lora_simcse_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|youtube_clip_lora_simcse_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.7 MB| + +## References + +https://huggingface.co/Soran/youtube_CLIP_LoRA_SimCSE + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-14t5_en.md b/docs/_posts/ahmedlone127/2024-09-02-14t5_en.md new file mode 100644 index 00000000000000..c47f08246976fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-14t5_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English 14t5 CLIPForZeroShotClassification from ismot +author: John Snow Labs +name: 14t5 +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`14t5` is a English model originally trained by ismot. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/14t5_en_5.5.0_3.0_1725257625939.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/14t5_en_5.5.0_3.0_1725257625939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("14t5","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("14t5","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|14t5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/ismot/14t5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-14t5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-14t5_pipeline_en.md new file mode 100644 index 00000000000000..e39af98200a166 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-14t5_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English 14t5_pipeline pipeline CLIPForZeroShotClassification from ismot +author: John Snow Labs +name: 14t5_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`14t5_pipeline` is a English model originally trained by ismot. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/14t5_pipeline_en_5.5.0_3.0_1725257895214.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/14t5_pipeline_en_5.5.0_3.0_1725257895214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("14t5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("14t5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|14t5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/ismot/14t5 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_en.md b/docs/_posts/ahmedlone127/2024-09-02-20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_en.md new file mode 100644 index 00000000000000..a82bf0440f9f6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English 20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling XlmRoBertaForQuestionAnswering from intanm +author: John Snow Labs +name: 20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_en_5.5.0_3.0_1725235584571.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_en_5.5.0_3.0_1725235584571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|861.2 MB| + +## References + +https://huggingface.co/intanm/20230429-002-baseline-xlmr-no-qa-ft-clickbait-spoiling \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_pipeline_en.md new file mode 100644 index 00000000000000..23720e83febc3a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English 20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm +author: John Snow Labs +name: 20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_pipeline_en_5.5.0_3.0_1725235658511.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_pipeline_en_5.5.0_3.0_1725235658511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|20230429_002_baseline_xlmr_norwegian_qa_ft_clickbait_spoiling_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|861.2 MB| + +## References + +https://huggingface.co/intanm/20230429-002-baseline-xlmr-no-qa-ft-clickbait-spoiling + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-230322_lxcd_nmt_english_korean_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-230322_lxcd_nmt_english_korean_v2_en.md new file mode 100644 index 00000000000000..e00b0bb6c6f56b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-230322_lxcd_nmt_english_korean_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English 230322_lxcd_nmt_english_korean_v2 MarianTransformer from Kyungill +author: John Snow Labs +name: 230322_lxcd_nmt_english_korean_v2 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`230322_lxcd_nmt_english_korean_v2` is a English model originally trained by Kyungill. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/230322_lxcd_nmt_english_korean_v2_en_5.5.0_3.0_1725305299993.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/230322_lxcd_nmt_english_korean_v2_en_5.5.0_3.0_1725305299993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("230322_lxcd_nmt_english_korean_v2","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("230322_lxcd_nmt_english_korean_v2","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|230322_lxcd_nmt_english_korean_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|540.4 MB| + +## References + +https://huggingface.co/Kyungill/230322-LXCD_NMT_en-ko_v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-230322_lxcd_nmt_english_korean_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-230322_lxcd_nmt_english_korean_v2_pipeline_en.md new file mode 100644 index 00000000000000..b3df437ec481c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-230322_lxcd_nmt_english_korean_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English 230322_lxcd_nmt_english_korean_v2_pipeline pipeline MarianTransformer from Kyungill +author: John Snow Labs +name: 230322_lxcd_nmt_english_korean_v2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`230322_lxcd_nmt_english_korean_v2_pipeline` is a English model originally trained by Kyungill. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/230322_lxcd_nmt_english_korean_v2_pipeline_en_5.5.0_3.0_1725305328366.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/230322_lxcd_nmt_english_korean_v2_pipeline_en_5.5.0_3.0_1725305328366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("230322_lxcd_nmt_english_korean_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("230322_lxcd_nmt_english_korean_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|230322_lxcd_nmt_english_korean_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|540.9 MB| + +## References + +https://huggingface.co/Kyungill/230322-LXCD_NMT_en-ko_v2 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-4_datasets_fake_news_with_balanced_en.md b/docs/_posts/ahmedlone127/2024-09-02-4_datasets_fake_news_with_balanced_en.md new file mode 100644 index 00000000000000..5d21024a7f0661 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-4_datasets_fake_news_with_balanced_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English 4_datasets_fake_news_with_balanced DistilBertForSequenceClassification from littlepinhorse +author: John Snow Labs +name: 4_datasets_fake_news_with_balanced +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`4_datasets_fake_news_with_balanced` is a English model originally trained by littlepinhorse. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/4_datasets_fake_news_with_balanced_en_5.5.0_3.0_1725305860564.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/4_datasets_fake_news_with_balanced_en_5.5.0_3.0_1725305860564.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("4_datasets_fake_news_with_balanced","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("4_datasets_fake_news_with_balanced", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|4_datasets_fake_news_with_balanced| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/littlepinhorse/4_datasets_fake_news_with_balanced \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-635_a2_albert_en.md b/docs/_posts/ahmedlone127/2024-09-02-635_a2_albert_en.md new file mode 100644 index 00000000000000..40f6704b5aa890 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-635_a2_albert_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English 635_a2_albert AlbertForQuestionAnswering from GoatMilk98 +author: John Snow Labs +name: 635_a2_albert +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`635_a2_albert` is a English model originally trained by GoatMilk98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/635_a2_albert_en_5.5.0_3.0_1725309937093.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/635_a2_albert_en_5.5.0_3.0_1725309937093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("635_a2_albert","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("635_a2_albert", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|635_a2_albert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/GoatMilk98/635-a2-albert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-635_a2_albert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-635_a2_albert_pipeline_en.md new file mode 100644 index 00000000000000..3f22e83e1eca28 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-635_a2_albert_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English 635_a2_albert_pipeline pipeline AlbertForQuestionAnswering from GoatMilk98 +author: John Snow Labs +name: 635_a2_albert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`635_a2_albert_pipeline` is a English model originally trained by GoatMilk98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/635_a2_albert_pipeline_en_5.5.0_3.0_1725309939684.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/635_a2_albert_pipeline_en_5.5.0_3.0_1725309939684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("635_a2_albert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("635_a2_albert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|635_a2_albert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/GoatMilk98/635-a2-albert + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-addrthner_en.md b/docs/_posts/ahmedlone127/2024-09-02-addrthner_en.md new file mode 100644 index 00000000000000..c18616d17b350d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-addrthner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English addrthner CamemBertForTokenClassification from F311 +author: John Snow Labs +name: addrthner +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, camembert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`addrthner` is a English model originally trained by F311. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/addrthner_en_5.5.0_3.0_1725266395679.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/addrthner_en_5.5.0_3.0_1725266395679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = CamemBertForTokenClassification.pretrained("addrthner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = CamemBertForTokenClassification.pretrained("addrthner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|addrthner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|392.2 MB| + +## References + +https://huggingface.co/F311/addrthner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-addrthner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-addrthner_pipeline_en.md new file mode 100644 index 00000000000000..5c4252a7c47347 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-addrthner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English addrthner_pipeline pipeline CamemBertForTokenClassification from F311 +author: John Snow Labs +name: addrthner_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`addrthner_pipeline` is a English model originally trained by F311. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/addrthner_pipeline_en_5.5.0_3.0_1725266416394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/addrthner_pipeline_en_5.5.0_3.0_1725266416394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("addrthner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("addrthner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|addrthner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|392.2 MB| + +## References + +https://huggingface.co/F311/addrthner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-adlhw1qa_roberta_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-adlhw1qa_roberta_large_pipeline_en.md new file mode 100644 index 00000000000000..7e99d37e1944cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-adlhw1qa_roberta_large_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English adlhw1qa_roberta_large_pipeline pipeline BertForQuestionAnswering from wanling1212 +author: John Snow Labs +name: adlhw1qa_roberta_large_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adlhw1qa_roberta_large_pipeline` is a English model originally trained by wanling1212. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adlhw1qa_roberta_large_pipeline_en_5.5.0_3.0_1725312505478.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adlhw1qa_roberta_large_pipeline_en_5.5.0_3.0_1725312505478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("adlhw1qa_roberta_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("adlhw1qa_roberta_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|adlhw1qa_roberta_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/wanling1212/ADLHW1QA_roberta_large + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-adversarial_paraphrasing_detector_en.md b/docs/_posts/ahmedlone127/2024-09-02-adversarial_paraphrasing_detector_en.md new file mode 100644 index 00000000000000..afb72ce25b3d7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-adversarial_paraphrasing_detector_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English adversarial_paraphrasing_detector RoBertaForSequenceClassification from AMHR +author: John Snow Labs +name: adversarial_paraphrasing_detector +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adversarial_paraphrasing_detector` is a English model originally trained by AMHR. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adversarial_paraphrasing_detector_en_5.5.0_3.0_1725238296202.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adversarial_paraphrasing_detector_en_5.5.0_3.0_1725238296202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("adversarial_paraphrasing_detector","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("adversarial_paraphrasing_detector", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|adversarial_paraphrasing_detector| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/AMHR/adversarial-paraphrasing-detector \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-adversarial_paraphrasing_detector_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-adversarial_paraphrasing_detector_pipeline_en.md new file mode 100644 index 00000000000000..1a752ed66aa5f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-adversarial_paraphrasing_detector_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English adversarial_paraphrasing_detector_pipeline pipeline RoBertaForSequenceClassification from AMHR +author: John Snow Labs +name: adversarial_paraphrasing_detector_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adversarial_paraphrasing_detector_pipeline` is a English model originally trained by AMHR. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adversarial_paraphrasing_detector_pipeline_en_5.5.0_3.0_1725238373128.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adversarial_paraphrasing_detector_pipeline_en_5.5.0_3.0_1725238373128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("adversarial_paraphrasing_detector_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("adversarial_paraphrasing_detector_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|adversarial_paraphrasing_detector_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/AMHR/adversarial-paraphrasing-detector + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-afro_xlmr_mini_finetuned_kintweetsb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-afro_xlmr_mini_finetuned_kintweetsb_pipeline_en.md new file mode 100644 index 00000000000000..f17543a096eda6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-afro_xlmr_mini_finetuned_kintweetsb_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English afro_xlmr_mini_finetuned_kintweetsb_pipeline pipeline XlmRoBertaEmbeddings from RogerB +author: John Snow Labs +name: afro_xlmr_mini_finetuned_kintweetsb_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_mini_finetuned_kintweetsb_pipeline` is a English model originally trained by RogerB. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afro_xlmr_mini_finetuned_kintweetsb_pipeline_en_5.5.0_3.0_1725271697550.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_mini_finetuned_kintweetsb_pipeline_en_5.5.0_3.0_1725271697550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("afro_xlmr_mini_finetuned_kintweetsb_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("afro_xlmr_mini_finetuned_kintweetsb_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|afro_xlmr_mini_finetuned_kintweetsb_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|443.1 MB| + +## References + +https://huggingface.co/RogerB/afro-xlmr-mini-finetuned-kintweetsB + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_arabic_ar.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_arabic_ar.md new file mode 100644 index 00000000000000..fca821a50ec7f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_arabic_ar.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Arabic albert_base_arabic AlbertEmbeddings from asafaya +author: John Snow Labs +name: albert_base_arabic +date: 2024-09-02 +tags: [ar, open_source, onnx, embeddings, albert] +task: Embeddings +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_arabic` is a Arabic model originally trained by asafaya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_arabic_ar_5.5.0_3.0_1725306773103.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_arabic_ar_5.5.0_3.0_1725306773103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = AlbertEmbeddings.pretrained("albert_base_arabic","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = AlbertEmbeddings.pretrained("albert_base_arabic","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_arabic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[albert]| +|Language:|ar| +|Size:|42.0 MB| + +## References + +https://huggingface.co/asafaya/albert-base-arabic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_arabic_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_arabic_pipeline_ar.md new file mode 100644 index 00000000000000..95980d7b8f89d8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_arabic_pipeline_ar.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Arabic albert_base_arabic_pipeline pipeline AlbertEmbeddings from asafaya +author: John Snow Labs +name: albert_base_arabic_pipeline +date: 2024-09-02 +tags: [ar, open_source, pipeline, onnx] +task: Embeddings +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_arabic_pipeline` is a Arabic model originally trained by asafaya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_arabic_pipeline_ar_5.5.0_3.0_1725306775483.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_arabic_pipeline_ar_5.5.0_3.0_1725306775483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_arabic_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_arabic_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_arabic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|42.0 MB| + +## References + +https://huggingface.co/asafaya/albert-base-arabic + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_1_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_1_en.md new file mode 100644 index 00000000000000..2216dab6830b6d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_base_qa_1 AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_1 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_1` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_1_en_5.5.0_3.0_1725236736298.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_1_en_5.5.0_3.0_1725236736298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_1_pipeline_en.md new file mode 100644 index 00000000000000..c15c003914b128 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_1_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_1_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_1_pipeline_en_5.5.0_3.0_1725236738681.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_1_pipeline_en_5.5.0_3.0_1725236738681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-1 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_2_lr_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_2_lr_1_pipeline_en.md new file mode 100644 index 00000000000000..10742f8633162c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_2_lr_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_2_lr_1_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_2_lr_1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2_lr_1_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_lr_1_pipeline_en_5.5.0_3.0_1725309660009.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_lr_1_pipeline_en_5.5.0_3.0_1725309660009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_2_lr_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_2_lr_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_2_lr_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-2-lr-1 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_2_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_2_en.md new file mode 100644 index 00000000000000..451399b92173ee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_base_qa_coqa_2_k_fold_2 AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_coqa_2_k_fold_2 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_coqa_2_k_fold_2` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_2_en_5.5.0_3.0_1725310000011.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_2_en_5.5.0_3.0_1725310000011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_2_k_fold_2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_2_k_fold_2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_coqa_2_k_fold_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-coQA-2-k-fold-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_3_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_3_en.md new file mode 100644 index 00000000000000..645b2f3a0357ba --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_3_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_base_qa_coqa_2_k_fold_3 AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_coqa_2_k_fold_3 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_coqa_2_k_fold_3` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_3_en_5.5.0_3.0_1725310209649.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_3_en_5.5.0_3.0_1725310209649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_2_k_fold_3","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_2_k_fold_3", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_coqa_2_k_fold_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-coQA-2-k-fold-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_3_pipeline_en.md new file mode 100644 index 00000000000000..9a0c13d4faace4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_coqa_2_k_fold_3_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_coqa_2_k_fold_3_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_coqa_2_k_fold_3_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_3_pipeline_en_5.5.0_3.0_1725310211913.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_3_pipeline_en_5.5.0_3.0_1725310211913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_coqa_2_k_fold_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_coqa_2_k_fold_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_coqa_2_k_fold_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-coQA-2-k-fold-3 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_4_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_4_en.md new file mode 100644 index 00000000000000..9101288ed96156 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_4_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_base_qa_coqa_2_k_fold_4 AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_coqa_2_k_fold_4 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_coqa_2_k_fold_4` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_4_en_5.5.0_3.0_1725237139672.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_4_en_5.5.0_3.0_1725237139672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_2_k_fold_4","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_2_k_fold_4", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_coqa_2_k_fold_4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-coQA-2-k-fold-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_4_pipeline_en.md new file mode 100644 index 00000000000000..3af6c1fcd30f72 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_k_fold_4_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_coqa_2_k_fold_4_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_coqa_2_k_fold_4_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_coqa_2_k_fold_4_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_4_pipeline_en_5.5.0_3.0_1725237142027.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_4_pipeline_en_5.5.0_3.0_1725237142027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_coqa_2_k_fold_4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_coqa_2_k_fold_4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_coqa_2_k_fold_4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-coQA-2-k-fold-4 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_lr1_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_lr1_en.md new file mode 100644 index 00000000000000..8138861258336d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_lr1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_base_qa_coqa_2_lr1 AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_coqa_2_lr1 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_coqa_2_lr1` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_lr1_en_5.5.0_3.0_1725237068671.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_lr1_en_5.5.0_3.0_1725237068671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_2_lr1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_2_lr1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_coqa_2_lr1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-coQA-2-lr1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_lr1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_lr1_pipeline_en.md new file mode 100644 index 00000000000000..7f23281b8fbf79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_2_lr1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_coqa_2_lr1_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_coqa_2_lr1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_coqa_2_lr1_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_lr1_pipeline_en_5.5.0_3.0_1725237070979.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_lr1_pipeline_en_5.5.0_3.0_1725237070979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_coqa_2_lr1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_coqa_2_lr1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_coqa_2_lr1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-coQA-2-lr1 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_3_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_3_en.md new file mode 100644 index 00000000000000..4002317dcd138e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_3_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_base_qa_coqa_3 AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_coqa_3 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_coqa_3` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_3_en_5.5.0_3.0_1725236619611.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_3_en_5.5.0_3.0_1725236619611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_3","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_3", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_coqa_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-coQA-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_3_pipeline_en.md new file mode 100644 index 00000000000000..a0d7f7cd0698cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_coqa_3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_coqa_3_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_coqa_3_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_coqa_3_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_3_pipeline_en_5.5.0_3.0_1725236622074.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_3_pipeline_en_5.5.0_3.0_1725236622074.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_coqa_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_coqa_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_coqa_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-coQA-3 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_v2_finetuned_squad_parsas_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_v2_finetuned_squad_parsas_en.md new file mode 100644 index 00000000000000..2c7afa99917fd9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_v2_finetuned_squad_parsas_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_base_v2_finetuned_squad_parsas AlbertForQuestionAnswering from ParsaS +author: John Snow Labs +name: albert_base_v2_finetuned_squad_parsas +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_finetuned_squad_parsas` is a English model originally trained by ParsaS. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_finetuned_squad_parsas_en_5.5.0_3.0_1725309655985.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_finetuned_squad_parsas_en_5.5.0_3.0_1725309655985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_v2_finetuned_squad_parsas","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_v2_finetuned_squad_parsas", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_v2_finetuned_squad_parsas| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|483.0 KB| + +## References + +https://huggingface.co/ParsaS/albert-base-v2-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_v2_finetuned_squad_parsas_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_v2_finetuned_squad_parsas_pipeline_en.md new file mode 100644 index 00000000000000..b9cf60547a606e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_v2_finetuned_squad_parsas_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_v2_finetuned_squad_parsas_pipeline pipeline AlbertForQuestionAnswering from ParsaS +author: John Snow Labs +name: albert_base_v2_finetuned_squad_parsas_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_finetuned_squad_parsas_pipeline` is a English model originally trained by ParsaS. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_finetuned_squad_parsas_pipeline_en_5.5.0_3.0_1725309656613.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_finetuned_squad_parsas_pipeline_en_5.5.0_3.0_1725309656613.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_v2_finetuned_squad_parsas_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_v2_finetuned_squad_parsas_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_v2_finetuned_squad_parsas_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|486.5 KB| + +## References + +https://huggingface.co/ParsaS/albert-base-v2-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_v2_finetuned_squad_v2_hadsag_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_v2_finetuned_squad_v2_hadsag_en.md new file mode 100644 index 00000000000000..b242d479b137d8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_v2_finetuned_squad_v2_hadsag_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_base_v2_finetuned_squad_v2_hadsag AlbertForQuestionAnswering from hadsag +author: John Snow Labs +name: albert_base_v2_finetuned_squad_v2_hadsag +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_finetuned_squad_v2_hadsag` is a English model originally trained by hadsag. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_finetuned_squad_v2_hadsag_en_5.5.0_3.0_1725237091320.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_finetuned_squad_v2_hadsag_en_5.5.0_3.0_1725237091320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_v2_finetuned_squad_v2_hadsag","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_v2_finetuned_squad_v2_hadsag", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_v2_finetuned_squad_v2_hadsag| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|53.9 MB| + +## References + +https://huggingface.co/hadsag/albert-base-v2-finetuned-squad-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_v2_finetuned_squad_v2_hadsag_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_v2_finetuned_squad_v2_hadsag_pipeline_en.md new file mode 100644 index 00000000000000..aa9edf727a906e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_v2_finetuned_squad_v2_hadsag_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_v2_finetuned_squad_v2_hadsag_pipeline pipeline AlbertForQuestionAnswering from hadsag +author: John Snow Labs +name: albert_base_v2_finetuned_squad_v2_hadsag_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_finetuned_squad_v2_hadsag_pipeline` is a English model originally trained by hadsag. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_finetuned_squad_v2_hadsag_pipeline_en_5.5.0_3.0_1725237094533.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_finetuned_squad_v2_hadsag_pipeline_en_5.5.0_3.0_1725237094533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_v2_finetuned_squad_v2_hadsag_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_v2_finetuned_squad_v2_hadsag_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_v2_finetuned_squad_v2_hadsag_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|53.9 MB| + +## References + +https://huggingface.co/hadsag/albert-base-v2-finetuned-squad-v2 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_italian_jobrecommendation_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_italian_jobrecommendation_en.md new file mode 100644 index 00000000000000..eebbae430d3104 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_italian_jobrecommendation_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English albert_italian_jobrecommendation AlbertForSequenceClassification from Apizhai +author: John Snow Labs +name: albert_italian_jobrecommendation +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_italian_jobrecommendation` is a English model originally trained by Apizhai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_italian_jobrecommendation_en_5.5.0_3.0_1725301409191.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_italian_jobrecommendation_en_5.5.0_3.0_1725301409191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_italian_jobrecommendation","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_italian_jobrecommendation", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_italian_jobrecommendation| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|44.3 MB| + +## References + +https://huggingface.co/Apizhai/Albert-IT-JobRecommendation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_italian_jobrecommendation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_italian_jobrecommendation_pipeline_en.md new file mode 100644 index 00000000000000..65d327a31f7d15 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_italian_jobrecommendation_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English albert_italian_jobrecommendation_pipeline pipeline AlbertForSequenceClassification from Apizhai +author: John Snow Labs +name: albert_italian_jobrecommendation_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_italian_jobrecommendation_pipeline` is a English model originally trained by Apizhai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_italian_jobrecommendation_pipeline_en_5.5.0_3.0_1725301411633.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_italian_jobrecommendation_pipeline_en_5.5.0_3.0_1725301411633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_italian_jobrecommendation_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_italian_jobrecommendation_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_italian_jobrecommendation_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.3 MB| + +## References + +https://huggingface.co/Apizhai/Albert-IT-JobRecommendation + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_fa.md b/docs/_posts/ahmedlone127/2024-09-02-albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_fa.md new file mode 100644 index 00000000000000..609d4fe97de6d0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_fa.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Persian albert_persian_farsi_base_v2_sentiment_deepsentipers_binary AlbertForSequenceClassification from m3hrdadfi +author: John Snow Labs +name: albert_persian_farsi_base_v2_sentiment_deepsentipers_binary +date: 2024-09-02 +tags: [fa, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: fa +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_persian_farsi_base_v2_sentiment_deepsentipers_binary` is a Persian model originally trained by m3hrdadfi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_fa_5.5.0_3.0_1725279145877.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_fa_5.5.0_3.0_1725279145877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_persian_farsi_base_v2_sentiment_deepsentipers_binary","fa") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_persian_farsi_base_v2_sentiment_deepsentipers_binary", "fa") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_persian_farsi_base_v2_sentiment_deepsentipers_binary| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|fa| +|Size:|68.5 MB| + +## References + +https://huggingface.co/m3hrdadfi/albert-fa-base-v2-sentiment-deepsentipers-binary \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_persian_poetry_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-09-02-albert_persian_poetry_pipeline_fa.md new file mode 100644 index 00000000000000..1c33cc595b4dbc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_persian_poetry_pipeline_fa.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Persian albert_persian_poetry_pipeline pipeline AlbertEmbeddings from mitra-mir +author: John Snow Labs +name: albert_persian_poetry_pipeline +date: 2024-09-02 +tags: [fa, open_source, pipeline, onnx] +task: Embeddings +language: fa +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_persian_poetry_pipeline` is a Persian model originally trained by mitra-mir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_persian_poetry_pipeline_fa_5.5.0_3.0_1725306635075.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_persian_poetry_pipeline_fa_5.5.0_3.0_1725306635075.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_persian_poetry_pipeline", lang = "fa") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_persian_poetry_pipeline", lang = "fa") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_persian_poetry_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fa| +|Size:|41.9 MB| + +## References + +https://huggingface.co/mitra-mir/ALBERT-Persian-Poetry + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_turkish_qa_turkish_squad_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-02-albert_turkish_qa_turkish_squad_pipeline_tr.md new file mode 100644 index 00000000000000..94e2b23163ab50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_turkish_qa_turkish_squad_pipeline_tr.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Turkish albert_turkish_qa_turkish_squad_pipeline pipeline AlbertForQuestionAnswering from anilguven +author: John Snow Labs +name: albert_turkish_qa_turkish_squad_pipeline +date: 2024-09-02 +tags: [tr, open_source, pipeline, onnx] +task: Question Answering +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_turkish_qa_turkish_squad_pipeline` is a Turkish model originally trained by anilguven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_turkish_qa_turkish_squad_pipeline_tr_5.5.0_3.0_1725310053736.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_turkish_qa_turkish_squad_pipeline_tr_5.5.0_3.0_1725310053736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_turkish_qa_turkish_squad_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_turkish_qa_turkish_squad_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_turkish_qa_turkish_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|42.9 MB| + +## References + +https://huggingface.co/anilguven/albert_tr_qa_turkish_squad + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_turkish_turkish_product_reviews_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-02-albert_turkish_turkish_product_reviews_pipeline_tr.md new file mode 100644 index 00000000000000..e6b7fe33d3661d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_turkish_turkish_product_reviews_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish albert_turkish_turkish_product_reviews_pipeline pipeline AlbertForSequenceClassification from anilguven +author: John Snow Labs +name: albert_turkish_turkish_product_reviews_pipeline +date: 2024-09-02 +tags: [tr, open_source, pipeline, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_turkish_turkish_product_reviews_pipeline` is a Turkish model originally trained by anilguven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_turkish_turkish_product_reviews_pipeline_tr_5.5.0_3.0_1725279929766.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_turkish_turkish_product_reviews_pipeline_tr_5.5.0_3.0_1725279929766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_turkish_turkish_product_reviews_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_turkish_turkish_product_reviews_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_turkish_turkish_product_reviews_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|45.1 MB| + +## References + +https://huggingface.co/anilguven/albert_tr_turkish_product_reviews + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_turkish_turkish_product_reviews_tr.md b/docs/_posts/ahmedlone127/2024-09-02-albert_turkish_turkish_product_reviews_tr.md new file mode 100644 index 00000000000000..46dae1019a6c40 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_turkish_turkish_product_reviews_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish albert_turkish_turkish_product_reviews AlbertForSequenceClassification from anilguven +author: John Snow Labs +name: albert_turkish_turkish_product_reviews +date: 2024-09-02 +tags: [tr, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_turkish_turkish_product_reviews` is a Turkish model originally trained by anilguven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_turkish_turkish_product_reviews_tr_5.5.0_3.0_1725279927234.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_turkish_turkish_product_reviews_tr_5.5.0_3.0_1725279927234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_turkish_turkish_product_reviews","tr") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_turkish_turkish_product_reviews", "tr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_turkish_turkish_product_reviews| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|45.1 MB| + +## References + +https://huggingface.co/anilguven/albert_tr_turkish_product_reviews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_xlarge_v2_finetuned_squad_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_xlarge_v2_finetuned_squad_v2_en.md new file mode 100644 index 00000000000000..fed8d92199fc9b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_xlarge_v2_finetuned_squad_v2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_xlarge_v2_finetuned_squad_v2 AlbertForQuestionAnswering from hadsag +author: John Snow Labs +name: albert_xlarge_v2_finetuned_squad_v2 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_xlarge_v2_finetuned_squad_v2` is a English model originally trained by hadsag. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_xlarge_v2_finetuned_squad_v2_en_5.5.0_3.0_1725236971375.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_xlarge_v2_finetuned_squad_v2_en_5.5.0_3.0_1725236971375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_xlarge_v2_finetuned_squad_v2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_xlarge_v2_finetuned_squad_v2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_xlarge_v2_finetuned_squad_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|204.8 MB| + +## References + +https://huggingface.co/hadsag/albert-xlarge-v2-finetuned-squad-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_xlarge_v2_finetuned_squad_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_xlarge_v2_finetuned_squad_v2_pipeline_en.md new file mode 100644 index 00000000000000..233dd14d44ae4a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-albert_xlarge_v2_finetuned_squad_v2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_xlarge_v2_finetuned_squad_v2_pipeline pipeline AlbertForQuestionAnswering from hadsag +author: John Snow Labs +name: albert_xlarge_v2_finetuned_squad_v2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_xlarge_v2_finetuned_squad_v2_pipeline` is a English model originally trained by hadsag. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_xlarge_v2_finetuned_squad_v2_pipeline_en_5.5.0_3.0_1725236982145.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_xlarge_v2_finetuned_squad_v2_pipeline_en_5.5.0_3.0_1725236982145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_xlarge_v2_finetuned_squad_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_xlarge_v2_finetuned_squad_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_xlarge_v2_finetuned_squad_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|204.8 MB| + +## References + +https://huggingface.co/hadsag/albert-xlarge-v2-finetuned-squad-v2 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_128_20_mnsr_en.md b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_128_20_mnsr_en.md new file mode 100644 index 00000000000000..825816ae48a4f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_128_20_mnsr_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English all_mpnet_base_128_20_mnsr MPNetEmbeddings from ronanki +author: John Snow Labs +name: all_mpnet_base_128_20_mnsr +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_128_20_mnsr` is a English model originally trained by ronanki. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_128_20_mnsr_en_5.5.0_3.0_1725314218081.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_128_20_mnsr_en_5.5.0_3.0_1725314218081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_128_20_mnsr","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_128_20_mnsr","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_128_20_mnsr| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/ronanki/all_mpnet_base_128_20_MNSR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_en.md b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_en.md new file mode 100644 index 00000000000000..fab2b2adceb99e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3 MPNetEmbeddings from luiz-and-robert-thesis +author: John Snow Labs +name: all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3` is a English model originally trained by luiz-and-robert-thesis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_en_5.5.0_3.0_1725313778603.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_en_5.5.0_3.0_1725313778603.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/luiz-and-robert-thesis/all-mpnet-base-newtriplets-v2-lr-1e-8-m-1-e-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_pipeline_en.md new file mode 100644 index 00000000000000..86a3c33d36c3a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_pipeline pipeline MPNetEmbeddings from luiz-and-robert-thesis +author: John Snow Labs +name: all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_pipeline` is a English model originally trained by luiz-and-robert-thesis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_pipeline_en_5.5.0_3.0_1725313801043.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_pipeline_en_5.5.0_3.0_1725313801043.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_newtriplets_v2_lr_1e_8_m_1_e_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/luiz-and-robert-thesis/all-mpnet-base-newtriplets-v2-lr-1e-8-m-1-e-3 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_fine_tuned_5_textbook_grobid_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_fine_tuned_5_textbook_grobid_pipeline_en.md new file mode 100644 index 00000000000000..674fabdf873594 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_fine_tuned_5_textbook_grobid_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English all_mpnet_base_v2_fine_tuned_5_textbook_grobid_pipeline pipeline MPNetEmbeddings from AhmetAytar +author: John Snow Labs +name: all_mpnet_base_v2_fine_tuned_5_textbook_grobid_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_fine_tuned_5_textbook_grobid_pipeline` is a English model originally trained by AhmetAytar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_5_textbook_grobid_pipeline_en_5.5.0_3.0_1725281031006.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_5_textbook_grobid_pipeline_en_5.5.0_3.0_1725281031006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("all_mpnet_base_v2_fine_tuned_5_textbook_grobid_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("all_mpnet_base_v2_fine_tuned_5_textbook_grobid_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_fine_tuned_5_textbook_grobid_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|935.1 KB| + +## References + +https://huggingface.co/AhmetAytar/all-mpnet-base-v2-fine-tuned_5_textbook_grobid + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_negation_en.md b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_negation_en.md new file mode 100644 index 00000000000000..bd25958f47696a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_negation_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English all_mpnet_base_v2_negation MPNetEmbeddings from dmlls +author: John Snow Labs +name: all_mpnet_base_v2_negation +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_negation` is a English model originally trained by dmlls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_negation_en_5.5.0_3.0_1725280360977.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_negation_en_5.5.0_3.0_1725280360977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_negation","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_negation","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_negation| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/dmlls/all-mpnet-base-v2-negation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_negation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_negation_pipeline_en.md new file mode 100644 index 00000000000000..6e68a3f22b3276 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_negation_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English all_mpnet_base_v2_negation_pipeline pipeline MPNetEmbeddings from dmlls +author: John Snow Labs +name: all_mpnet_base_v2_negation_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_negation_pipeline` is a English model originally trained by dmlls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_negation_pipeline_en_5.5.0_3.0_1725280391836.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_negation_pipeline_en_5.5.0_3.0_1725280391836.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("all_mpnet_base_v2_negation_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("all_mpnet_base_v2_negation_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_negation_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/dmlls/all-mpnet-base-v2-negation + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_sts_romaniox_en.md b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_sts_romaniox_en.md new file mode 100644 index 00000000000000..eccf0039291dac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_sts_romaniox_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English all_mpnet_base_v2_sts_romaniox MPNetEmbeddings from Romaniox +author: John Snow Labs +name: all_mpnet_base_v2_sts_romaniox +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_sts_romaniox` is a English model originally trained by Romaniox. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_sts_romaniox_en_5.5.0_3.0_1725280556202.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_sts_romaniox_en_5.5.0_3.0_1725280556202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_sts_romaniox","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_sts_romaniox","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_sts_romaniox| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/Romaniox/all-mpnet-base-v2-sts \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_tasky_classification_en.md b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_tasky_classification_en.md new file mode 100644 index 00000000000000..98dd420595a6cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_tasky_classification_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English all_mpnet_base_v2_tasky_classification MPNetEmbeddings from khalidalt +author: John Snow Labs +name: all_mpnet_base_v2_tasky_classification +date: 2024-09-02 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_tasky_classification` is a English model originally trained by khalidalt. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_tasky_classification_en_5.5.0_3.0_1725255517036.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_tasky_classification_en_5.5.0_3.0_1725255517036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2_tasky_classification","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2_tasky_classification", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_tasky_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +References + +https://huggingface.co/khalidalt/all-mpnet-base-v2-tasky-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_tasky_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_tasky_classification_pipeline_en.md new file mode 100644 index 00000000000000..891af781ac9a6a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_tasky_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English all_mpnet_base_v2_tasky_classification_pipeline pipeline MPNetForSequenceClassification from khalidalt +author: John Snow Labs +name: all_mpnet_base_v2_tasky_classification_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_tasky_classification_pipeline` is a English model originally trained by khalidalt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_tasky_classification_pipeline_en_5.5.0_3.0_1725255538734.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_tasky_classification_pipeline_en_5.5.0_3.0_1725255538734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("all_mpnet_base_v2_tasky_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("all_mpnet_base_v2_tasky_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_tasky_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/khalidalt/all-mpnet-base-v2-tasky-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-answer_equivalence_distilroberta_en.md b/docs/_posts/ahmedlone127/2024-09-02-answer_equivalence_distilroberta_en.md new file mode 100644 index 00000000000000..a42c5871c080b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-answer_equivalence_distilroberta_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English answer_equivalence_distilroberta RoBertaForSequenceClassification from zli12321 +author: John Snow Labs +name: answer_equivalence_distilroberta +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`answer_equivalence_distilroberta` is a English model originally trained by zli12321. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/answer_equivalence_distilroberta_en_5.5.0_3.0_1725277394317.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/answer_equivalence_distilroberta_en_5.5.0_3.0_1725277394317.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("answer_equivalence_distilroberta","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("answer_equivalence_distilroberta", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|answer_equivalence_distilroberta| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|308.7 MB| + +## References + +https://huggingface.co/zli12321/answer_equivalence_distilroberta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-answer_equivalence_distilroberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-answer_equivalence_distilroberta_pipeline_en.md new file mode 100644 index 00000000000000..13233f684f9365 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-answer_equivalence_distilroberta_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English answer_equivalence_distilroberta_pipeline pipeline RoBertaForSequenceClassification from zli12321 +author: John Snow Labs +name: answer_equivalence_distilroberta_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`answer_equivalence_distilroberta_pipeline` is a English model originally trained by zli12321. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/answer_equivalence_distilroberta_pipeline_en_5.5.0_3.0_1725277411218.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/answer_equivalence_distilroberta_pipeline_en_5.5.0_3.0_1725277411218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("answer_equivalence_distilroberta_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("answer_equivalence_distilroberta_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|answer_equivalence_distilroberta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|308.7 MB| + +## References + +https://huggingface.co/zli12321/answer_equivalence_distilroberta + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-answer_equivalence_roberta_zongxia_en.md b/docs/_posts/ahmedlone127/2024-09-02-answer_equivalence_roberta_zongxia_en.md new file mode 100644 index 00000000000000..e3d98797f938ce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-answer_equivalence_roberta_zongxia_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English answer_equivalence_roberta_zongxia RoBertaForSequenceClassification from Zongxia +author: John Snow Labs +name: answer_equivalence_roberta_zongxia +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`answer_equivalence_roberta_zongxia` is a English model originally trained by Zongxia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/answer_equivalence_roberta_zongxia_en_5.5.0_3.0_1725277073112.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/answer_equivalence_roberta_zongxia_en_5.5.0_3.0_1725277073112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("answer_equivalence_roberta_zongxia","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("answer_equivalence_roberta_zongxia", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|answer_equivalence_roberta_zongxia| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|443.6 MB| + +## References + +https://huggingface.co/Zongxia/answer_equivalence_roberta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-answer_equivalence_roberta_zongxia_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-answer_equivalence_roberta_zongxia_pipeline_en.md new file mode 100644 index 00000000000000..7dce7f9646de27 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-answer_equivalence_roberta_zongxia_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English answer_equivalence_roberta_zongxia_pipeline pipeline RoBertaForSequenceClassification from Zongxia +author: John Snow Labs +name: answer_equivalence_roberta_zongxia_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`answer_equivalence_roberta_zongxia_pipeline` is a English model originally trained by Zongxia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/answer_equivalence_roberta_zongxia_pipeline_en_5.5.0_3.0_1725277104880.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/answer_equivalence_roberta_zongxia_pipeline_en_5.5.0_3.0_1725277104880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("answer_equivalence_roberta_zongxia_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("answer_equivalence_roberta_zongxia_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|answer_equivalence_roberta_zongxia_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|443.6 MB| + +## References + +https://huggingface.co/Zongxia/answer_equivalence_roberta + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-arabictranslator_en.md b/docs/_posts/ahmedlone127/2024-09-02-arabictranslator_en.md new file mode 100644 index 00000000000000..4c967827adaac8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-arabictranslator_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English arabictranslator MarianTransformer from PontifexMaximus +author: John Snow Labs +name: arabictranslator +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabictranslator` is a English model originally trained by PontifexMaximus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabictranslator_en_5.5.0_3.0_1725242774544.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabictranslator_en_5.5.0_3.0_1725242774544.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("arabictranslator","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("arabictranslator","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabictranslator| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|527.9 MB| + +## References + +https://huggingface.co/PontifexMaximus/ArabicTranslator \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-arabictranslator_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-arabictranslator_pipeline_en.md new file mode 100644 index 00000000000000..7c4d279a2f22a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-arabictranslator_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English arabictranslator_pipeline pipeline MarianTransformer from PontifexMaximus +author: John Snow Labs +name: arabictranslator_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabictranslator_pipeline` is a English model originally trained by PontifexMaximus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabictranslator_pipeline_en_5.5.0_3.0_1725242802454.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabictranslator_pipeline_en_5.5.0_3.0_1725242802454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("arabictranslator_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("arabictranslator_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabictranslator_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|528.5 MB| + +## References + +https://huggingface.co/PontifexMaximus/ArabicTranslator + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ascle_english_spanish_ufal_marianmt_en.md b/docs/_posts/ahmedlone127/2024-09-02-ascle_english_spanish_ufal_marianmt_en.md new file mode 100644 index 00000000000000..2dfc4e5172c7cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ascle_english_spanish_ufal_marianmt_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ascle_english_spanish_ufal_marianmt MarianTransformer from li-lab +author: John Snow Labs +name: ascle_english_spanish_ufal_marianmt +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ascle_english_spanish_ufal_marianmt` is a English model originally trained by li-lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ascle_english_spanish_ufal_marianmt_en_5.5.0_3.0_1725295319148.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ascle_english_spanish_ufal_marianmt_en_5.5.0_3.0_1725295319148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("ascle_english_spanish_ufal_marianmt","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("ascle_english_spanish_ufal_marianmt","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ascle_english_spanish_ufal_marianmt| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|539.7 MB| + +## References + +https://huggingface.co/li-lab/ascle-en-es-UFAL-MarianMT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-autotrain_i7gko_heakm_en.md b/docs/_posts/ahmedlone127/2024-09-02-autotrain_i7gko_heakm_en.md new file mode 100644 index 00000000000000..2d768873bfb913 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-autotrain_i7gko_heakm_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English autotrain_i7gko_heakm MPNetForSequenceClassification from BloodJackson +author: John Snow Labs +name: autotrain_i7gko_heakm +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, mpnet] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_i7gko_heakm` is a English model originally trained by BloodJackson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_i7gko_heakm_en_5.5.0_3.0_1725255694147.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_i7gko_heakm_en_5.5.0_3.0_1725255694147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = MPNetForSequenceClassification.pretrained("autotrain_i7gko_heakm","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = MPNetForSequenceClassification.pretrained("autotrain_i7gko_heakm", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_i7gko_heakm| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.9 MB| + +## References + +https://huggingface.co/BloodJackson/autotrain-i7gko-heakm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-autotrain_i7gko_heakm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-autotrain_i7gko_heakm_pipeline_en.md new file mode 100644 index 00000000000000..c35a349f779b49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-autotrain_i7gko_heakm_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English autotrain_i7gko_heakm_pipeline pipeline MPNetForSequenceClassification from BloodJackson +author: John Snow Labs +name: autotrain_i7gko_heakm_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_i7gko_heakm_pipeline` is a English model originally trained by BloodJackson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_i7gko_heakm_pipeline_en_5.5.0_3.0_1725255716249.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_i7gko_heakm_pipeline_en_5.5.0_3.0_1725255716249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_i7gko_heakm_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_i7gko_heakm_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_i7gko_heakm_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.9 MB| + +## References + +https://huggingface.co/BloodJackson/autotrain-i7gko-heakm + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-autotrain_nrfmc_2jyt8_en.md b/docs/_posts/ahmedlone127/2024-09-02-autotrain_nrfmc_2jyt8_en.md new file mode 100644 index 00000000000000..d8b0541bb6450e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-autotrain_nrfmc_2jyt8_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English autotrain_nrfmc_2jyt8 MPNetEmbeddings from bhawanahettiarachchi +author: John Snow Labs +name: autotrain_nrfmc_2jyt8 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_nrfmc_2jyt8` is a English model originally trained by bhawanahettiarachchi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_nrfmc_2jyt8_en_5.5.0_3.0_1725258269040.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_nrfmc_2jyt8_en_5.5.0_3.0_1725258269040.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("autotrain_nrfmc_2jyt8","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("autotrain_nrfmc_2jyt8","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_nrfmc_2jyt8| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/bhawanahettiarachchi/autotrain-nrfmc-2jyt8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-autotrain_nrfmc_2jyt8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-autotrain_nrfmc_2jyt8_pipeline_en.md new file mode 100644 index 00000000000000..c0ac16f26f4a07 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-autotrain_nrfmc_2jyt8_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English autotrain_nrfmc_2jyt8_pipeline pipeline MPNetEmbeddings from bhawanahettiarachchi +author: John Snow Labs +name: autotrain_nrfmc_2jyt8_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_nrfmc_2jyt8_pipeline` is a English model originally trained by bhawanahettiarachchi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_nrfmc_2jyt8_pipeline_en_5.5.0_3.0_1725258290753.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_nrfmc_2jyt8_pipeline_en_5.5.0_3.0_1725258290753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_nrfmc_2jyt8_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_nrfmc_2jyt8_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_nrfmc_2jyt8_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/bhawanahettiarachchi/autotrain-nrfmc-2jyt8 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-autotrain_swot_deberta_small_3265691117_en.md b/docs/_posts/ahmedlone127/2024-09-02-autotrain_swot_deberta_small_3265691117_en.md new file mode 100644 index 00000000000000..c2eb93de9c7655 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-autotrain_swot_deberta_small_3265691117_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English autotrain_swot_deberta_small_3265691117 DeBertaForQuestionAnswering from chau +author: John Snow Labs +name: autotrain_swot_deberta_small_3265691117 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_swot_deberta_small_3265691117` is a English model originally trained by chau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_swot_deberta_small_3265691117_en_5.5.0_3.0_1725290967989.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_swot_deberta_small_3265691117_en_5.5.0_3.0_1725290967989.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("autotrain_swot_deberta_small_3265691117","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("autotrain_swot_deberta_small_3265691117", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_swot_deberta_small_3265691117| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/chau/autotrain-swot-deberta-small-3265691117 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-autotrain_swot_deberta_small_3265691117_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-autotrain_swot_deberta_small_3265691117_pipeline_en.md new file mode 100644 index 00000000000000..e0c74c498e8ab4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-autotrain_swot_deberta_small_3265691117_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English autotrain_swot_deberta_small_3265691117_pipeline pipeline DeBertaForQuestionAnswering from chau +author: John Snow Labs +name: autotrain_swot_deberta_small_3265691117_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_swot_deberta_small_3265691117_pipeline` is a English model originally trained by chau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_swot_deberta_small_3265691117_pipeline_en_5.5.0_3.0_1725291064907.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_swot_deberta_small_3265691117_pipeline_en_5.5.0_3.0_1725291064907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_swot_deberta_small_3265691117_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_swot_deberta_small_3265691117_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_swot_deberta_small_3265691117_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/chau/autotrain-swot-deberta-small-3265691117 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-autotrain_swot_debertal_large_25_3269791252_en.md b/docs/_posts/ahmedlone127/2024-09-02-autotrain_swot_debertal_large_25_3269791252_en.md new file mode 100644 index 00000000000000..108640b0805060 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-autotrain_swot_debertal_large_25_3269791252_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English autotrain_swot_debertal_large_25_3269791252 DeBertaForQuestionAnswering from chau +author: John Snow Labs +name: autotrain_swot_debertal_large_25_3269791252 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_swot_debertal_large_25_3269791252` is a English model originally trained by chau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_swot_debertal_large_25_3269791252_en_5.5.0_3.0_1725269157811.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_swot_debertal_large_25_3269791252_en_5.5.0_3.0_1725269157811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("autotrain_swot_debertal_large_25_3269791252","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("autotrain_swot_debertal_large_25_3269791252", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_swot_debertal_large_25_3269791252| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/chau/autotrain-swot-debertal-large-25-3269791252 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-autotrain_swot_debertal_large_25_3269791252_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-autotrain_swot_debertal_large_25_3269791252_pipeline_en.md new file mode 100644 index 00000000000000..159d2b7d66315c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-autotrain_swot_debertal_large_25_3269791252_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English autotrain_swot_debertal_large_25_3269791252_pipeline pipeline DeBertaForQuestionAnswering from chau +author: John Snow Labs +name: autotrain_swot_debertal_large_25_3269791252_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_swot_debertal_large_25_3269791252_pipeline` is a English model originally trained by chau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_swot_debertal_large_25_3269791252_pipeline_en_5.5.0_3.0_1725269258776.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_swot_debertal_large_25_3269791252_pipeline_en_5.5.0_3.0_1725269258776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_swot_debertal_large_25_3269791252_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_swot_debertal_large_25_3269791252_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_swot_debertal_large_25_3269791252_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/chau/autotrain-swot-debertal-large-25-3269791252 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-02-babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_en.md new file mode 100644 index 00000000000000..67fb5ac79f84f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad RoBertaForQuestionAnswering from lielbin +author: John Snow Labs +name: babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad` is a English model originally trained by lielbin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_en_5.5.0_3.0_1725251695428.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_en_5.5.0_3.0_1725251695428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|31.9 MB| + +## References + +https://huggingface.co/lielbin/BabyBERTa-aochildes_1.25M_aochildes-french1.25M-without-Masking-seed3-finetuned-SQuAD \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_pipeline_en.md new file mode 100644 index 00000000000000..53d2da579d8160 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_pipeline pipeline RoBertaForQuestionAnswering from lielbin +author: John Snow Labs +name: babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_pipeline` is a English model originally trained by lielbin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_pipeline_en_5.5.0_3.0_1725251697346.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_pipeline_en_5.5.0_3.0_1725251697346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|babyberta_aochildes_1_25m_aochildes_french1_25m_without_masking_seed3_finetuned_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|31.9 MB| + +## References + +https://huggingface.co/lielbin/BabyBERTa-aochildes_1.25M_aochildes-french1.25M-without-Masking-seed3-finetuned-SQuAD + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-balu94distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-02-balu94distilbert_en.md new file mode 100644 index 00000000000000..625a768c863833 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-balu94distilbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English balu94distilbert DistilBertForTokenClassification from Balu94pratap +author: John Snow Labs +name: balu94distilbert +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`balu94distilbert` is a English model originally trained by Balu94pratap. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/balu94distilbert_en_5.5.0_3.0_1725268037693.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/balu94distilbert_en_5.5.0_3.0_1725268037693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("balu94distilbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("balu94distilbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|balu94distilbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|243.3 MB| + +## References + +https://huggingface.co/Balu94pratap/balu94distilbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-balu94distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-balu94distilbert_pipeline_en.md new file mode 100644 index 00000000000000..8f2a805d31901c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-balu94distilbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English balu94distilbert_pipeline pipeline DistilBertForTokenClassification from Balu94pratap +author: John Snow Labs +name: balu94distilbert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`balu94distilbert_pipeline` is a English model originally trained by Balu94pratap. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/balu94distilbert_pipeline_en_5.5.0_3.0_1725268051879.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/balu94distilbert_pipeline_en_5.5.0_3.0_1725268051879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("balu94distilbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("balu94distilbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|balu94distilbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.3 MB| + +## References + +https://huggingface.co/Balu94pratap/balu94distilbert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-baseroberta_finetuned_squadcovid_en.md b/docs/_posts/ahmedlone127/2024-09-02-baseroberta_finetuned_squadcovid_en.md new file mode 100644 index 00000000000000..2c5e0cc20050c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-baseroberta_finetuned_squadcovid_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English baseroberta_finetuned_squadcovid RoBertaForQuestionAnswering from Rahul13 +author: John Snow Labs +name: baseroberta_finetuned_squadcovid +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baseroberta_finetuned_squadcovid` is a English model originally trained by Rahul13. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baseroberta_finetuned_squadcovid_en_5.5.0_3.0_1725252667328.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baseroberta_finetuned_squadcovid_en_5.5.0_3.0_1725252667328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("baseroberta_finetuned_squadcovid","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("baseroberta_finetuned_squadcovid", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|baseroberta_finetuned_squadcovid| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|462.6 MB| + +## References + +https://huggingface.co/Rahul13/baseroberta-finetuned_squadcovid \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-baseroberta_finetuned_squadcovid_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-baseroberta_finetuned_squadcovid_pipeline_en.md new file mode 100644 index 00000000000000..4ee06f9b398251 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-baseroberta_finetuned_squadcovid_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English baseroberta_finetuned_squadcovid_pipeline pipeline RoBertaForQuestionAnswering from Rahul13 +author: John Snow Labs +name: baseroberta_finetuned_squadcovid_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baseroberta_finetuned_squadcovid_pipeline` is a English model originally trained by Rahul13. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baseroberta_finetuned_squadcovid_pipeline_en_5.5.0_3.0_1725252692552.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baseroberta_finetuned_squadcovid_pipeline_en_5.5.0_3.0_1725252692552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("baseroberta_finetuned_squadcovid_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("baseroberta_finetuned_squadcovid_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|baseroberta_finetuned_squadcovid_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|462.6 MB| + +## References + +https://huggingface.co/Rahul13/baseroberta-finetuned_squadcovid + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_base_bulgarian_bg.md b/docs/_posts/ahmedlone127/2024-09-02-bert_base_bulgarian_bg.md new file mode 100644 index 00000000000000..5f343419ef2bdc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_base_bulgarian_bg.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Bulgarian bert_base_bulgarian BertEmbeddings from rmihaylov +author: John Snow Labs +name: bert_base_bulgarian +date: 2024-09-02 +tags: [bg, open_source, onnx, embeddings, bert] +task: Embeddings +language: bg +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_bulgarian` is a Bulgarian model originally trained by rmihaylov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_bulgarian_bg_5.5.0_3.0_1725315237751.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_bulgarian_bg_5.5.0_3.0_1725315237751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = BertEmbeddings.pretrained("bert_base_bulgarian","bg") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("bert_base_bulgarian","bg") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_bulgarian| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|bg| +|Size:|665.0 MB| + +## References + +https://huggingface.co/rmihaylov/bert-base-bg \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_base_bulgarian_pipeline_bg.md b/docs/_posts/ahmedlone127/2024-09-02-bert_base_bulgarian_pipeline_bg.md new file mode 100644 index 00000000000000..db780f558b7151 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_base_bulgarian_pipeline_bg.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Bulgarian bert_base_bulgarian_pipeline pipeline BertEmbeddings from rmihaylov +author: John Snow Labs +name: bert_base_bulgarian_pipeline +date: 2024-09-02 +tags: [bg, open_source, pipeline, onnx] +task: Embeddings +language: bg +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_bulgarian_pipeline` is a Bulgarian model originally trained by rmihaylov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_bulgarian_pipeline_bg_5.5.0_3.0_1725315271575.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_bulgarian_pipeline_bg_5.5.0_3.0_1725315271575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_bulgarian_pipeline", lang = "bg") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_bulgarian_pipeline", lang = "bg") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_bulgarian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|bg| +|Size:|665.0 MB| + +## References + +https://huggingface.co/rmihaylov/bert-base-bg + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_base_multilingual_uncased_google_bert_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-bert_base_multilingual_uncased_google_bert_pipeline_xx.md new file mode 100644 index 00000000000000..bad7bd1ca1ad85 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_base_multilingual_uncased_google_bert_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_google_bert_pipeline pipeline BertEmbeddings from google-bert +author: John Snow Labs +name: bert_base_multilingual_uncased_google_bert_pipeline +date: 2024-09-02 +tags: [xx, open_source, pipeline, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_uncased_google_bert_pipeline` is a Multilingual model originally trained by google-bert. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_google_bert_pipeline_xx_5.5.0_3.0_1725314810695.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_google_bert_pipeline_xx_5.5.0_3.0_1725314810695.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_uncased_google_bert_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_uncased_google_bert_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_google_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|625.5 MB| + +## References + +https://huggingface.co/google-bert/bert-base-multilingual-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_base_multilingual_uncased_google_bert_xx.md b/docs/_posts/ahmedlone127/2024-09-02-bert_base_multilingual_uncased_google_bert_xx.md new file mode 100644 index 00000000000000..30de8933f71206 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_base_multilingual_uncased_google_bert_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_google_bert BertEmbeddings from google-bert +author: John Snow Labs +name: bert_base_multilingual_uncased_google_bert +date: 2024-09-02 +tags: [xx, open_source, onnx, embeddings, bert] +task: Embeddings +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_uncased_google_bert` is a Multilingual model originally trained by google-bert. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_google_bert_xx_5.5.0_3.0_1725314779012.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_google_bert_xx_5.5.0_3.0_1725314779012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = BertEmbeddings.pretrained("bert_base_multilingual_uncased_google_bert","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("bert_base_multilingual_uncased_google_bert","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_google_bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|xx| +|Size:|625.5 MB| + +## References + +https://huggingface.co/google-bert/bert-base-multilingual-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_base_uncased_google_bert_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_base_uncased_google_bert_en.md new file mode 100644 index 00000000000000..13484b3a7cb020 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_base_uncased_google_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_google_bert BertEmbeddings from google-bert +author: John Snow Labs +name: bert_base_uncased_google_bert +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_google_bert` is a English model originally trained by google-bert. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_google_bert_en_5.5.0_3.0_1725315523101.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_google_bert_en_5.5.0_3.0_1725315523101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = BertEmbeddings.pretrained("bert_base_uncased_google_bert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("bert_base_uncased_google_bert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_google_bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/google-bert/bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_base_uncased_google_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_base_uncased_google_bert_pipeline_en.md new file mode 100644 index 00000000000000..8208f7dee4c352 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_base_uncased_google_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_google_bert_pipeline pipeline BertEmbeddings from google-bert +author: John Snow Labs +name: bert_base_uncased_google_bert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_google_bert_pipeline` is a English model originally trained by google-bert. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_google_bert_pipeline_en_5.5.0_3.0_1725315543332.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_google_bert_pipeline_en_5.5.0_3.0_1725315543332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_google_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_google_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_google_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/google-bert/bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_autonlp_imdb_sentiment_analysis_623817873_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_autonlp_imdb_sentiment_analysis_623817873_en.md new file mode 100644 index 00000000000000..9305d61cd8ac04 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_autonlp_imdb_sentiment_analysis_623817873_en.md @@ -0,0 +1,104 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from chiragme) +author: John Snow Labs +name: bert_classifier_autonlp_imdb_sentiment_analysis_623817873 +date: 2024-09-02 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-imdb-sentiment-analysis-623817873` is a English model originally trained by `chiragme`. + +## Predicted Entities + +`neg`, `pos` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_imdb_sentiment_analysis_623817873_en_5.5.0_3.0_1725293652267.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_imdb_sentiment_analysis_623817873_en_5.5.0_3.0_1725293652267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_autonlp_imdb_sentiment_analysis_623817873","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_autonlp_imdb_sentiment_analysis_623817873","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.imdb_sentiment.").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_autonlp_imdb_sentiment_analysis_623817873| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.2 GB| + +## References + +References + +- https://huggingface.co/chiragme/autonlp-imdb-sentiment-analysis-623817873 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_autonlp_imdb_sentiment_analysis_623817873_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_autonlp_imdb_sentiment_analysis_623817873_pipeline_en.md new file mode 100644 index 00000000000000..7650c46c5be35b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_autonlp_imdb_sentiment_analysis_623817873_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classifier_autonlp_imdb_sentiment_analysis_623817873_pipeline pipeline BertForSequenceClassification from chiragme +author: John Snow Labs +name: bert_classifier_autonlp_imdb_sentiment_analysis_623817873_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_autonlp_imdb_sentiment_analysis_623817873_pipeline` is a English model originally trained by chiragme. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_imdb_sentiment_analysis_623817873_pipeline_en_5.5.0_3.0_1725293715704.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_imdb_sentiment_analysis_623817873_pipeline_en_5.5.0_3.0_1725293715704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_autonlp_imdb_sentiment_analysis_623817873_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_autonlp_imdb_sentiment_analysis_623817873_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_autonlp_imdb_sentiment_analysis_623817873_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/chiragme/autonlp-imdb-sentiment-analysis-623817873 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_autotrain_gluemodels_1010733562_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_autotrain_gluemodels_1010733562_en.md new file mode 100644 index 00000000000000..7d5e786eb63224 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_autotrain_gluemodels_1010733562_en.md @@ -0,0 +1,104 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from deepesh0x) +author: John Snow Labs +name: bert_classifier_autotrain_gluemodels_1010733562 +date: 2024-09-02 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autotrain-GlueModels-1010733562` is a English model originally trained by `deepesh0x`. + +## Predicted Entities + +`negative`, `positive` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_autotrain_gluemodels_1010733562_en_5.5.0_3.0_1725294066338.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_autotrain_gluemodels_1010733562_en_5.5.0_3.0_1725294066338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_autotrain_gluemodels_1010733562","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_autotrain_gluemodels_1010733562","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.glue.").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_autotrain_gluemodels_1010733562| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +References + +- https://huggingface.co/deepesh0x/autotrain-GlueModels-1010733562 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_autotrain_gluemodels_1010733562_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_autotrain_gluemodels_1010733562_pipeline_en.md new file mode 100644 index 00000000000000..f5dde2598083f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_autotrain_gluemodels_1010733562_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classifier_autotrain_gluemodels_1010733562_pipeline pipeline BertForSequenceClassification from deepesh0x +author: John Snow Labs +name: bert_classifier_autotrain_gluemodels_1010733562_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_autotrain_gluemodels_1010733562_pipeline` is a English model originally trained by deepesh0x. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_autotrain_gluemodels_1010733562_pipeline_en_5.5.0_3.0_1725294086886.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_autotrain_gluemodels_1010733562_pipeline_en_5.5.0_3.0_1725294086886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_autotrain_gluemodels_1010733562_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_autotrain_gluemodels_1010733562_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_autotrain_gluemodels_1010733562_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/deepesh0x/autotrain-GlueModels-1010733562 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_bert_base_english_hindi_codemix_cased_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_bert_base_english_hindi_codemix_cased_pipeline_xx.md new file mode 100644 index 00000000000000..09d1063c3a25bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_bert_base_english_hindi_codemix_cased_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_classifier_bert_base_english_hindi_codemix_cased_pipeline pipeline BertForSequenceClassification from rohanrajpal +author: John Snow Labs +name: bert_classifier_bert_base_english_hindi_codemix_cased_pipeline +date: 2024-09-02 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_bert_base_english_hindi_codemix_cased_pipeline` is a Multilingual model originally trained by rohanrajpal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_english_hindi_codemix_cased_pipeline_xx_5.5.0_3.0_1725293581207.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_english_hindi_codemix_cased_pipeline_xx_5.5.0_3.0_1725293581207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_bert_base_english_hindi_codemix_cased_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_bert_base_english_hindi_codemix_cased_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_bert_base_english_hindi_codemix_cased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/rohanrajpal/bert-base-en-hi-codemix-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_bert_base_english_hindi_codemix_cased_xx.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_bert_base_english_hindi_codemix_cased_xx.md new file mode 100644 index 00000000000000..038e89f393293e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_bert_base_english_hindi_codemix_cased_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_classifier_bert_base_english_hindi_codemix_cased BertForSequenceClassification from rohanrajpal +author: John Snow Labs +name: bert_classifier_bert_base_english_hindi_codemix_cased +date: 2024-09-02 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_bert_base_english_hindi_codemix_cased` is a Multilingual model originally trained by rohanrajpal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_english_hindi_codemix_cased_xx_5.5.0_3.0_1725293546555.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_english_hindi_codemix_cased_xx_5.5.0_3.0_1725293546555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_english_hindi_codemix_cased","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_english_hindi_codemix_cased", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_bert_base_english_hindi_codemix_cased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/rohanrajpal/bert-base-en-hi-codemix-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_klue_tc_base_multilingual_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_klue_tc_base_multilingual_cased_pipeline_en.md new file mode 100644 index 00000000000000..d68f63bd632ec5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_klue_tc_base_multilingual_cased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classifier_klue_tc_base_multilingual_cased_pipeline pipeline BertForSequenceClassification from seongju +author: John Snow Labs +name: bert_classifier_klue_tc_base_multilingual_cased_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_klue_tc_base_multilingual_cased_pipeline` is a English model originally trained by seongju. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_klue_tc_base_multilingual_cased_pipeline_en_5.5.0_3.0_1725293625814.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_klue_tc_base_multilingual_cased_pipeline_en_5.5.0_3.0_1725293625814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_klue_tc_base_multilingual_cased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_klue_tc_base_multilingual_cased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_klue_tc_base_multilingual_cased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/seongju/klue-tc-bert-base-multilingual-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_norwegian_bokml_base_target_group_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_norwegian_bokml_base_target_group_en.md new file mode 100644 index 00000000000000..49e2754e200369 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_norwegian_bokml_base_target_group_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_classifier_norwegian_bokml_base_target_group BertForSequenceClassification from thusken +author: John Snow Labs +name: bert_classifier_norwegian_bokml_base_target_group +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_norwegian_bokml_base_target_group` is a English model originally trained by thusken. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_norwegian_bokml_base_target_group_en_5.5.0_3.0_1725293449434.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_norwegian_bokml_base_target_group_en_5.5.0_3.0_1725293449434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_norwegian_bokml_base_target_group","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_norwegian_bokml_base_target_group", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_norwegian_bokml_base_target_group| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|668.4 MB| + +## References + +https://huggingface.co/thusken/nb-bert-base-target-group \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_norwegian_bokml_base_target_group_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_norwegian_bokml_base_target_group_pipeline_en.md new file mode 100644 index 00000000000000..eeda2e2c8ecd35 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_norwegian_bokml_base_target_group_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classifier_norwegian_bokml_base_target_group_pipeline pipeline BertForSequenceClassification from thusken +author: John Snow Labs +name: bert_classifier_norwegian_bokml_base_target_group_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_norwegian_bokml_base_target_group_pipeline` is a English model originally trained by thusken. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_norwegian_bokml_base_target_group_pipeline_en_5.5.0_3.0_1725293483148.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_norwegian_bokml_base_target_group_pipeline_en_5.5.0_3.0_1725293483148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_norwegian_bokml_base_target_group_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_norwegian_bokml_base_target_group_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_norwegian_bokml_base_target_group_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|668.5 MB| + +## References + +https://huggingface.co/thusken/nb-bert-base-target-group + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sanskrit_saskta_sub1_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sanskrit_saskta_sub1_en.md new file mode 100644 index 00000000000000..784c18a4dea7d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sanskrit_saskta_sub1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_classifier_sanskrit_saskta_sub1 BertForSequenceClassification from researchaccount +author: John Snow Labs +name: bert_classifier_sanskrit_saskta_sub1 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sanskrit_saskta_sub1` is a English model originally trained by researchaccount. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub1_en_5.5.0_3.0_1725293352062.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub1_en_5.5.0_3.0_1725293352062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_sanskrit_saskta_sub1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_sanskrit_saskta_sub1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sanskrit_saskta_sub1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|610.9 MB| + +## References + +https://huggingface.co/researchaccount/sa_sub1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sanskrit_saskta_sub3_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sanskrit_saskta_sub3_en.md new file mode 100644 index 00000000000000..9ec98c00d025f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sanskrit_saskta_sub3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_classifier_sanskrit_saskta_sub3 BertForSequenceClassification from researchaccount +author: John Snow Labs +name: bert_classifier_sanskrit_saskta_sub3 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sanskrit_saskta_sub3` is a English model originally trained by researchaccount. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub3_en_5.5.0_3.0_1725293242526.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub3_en_5.5.0_3.0_1725293242526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_sanskrit_saskta_sub3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_sanskrit_saskta_sub3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sanskrit_saskta_sub3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|610.9 MB| + +## References + +https://huggingface.co/researchaccount/sa_sub3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sanskrit_saskta_sub3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sanskrit_saskta_sub3_pipeline_en.md new file mode 100644 index 00000000000000..f71dc81219cbcc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sanskrit_saskta_sub3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classifier_sanskrit_saskta_sub3_pipeline pipeline BertForSequenceClassification from researchaccount +author: John Snow Labs +name: bert_classifier_sanskrit_saskta_sub3_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sanskrit_saskta_sub3_pipeline` is a English model originally trained by researchaccount. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub3_pipeline_en_5.5.0_3.0_1725293278874.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub3_pipeline_en_5.5.0_3.0_1725293278874.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_sanskrit_saskta_sub3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_sanskrit_saskta_sub3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sanskrit_saskta_sub3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|610.9 MB| + +## References + +https://huggingface.co/researchaccount/sa_sub3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sead_l_6_h_256_a_8_qqp_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sead_l_6_h_256_a_8_qqp_en.md new file mode 100644 index 00000000000000..6d49cb4de1e8e8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sead_l_6_h_256_a_8_qqp_en.md @@ -0,0 +1,111 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from course5i) +author: John Snow Labs +name: bert_classifier_sead_l_6_h_256_a_8_qqp +date: 2024-09-02 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `SEAD-L-6_H-256_A-8-qqp` is a English model originally trained by `course5i`. + +## Predicted Entities + +`0`, `1` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_256_a_8_qqp_en_5.5.0_3.0_1725293522744.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_256_a_8_qqp_en_5.5.0_3.0_1725293522744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_sead_l_6_h_256_a_8_qqp","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_sead_l_6_h_256_a_8_qqp","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.glue_qqp.6l_256d_a8a_256d.by_course5i").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sead_l_6_h_256_a_8_qqp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|47.4 MB| + +## References + +References + +- https://huggingface.co/course5i/SEAD-L-6_H-256_A-8-qqp +- https://arxiv.org/abs/1910.01108 +- https://arxiv.org/abs/1909.10351 +- https://arxiv.org/abs/2002.10957 +- https://arxiv.org/abs/1810.04805 +- https://arxiv.org/abs/1804.07461 +- https://arxiv.org/abs/1905.00537 +- https://www.adasci.org/journals/lattice-35309407/?volumes=true&open=621a3b18edc4364e8a96cb63 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sead_l_6_h_256_a_8_qqp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sead_l_6_h_256_a_8_qqp_pipeline_en.md new file mode 100644 index 00000000000000..3df9d057d80bd1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sead_l_6_h_256_a_8_qqp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classifier_sead_l_6_h_256_a_8_qqp_pipeline pipeline BertForSequenceClassification from course5i +author: John Snow Labs +name: bert_classifier_sead_l_6_h_256_a_8_qqp_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sead_l_6_h_256_a_8_qqp_pipeline` is a English model originally trained by course5i. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_256_a_8_qqp_pipeline_en_5.5.0_3.0_1725293525619.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_256_a_8_qqp_pipeline_en_5.5.0_3.0_1725293525619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_sead_l_6_h_256_a_8_qqp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_sead_l_6_h_256_a_8_qqp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_sead_l_6_h_256_a_8_qqp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|47.4 MB| + +## References + +https://huggingface.co/course5i/SEAD-L-6_H-256_A-8-qqp + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_embeddings_custom_legalbert_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_embeddings_custom_legalbert_en.md new file mode 100644 index 00000000000000..5bc8b467b886b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_embeddings_custom_legalbert_en.md @@ -0,0 +1,90 @@ +--- +layout: model +title: English Legal BERT Embedding Cased model +author: John Snow Labs +name: bert_embeddings_custom_legalbert +date: 2024-09-02 +tags: [en, open_source, embeddings, bert, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BERT Embedding model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `custom-legalbert` is a English model originally trained by `zlucia`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_embeddings_custom_legalbert_en_5.5.0_3.0_1725314755008.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_embeddings_custom_legalbert_en_5.5.0_3.0_1725314755008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = BertEmbeddings.pretrained("bert_embeddings_custom_legalbert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings]) + +data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` + + +{:.nlu-block} +```python +import nlu +nlu.load("en.embed.legalbert.legal.custom.by_zlucia").predict("""I love Spark NLP""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_embeddings_custom_legalbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|en| +|Size:|411.6 MB| + +## References + +References + +- https://huggingface.co/zlucia/custom-legalbert +- https://arxiv.org/abs/1808.06226 +- https://case.law/ +- https://arxiv.org/abs/2104.08671 +- https://github.com/reglab/casehold \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_embeddings_custom_legalbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_embeddings_custom_legalbert_pipeline_en.md new file mode 100644 index 00000000000000..6c11c20ea42caa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_embeddings_custom_legalbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_embeddings_custom_legalbert_pipeline pipeline BertEmbeddings from zlucia +author: John Snow Labs +name: bert_embeddings_custom_legalbert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_embeddings_custom_legalbert_pipeline` is a English model originally trained by zlucia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_embeddings_custom_legalbert_pipeline_en_5.5.0_3.0_1725314774837.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_embeddings_custom_legalbert_pipeline_en_5.5.0_3.0_1725314774837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_embeddings_custom_legalbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_embeddings_custom_legalbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_embeddings_custom_legalbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.6 MB| + +## References + +https://huggingface.co/zlucia/custom-legalbert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_finetuned_cuad_legalbert1_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_finetuned_cuad_legalbert1_en.md new file mode 100644 index 00000000000000..5b3301847308df --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_finetuned_cuad_legalbert1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_finetuned_cuad_legalbert1 BertForQuestionAnswering from Jasu +author: John Snow Labs +name: bert_finetuned_cuad_legalbert1 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_cuad_legalbert1` is a English model originally trained by Jasu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_cuad_legalbert1_en_5.5.0_3.0_1725312853394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_cuad_legalbert1_en_5.5.0_3.0_1725312853394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_cuad_legalbert1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_cuad_legalbert1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_cuad_legalbert1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/Jasu/bert-finetuned-cuad-legalbert1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_italian_uncased_question_answering_it.md b/docs/_posts/ahmedlone127/2024-09-02-bert_italian_uncased_question_answering_it.md new file mode 100644 index 00000000000000..245b9d6377e613 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_italian_uncased_question_answering_it.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Italian bert_italian_uncased_question_answering BertForQuestionAnswering from osiria +author: John Snow Labs +name: bert_italian_uncased_question_answering +date: 2024-09-02 +tags: [it, open_source, onnx, question_answering, bert] +task: Question Answering +language: it +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_italian_uncased_question_answering` is a Italian model originally trained by osiria. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_italian_uncased_question_answering_it_5.5.0_3.0_1725312689985.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_italian_uncased_question_answering_it_5.5.0_3.0_1725312689985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_italian_uncased_question_answering","it") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_italian_uncased_question_answering", "it") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_italian_uncased_question_answering| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|it| +|Size:|407.1 MB| + +## References + +https://huggingface.co/osiria/bert-italian-uncased-question-answering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_sequence_classifier_rubert_sentiment_ru.md b/docs/_posts/ahmedlone127/2024-09-02-bert_sequence_classifier_rubert_sentiment_ru.md new file mode 100644 index 00000000000000..1e7efde36db9fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_sequence_classifier_rubert_sentiment_ru.md @@ -0,0 +1,103 @@ +--- +layout: model +title: BERT Sequence Classification - Russian Sentiment Analysis (bert_sequence_classifier_rubert_sentiment) +author: John Snow Labs +name: bert_sequence_classifier_rubert_sentiment +date: 2024-09-02 +tags: [ru, russian, bert, sentiment, rubert, open_source, onnx] +task: Text Classification +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +# RuBERT for Sentiment Analysis +Short Russian texts sentiment classification + +This is a [DeepPavlov/rubert-base-cased-conversational](https://huggingface.co/DeepPavlov/rubert-base-cased-conversational) model trained on aggregated corpus of 351.797 texts. + +## Predicted Entities + +`NEUTRAL`, `POSITIVE`, `NEGATIVE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_rubert_sentiment_ru_5.5.0_3.0_1725293870033.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_rubert_sentiment_ru_5.5.0_3.0_1725293870033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification \ + .pretrained('bert_sequence_classifier_rubert_sentiment', 'ru') \ + .setInputCols(['token', 'document']) \ + .setOutputCol('class') \ + .setCaseSensitive(False) \ + .setMaxSentenceLength(512) + +pipeline = Pipeline(stages=[ + document_assembler, + tokenizer, + sequenceClassifier +]) + +example = spark.createDataFrame([['Ты мне нравишься. Я тебя люблю']]).toDF("text") +result = pipeline.fit(example).transform(example) +``` +```scala +val document_assembler = DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_rubert_sentiment", "ru") + .setInputCols("document", "token") + .setOutputCol("class") + .setCaseSensitive(false) + .setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, sequenceClassifier)) + +val example = Seq("Ты мне нравишься. Я тебя люблю").toDS.toDF("text") + +val result = pipeline.fit(example).transform(example) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_rubert_sentiment| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ru| +|Size:|664.5 MB| \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_squad_portuguese_pt.md b/docs/_posts/ahmedlone127/2024-09-02-bert_squad_portuguese_pt.md new file mode 100644 index 00000000000000..84c9343056d642 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bert_squad_portuguese_pt.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Portuguese bert_squad_portuguese BertForQuestionAnswering from rhaymison +author: John Snow Labs +name: bert_squad_portuguese +date: 2024-09-02 +tags: [pt, open_source, onnx, question_answering, bert] +task: Question Answering +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_squad_portuguese` is a Portuguese model originally trained by rhaymison. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_squad_portuguese_pt_5.5.0_3.0_1725313123219.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_squad_portuguese_pt_5.5.0_3.0_1725313123219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_squad_portuguese","pt") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_squad_portuguese", "pt") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_squad_portuguese| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|pt| +|Size:|405.9 MB| + +## References + +https://huggingface.co/rhaymison/bert-squad-portuguese \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-best_model_yelp_polarity_16_100_en.md b/docs/_posts/ahmedlone127/2024-09-02-best_model_yelp_polarity_16_100_en.md new file mode 100644 index 00000000000000..03e3a4948e7c4d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-best_model_yelp_polarity_16_100_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English best_model_yelp_polarity_16_100 AlbertForSequenceClassification from simonycl +author: John Snow Labs +name: best_model_yelp_polarity_16_100 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_yelp_polarity_16_100` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_yelp_polarity_16_100_en_5.5.0_3.0_1725279401767.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_yelp_polarity_16_100_en_5.5.0_3.0_1725279401767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("best_model_yelp_polarity_16_100","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("best_model_yelp_polarity_16_100", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_yelp_polarity_16_100| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/simonycl/best_model-yelp_polarity-16-100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-best_model_yelp_polarity_16_100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-best_model_yelp_polarity_16_100_pipeline_en.md new file mode 100644 index 00000000000000..a144de84edc9a4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-best_model_yelp_polarity_16_100_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English best_model_yelp_polarity_16_100_pipeline pipeline AlbertForSequenceClassification from simonycl +author: John Snow Labs +name: best_model_yelp_polarity_16_100_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_yelp_polarity_16_100_pipeline` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_yelp_polarity_16_100_pipeline_en_5.5.0_3.0_1725279404286.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_yelp_polarity_16_100_pipeline_en_5.5.0_3.0_1725279404286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("best_model_yelp_polarity_16_100_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("best_model_yelp_polarity_16_100_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_yelp_polarity_16_100_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/simonycl/best_model-yelp_polarity-16-100 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-best_model_yelp_polarity_32_42_en.md b/docs/_posts/ahmedlone127/2024-09-02-best_model_yelp_polarity_32_42_en.md new file mode 100644 index 00000000000000..2296438cf8c3d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-best_model_yelp_polarity_32_42_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English best_model_yelp_polarity_32_42 AlbertForSequenceClassification from simonycl +author: John Snow Labs +name: best_model_yelp_polarity_32_42 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_yelp_polarity_32_42` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_yelp_polarity_32_42_en_5.5.0_3.0_1725301247636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_yelp_polarity_32_42_en_5.5.0_3.0_1725301247636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("best_model_yelp_polarity_32_42","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("best_model_yelp_polarity_32_42", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_yelp_polarity_32_42| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/simonycl/best_model-yelp_polarity-32-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_arguana_dataset_10k_2k_e1_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_arguana_dataset_10k_2k_e1_en.md new file mode 100644 index 00000000000000..473cce3e75a735 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_arguana_dataset_10k_2k_e1_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_arguana_dataset_10k_2k_e1 BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_arguana_dataset_10k_2k_e1 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_arguana_dataset_10k_2k_e1` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_arguana_dataset_10k_2k_e1_en_5.5.0_3.0_1725263313302.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_arguana_dataset_10k_2k_e1_en_5.5.0_3.0_1725263313302.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_arguana_dataset_10k_2k_e1","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_arguana_dataset_10k_2k_e1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_arguana_dataset_10k_2k_e1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|398.1 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-arguana-dataset-10k-2k-e1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_arguana_dataset_10k_2k_e1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_arguana_dataset_10k_2k_e1_pipeline_en.md new file mode 100644 index 00000000000000..f09fa851a2a099 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_arguana_dataset_10k_2k_e1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_arguana_dataset_10k_2k_e1_pipeline pipeline BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_arguana_dataset_10k_2k_e1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_arguana_dataset_10k_2k_e1_pipeline` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_arguana_dataset_10k_2k_e1_pipeline_en_5.5.0_3.0_1725263338121.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_arguana_dataset_10k_2k_e1_pipeline_en_5.5.0_3.0_1725263338121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_arguana_dataset_10k_2k_e1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_arguana_dataset_10k_2k_e1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_arguana_dataset_10k_2k_e1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|398.1 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-arguana-dataset-10k-2k-e1 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_bioasq_matryoshka_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_bioasq_matryoshka_en.md new file mode 100644 index 00000000000000..a4024ba0e115c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_bioasq_matryoshka_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_bioasq_matryoshka BGEEmbeddings from juanpablomesa +author: John Snow Labs +name: bge_base_bioasq_matryoshka +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_bioasq_matryoshka` is a English model originally trained by juanpablomesa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_bioasq_matryoshka_en_5.5.0_3.0_1725262733122.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_bioasq_matryoshka_en_5.5.0_3.0_1725262733122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_bioasq_matryoshka","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_bioasq_matryoshka","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_bioasq_matryoshka| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|388.5 MB| + +## References + +https://huggingface.co/juanpablomesa/bge-base-bioasq-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_bioasq_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_bioasq_matryoshka_pipeline_en.md new file mode 100644 index 00000000000000..78e9d18ab5e095 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_bioasq_matryoshka_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_bioasq_matryoshka_pipeline pipeline BGEEmbeddings from juanpablomesa +author: John Snow Labs +name: bge_base_bioasq_matryoshka_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_bioasq_matryoshka_pipeline` is a English model originally trained by juanpablomesa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_bioasq_matryoshka_pipeline_en_5.5.0_3.0_1725262760628.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_bioasq_matryoshka_pipeline_en_5.5.0_3.0_1725262760628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_bioasq_matryoshka_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_bioasq_matryoshka_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_bioasq_matryoshka_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|388.5 MB| + +## References + +https://huggingface.co/juanpablomesa/bge-base-bioasq-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_climate_fever_dataset_10k_2k_e2_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_climate_fever_dataset_10k_2k_e2_en.md new file mode 100644 index 00000000000000..2da969b5054645 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_climate_fever_dataset_10k_2k_e2_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_climate_fever_dataset_10k_2k_e2 BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_climate_fever_dataset_10k_2k_e2 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_climate_fever_dataset_10k_2k_e2` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_climate_fever_dataset_10k_2k_e2_en_5.5.0_3.0_1725263228825.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_climate_fever_dataset_10k_2k_e2_en_5.5.0_3.0_1725263228825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_climate_fever_dataset_10k_2k_e2","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_climate_fever_dataset_10k_2k_e2","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_climate_fever_dataset_10k_2k_e2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|403.1 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-climate_fever-dataset-10k-2k-e2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_climate_fever_dataset_10k_2k_e2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_climate_fever_dataset_10k_2k_e2_pipeline_en.md new file mode 100644 index 00000000000000..f0497f21af6c4d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_climate_fever_dataset_10k_2k_e2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_climate_fever_dataset_10k_2k_e2_pipeline pipeline BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_climate_fever_dataset_10k_2k_e2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_climate_fever_dataset_10k_2k_e2_pipeline` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_climate_fever_dataset_10k_2k_e2_pipeline_en_5.5.0_3.0_1725263252306.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_climate_fever_dataset_10k_2k_e2_pipeline_en_5.5.0_3.0_1725263252306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_climate_fever_dataset_10k_2k_e2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_climate_fever_dataset_10k_2k_e2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_climate_fever_dataset_10k_2k_e2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.1 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-climate_fever-dataset-10k-2k-e2 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_trivia_anchor_positive_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_trivia_anchor_positive_en.md new file mode 100644 index 00000000000000..d5b7e8beeba92b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_trivia_anchor_positive_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_english_trivia_anchor_positive BGEEmbeddings from SepKeyPro +author: John Snow Labs +name: bge_base_english_trivia_anchor_positive +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_trivia_anchor_positive` is a English model originally trained by SepKeyPro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_trivia_anchor_positive_en_5.5.0_3.0_1725240933579.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_trivia_anchor_positive_en_5.5.0_3.0_1725240933579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_english_trivia_anchor_positive","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_english_trivia_anchor_positive","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_trivia_anchor_positive| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|404.3 MB| + +## References + +https://huggingface.co/SepKeyPro/bge-base-en-trivia-anchor-positive \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_finetuned_ragds_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_finetuned_ragds_v2_en.md new file mode 100644 index 00000000000000..d1435a7bcbdaf2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_finetuned_ragds_v2_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_english_v1_5_finetuned_ragds_v2 BGEEmbeddings from IlhamEbdesk +author: John Snow Labs +name: bge_base_english_v1_5_finetuned_ragds_v2 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_finetuned_ragds_v2` is a English model originally trained by IlhamEbdesk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_ragds_v2_en_5.5.0_3.0_1725241093600.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_ragds_v2_en_5.5.0_3.0_1725241093600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_finetuned_ragds_v2","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_finetuned_ragds_v2","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_finetuned_ragds_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|398.2 MB| + +## References + +https://huggingface.co/IlhamEbdesk/bge-base-en-v1.5-finetuned_ragds_v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_finetuned_ragds_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_finetuned_ragds_v2_pipeline_en.md new file mode 100644 index 00000000000000..05f170459af6a4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_finetuned_ragds_v2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_english_v1_5_finetuned_ragds_v2_pipeline pipeline BGEEmbeddings from IlhamEbdesk +author: John Snow Labs +name: bge_base_english_v1_5_finetuned_ragds_v2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_finetuned_ragds_v2_pipeline` is a English model originally trained by IlhamEbdesk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_ragds_v2_pipeline_en_5.5.0_3.0_1725241117482.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_ragds_v2_pipeline_en_5.5.0_3.0_1725241117482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_english_v1_5_finetuned_ragds_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_english_v1_5_finetuned_ragds_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_finetuned_ragds_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|398.2 MB| + +## References + +https://huggingface.co/IlhamEbdesk/bge-base-en-v1.5-finetuned_ragds_v2 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_fte_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_fte_en.md new file mode 100644 index 00000000000000..c94bfd6c40c460 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_fte_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_english_v1_5_fte BGEEmbeddings from dipanjanS +author: John Snow Labs +name: bge_base_english_v1_5_fte +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_fte` is a English model originally trained by dipanjanS. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_fte_en_5.5.0_3.0_1725241427814.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_fte_en_5.5.0_3.0_1725241427814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_fte","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_fte","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_fte| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|383.9 MB| + +## References + +https://huggingface.co/dipanjanS/bge-base-en-v1.5-fte \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_fte_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_fte_pipeline_en.md new file mode 100644 index 00000000000000..fbbd5bcf6d2b76 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_fte_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_english_v1_5_fte_pipeline pipeline BGEEmbeddings from dipanjanS +author: John Snow Labs +name: bge_base_english_v1_5_fte_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_fte_pipeline` is a English model originally trained by dipanjanS. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_fte_pipeline_en_5.5.0_3.0_1725241461208.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_fte_pipeline_en_5.5.0_3.0_1725241461208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_english_v1_5_fte_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_english_v1_5_fte_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_fte_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.9 MB| + +## References + +https://huggingface.co/dipanjanS/bge-base-en-v1.5-fte + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_klej_dyk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_klej_dyk_pipeline_en.md new file mode 100644 index 00000000000000..db5624c972975c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_klej_dyk_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_english_v1_5_klej_dyk_pipeline pipeline BGEEmbeddings from ve88ifz2 +author: John Snow Labs +name: bge_base_english_v1_5_klej_dyk_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_klej_dyk_pipeline` is a English model originally trained by ve88ifz2. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_klej_dyk_pipeline_en_5.5.0_3.0_1725241984605.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_klej_dyk_pipeline_en_5.5.0_3.0_1725241984605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_english_v1_5_klej_dyk_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_english_v1_5_klej_dyk_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_klej_dyk_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|385.5 MB| + +## References + +https://huggingface.co/ve88ifz2/bge-base-en-v1.5-klej-dyk + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_klej_dyk_v0_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_klej_dyk_v0_2_pipeline_en.md new file mode 100644 index 00000000000000..d80cbd0615a9ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_klej_dyk_v0_2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_english_v1_5_klej_dyk_v0_2_pipeline pipeline BGEEmbeddings from ve88ifz2 +author: John Snow Labs +name: bge_base_english_v1_5_klej_dyk_v0_2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_klej_dyk_v0_2_pipeline` is a English model originally trained by ve88ifz2. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_klej_dyk_v0_2_pipeline_en_5.5.0_3.0_1725242127755.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_klej_dyk_v0_2_pipeline_en_5.5.0_3.0_1725242127755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_english_v1_5_klej_dyk_v0_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_english_v1_5_klej_dyk_v0_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_klej_dyk_v0_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|385.6 MB| + +## References + +https://huggingface.co/ve88ifz2/bge-base-en-v1.5-klej-dyk-v0.2 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka4_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka4_en.md new file mode 100644 index 00000000000000..80c837dc07dc83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka4_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka4 BGEEmbeddings from ValentinaKim +author: John Snow Labs +name: bge_base_financial_matryoshka4 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka4` is a English model originally trained by ValentinaKim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka4_en_5.5.0_3.0_1725241673657.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka4_en_5.5.0_3.0_1725241673657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka4","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka4","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|256.0 MB| + +## References + +https://huggingface.co/ValentinaKim/bge-base-financial-matryoshka4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka4_pipeline_en.md new file mode 100644 index 00000000000000..ad3b5b8d1b0470 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka4_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka4_pipeline pipeline BGEEmbeddings from ValentinaKim +author: John Snow Labs +name: bge_base_financial_matryoshka4_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka4_pipeline` is a English model originally trained by ValentinaKim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka4_pipeline_en_5.5.0_3.0_1725241752224.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka4_pipeline_en_5.5.0_3.0_1725241752224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|256.0 MB| + +## References + +https://huggingface.co/ValentinaKim/bge-base-financial-matryoshka4 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_anisha_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_anisha_en.md new file mode 100644 index 00000000000000..49d9ba5e58d54b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_anisha_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_anisha BGEEmbeddings from anishareddyalla +author: John Snow Labs +name: bge_base_financial_matryoshka_anisha +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_anisha` is a English model originally trained by anishareddyalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_anisha_en_5.5.0_3.0_1725263196029.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_anisha_en_5.5.0_3.0_1725263196029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_anisha","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_anisha","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_anisha| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/anishareddyalla/bge-base-financial-matryoshka-anisha \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_anisha_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_anisha_pipeline_en.md new file mode 100644 index 00000000000000..884698813262d8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_anisha_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_anisha_pipeline pipeline BGEEmbeddings from anishareddyalla +author: John Snow Labs +name: bge_base_financial_matryoshka_anisha_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_anisha_pipeline` is a English model originally trained by anishareddyalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_anisha_pipeline_en_5.5.0_3.0_1725263225226.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_anisha_pipeline_en_5.5.0_3.0_1725263225226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_anisha_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_anisha_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_anisha_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/anishareddyalla/bge-base-financial-matryoshka-anisha + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_bhlim_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_bhlim_en.md new file mode 100644 index 00000000000000..24a607ac29c5f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_bhlim_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_bhlim BGEEmbeddings from bhlim +author: John Snow Labs +name: bge_base_financial_matryoshka_bhlim +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_bhlim` is a English model originally trained by bhlim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_bhlim_en_5.5.0_3.0_1725241473614.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_bhlim_en_5.5.0_3.0_1725241473614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_bhlim","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_bhlim","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_bhlim| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/bhlim/bge-base-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_bhlim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_bhlim_pipeline_en.md new file mode 100644 index 00000000000000..da5aa9b93993d3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_bhlim_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_bhlim_pipeline pipeline BGEEmbeddings from bhlim +author: John Snow Labs +name: bge_base_financial_matryoshka_bhlim_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_bhlim_pipeline` is a English model originally trained by bhlim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_bhlim_pipeline_en_5.5.0_3.0_1725241504547.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_bhlim_pipeline_en_5.5.0_3.0_1725241504547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_bhlim_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_bhlim_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_bhlim_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/bhlim/bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_cngcv_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_cngcv_en.md new file mode 100644 index 00000000000000..bc77cab14a8e52 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_cngcv_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_cngcv BGEEmbeddings from cngcv +author: John Snow Labs +name: bge_base_financial_matryoshka_cngcv +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_cngcv` is a English model originally trained by cngcv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_cngcv_en_5.5.0_3.0_1725262856261.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_cngcv_en_5.5.0_3.0_1725262856261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_cngcv","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_cngcv","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_cngcv| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|376.2 MB| + +## References + +https://huggingface.co/cngcv/bge-base-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_cngcv_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_cngcv_pipeline_en.md new file mode 100644 index 00000000000000..b976512a970cc1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_cngcv_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_cngcv_pipeline pipeline BGEEmbeddings from cngcv +author: John Snow Labs +name: bge_base_financial_matryoshka_cngcv_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_cngcv_pipeline` is a English model originally trained by cngcv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_cngcv_pipeline_en_5.5.0_3.0_1725262888354.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_cngcv_pipeline_en_5.5.0_3.0_1725262888354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_cngcv_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_cngcv_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_cngcv_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|376.2 MB| + +## References + +https://huggingface.co/cngcv/bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_juanpablomesa_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_juanpablomesa_en.md new file mode 100644 index 00000000000000..4801c3fca49fc6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_juanpablomesa_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_juanpablomesa BGEEmbeddings from juanpablomesa +author: John Snow Labs +name: bge_base_financial_matryoshka_juanpablomesa +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_juanpablomesa` is a English model originally trained by juanpablomesa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_juanpablomesa_en_5.5.0_3.0_1725262797745.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_juanpablomesa_en_5.5.0_3.0_1725262797745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_juanpablomesa","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_juanpablomesa","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_juanpablomesa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|399.7 MB| + +## References + +https://huggingface.co/juanpablomesa/bge-base-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_juanpablomesa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_juanpablomesa_pipeline_en.md new file mode 100644 index 00000000000000..11c4ce2ef92e01 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_juanpablomesa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_juanpablomesa_pipeline pipeline BGEEmbeddings from juanpablomesa +author: John Snow Labs +name: bge_base_financial_matryoshka_juanpablomesa_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_juanpablomesa_pipeline` is a English model originally trained by juanpablomesa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_juanpablomesa_pipeline_en_5.5.0_3.0_1725262820953.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_juanpablomesa_pipeline_en_5.5.0_3.0_1725262820953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_juanpablomesa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_juanpablomesa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_juanpablomesa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|399.7 MB| + +## References + +https://huggingface.co/juanpablomesa/bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_korruz_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_korruz_en.md new file mode 100644 index 00000000000000..1f16a3b29f935e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_korruz_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_korruz BGEEmbeddings from korruz +author: John Snow Labs +name: bge_base_financial_matryoshka_korruz +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_korruz` is a English model originally trained by korruz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_korruz_en_5.5.0_3.0_1725263102876.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_korruz_en_5.5.0_3.0_1725263102876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_korruz","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_korruz","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_korruz| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/korruz/bge-base-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_korruz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_korruz_pipeline_en.md new file mode 100644 index 00000000000000..27324350439d74 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_korruz_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_korruz_pipeline pipeline BGEEmbeddings from korruz +author: John Snow Labs +name: bge_base_financial_matryoshka_korruz_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_korruz_pipeline` is a English model originally trained by korruz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_korruz_pipeline_en_5.5.0_3.0_1725263130992.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_korruz_pipeline_en_5.5.0_3.0_1725263130992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_korruz_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_korruz_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_korruz_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/korruz/bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_kperkins411_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_kperkins411_en.md new file mode 100644 index 00000000000000..e178e0b74d87ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_kperkins411_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_kperkins411 BGEEmbeddings from kperkins411 +author: John Snow Labs +name: bge_base_financial_matryoshka_kperkins411 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_kperkins411` is a English model originally trained by kperkins411. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_kperkins411_en_5.5.0_3.0_1725241949279.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_kperkins411_en_5.5.0_3.0_1725241949279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_kperkins411","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_kperkins411","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_kperkins411| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/kperkins411/bge-base-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_kperkins411_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_kperkins411_pipeline_en.md new file mode 100644 index 00000000000000..4f92f8cee63eff --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_kperkins411_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_kperkins411_pipeline pipeline BGEEmbeddings from kperkins411 +author: John Snow Labs +name: bge_base_financial_matryoshka_kperkins411_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_kperkins411_pipeline` is a English model originally trained by kperkins411. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_kperkins411_pipeline_en_5.5.0_3.0_1725241978645.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_kperkins411_pipeline_en_5.5.0_3.0_1725241978645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_kperkins411_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_kperkins411_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_kperkins411_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/kperkins411/bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_naruke_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_naruke_pipeline_en.md new file mode 100644 index 00000000000000..8a1f418c5c35c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_naruke_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_naruke_pipeline pipeline BGEEmbeddings from Naruke +author: John Snow Labs +name: bge_base_financial_matryoshka_naruke_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_naruke_pipeline` is a English model originally trained by Naruke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_naruke_pipeline_en_5.5.0_3.0_1725263231426.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_naruke_pipeline_en_5.5.0_3.0_1725263231426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_naruke_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_naruke_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_naruke_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/Naruke/bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_nvda_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_nvda_en.md new file mode 100644 index 00000000000000..94ea805cbe2a5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_nvda_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_nvda BGEEmbeddings from anikulkar +author: John Snow Labs +name: bge_base_financial_matryoshka_nvda +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_nvda` is a English model originally trained by anikulkar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_nvda_en_5.5.0_3.0_1725241810701.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_nvda_en_5.5.0_3.0_1725241810701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_nvda","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_nvda","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_nvda| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|376.2 MB| + +## References + +https://huggingface.co/anikulkar/bge-base-financial-matryoshka-nvda \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_nvda_iter20_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_nvda_iter20_en.md new file mode 100644 index 00000000000000..f17d27be096cf3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_nvda_iter20_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_nvda_iter20 BGEEmbeddings from anikulkar +author: John Snow Labs +name: bge_base_financial_matryoshka_nvda_iter20 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_nvda_iter20` is a English model originally trained by anikulkar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_nvda_iter20_en_5.5.0_3.0_1725262659066.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_nvda_iter20_en_5.5.0_3.0_1725262659066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_nvda_iter20","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_nvda_iter20","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_nvda_iter20| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|376.2 MB| + +## References + +https://huggingface.co/anikulkar/bge-base-financial-matryoshka-nvda-iter20 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_nvda_iter20_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_nvda_iter20_pipeline_en.md new file mode 100644 index 00000000000000..85141c0ab46702 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_nvda_iter20_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_nvda_iter20_pipeline pipeline BGEEmbeddings from anikulkar +author: John Snow Labs +name: bge_base_financial_matryoshka_nvda_iter20_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_nvda_iter20_pipeline` is a English model originally trained by anikulkar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_nvda_iter20_pipeline_en_5.5.0_3.0_1725262690223.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_nvda_iter20_pipeline_en_5.5.0_3.0_1725262690223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_nvda_iter20_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_nvda_iter20_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_nvda_iter20_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|376.2 MB| + +## References + +https://huggingface.co/anikulkar/bge-base-financial-matryoshka-nvda-iter20 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_nvda_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_nvda_pipeline_en.md new file mode 100644 index 00000000000000..640ea181cb325c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_nvda_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_nvda_pipeline pipeline BGEEmbeddings from anikulkar +author: John Snow Labs +name: bge_base_financial_matryoshka_nvda_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_nvda_pipeline` is a English model originally trained by anikulkar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_nvda_pipeline_en_5.5.0_3.0_1725241844119.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_nvda_pipeline_en_5.5.0_3.0_1725241844119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_nvda_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_nvda_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_nvda_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|376.2 MB| + +## References + +https://huggingface.co/anikulkar/bge-base-financial-matryoshka-nvda + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_test_4_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_test_4_en.md new file mode 100644 index 00000000000000..47406791546903 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_test_4_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_test_4 BGEEmbeddings from NickyNicky +author: John Snow Labs +name: bge_base_financial_matryoshka_test_4 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_test_4` is a English model originally trained by NickyNicky. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_4_en_5.5.0_3.0_1725263500163.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_4_en_5.5.0_3.0_1725263500163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_test_4","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_test_4","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_test_4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/NickyNicky/bge-base-financial-matryoshka_test_4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_test_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_test_4_pipeline_en.md new file mode 100644 index 00000000000000..9597de5caf94d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_test_4_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_test_4_pipeline pipeline BGEEmbeddings from NickyNicky +author: John Snow Labs +name: bge_base_financial_matryoshka_test_4_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_test_4_pipeline` is a English model originally trained by NickyNicky. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_4_pipeline_en_5.5.0_3.0_1725263528612.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_4_pipeline_en_5.5.0_3.0_1725263528612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_test_4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_test_4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_test_4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/NickyNicky/bge-base-financial-matryoshka_test_4 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_yohhei_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_yohhei_en.md new file mode 100644 index 00000000000000..8113de4dd5d67e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_yohhei_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_yohhei BGEEmbeddings from Yohhei +author: John Snow Labs +name: bge_base_financial_matryoshka_yohhei +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_yohhei` is a English model originally trained by Yohhei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_yohhei_en_5.5.0_3.0_1725240939506.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_yohhei_en_5.5.0_3.0_1725240939506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_yohhei","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_yohhei","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_yohhei| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/Yohhei/bge-base-financial-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_yohhei_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_yohhei_pipeline_en.md new file mode 100644 index 00000000000000..b0761fd06b4ce4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_yohhei_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_financial_matryoshka_yohhei_pipeline pipeline BGEEmbeddings from Yohhei +author: John Snow Labs +name: bge_base_financial_matryoshka_yohhei_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_yohhei_pipeline` is a English model originally trained by Yohhei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_yohhei_pipeline_en_5.5.0_3.0_1725240967673.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_yohhei_pipeline_en_5.5.0_3.0_1725240967673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_financial_matryoshka_yohhei_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_yohhei_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_financial_matryoshka_yohhei_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/Yohhei/bge-base-financial-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_matryoshka_aws_casestudies_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_matryoshka_aws_casestudies_en.md new file mode 100644 index 00000000000000..ca7a00c37166a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_matryoshka_aws_casestudies_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_matryoshka_aws_casestudies BGEEmbeddings from anishareddyalla +author: John Snow Labs +name: bge_base_matryoshka_aws_casestudies +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_matryoshka_aws_casestudies` is a English model originally trained by anishareddyalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_matryoshka_aws_casestudies_en_5.5.0_3.0_1725242096135.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_matryoshka_aws_casestudies_en_5.5.0_3.0_1725242096135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_matryoshka_aws_casestudies","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_matryoshka_aws_casestudies","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_matryoshka_aws_casestudies| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|390.4 MB| + +## References + +https://huggingface.co/anishareddyalla/bge-base-matryoshka-aws-casestudies \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_matryoshka_aws_casestudies_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_matryoshka_aws_casestudies_pipeline_en.md new file mode 100644 index 00000000000000..4b0e9ea6dc5f6f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_matryoshka_aws_casestudies_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_matryoshka_aws_casestudies_pipeline pipeline BGEEmbeddings from anishareddyalla +author: John Snow Labs +name: bge_base_matryoshka_aws_casestudies_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_matryoshka_aws_casestudies_pipeline` is a English model originally trained by anishareddyalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_matryoshka_aws_casestudies_pipeline_en_5.5.0_3.0_1725242126148.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_matryoshka_aws_casestudies_pipeline_en_5.5.0_3.0_1725242126148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_matryoshka_aws_casestudies_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_matryoshka_aws_casestudies_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_matryoshka_aws_casestudies_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|390.4 MB| + +## References + +https://huggingface.co/anishareddyalla/bge-base-matryoshka-aws-casestudies + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_mbpp_processed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_mbpp_processed_pipeline_en.md new file mode 100644 index 00000000000000..f152215163b6ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_mbpp_processed_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_mbpp_processed_pipeline pipeline BGEEmbeddings from Nutanix +author: John Snow Labs +name: bge_base_mbpp_processed_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_mbpp_processed_pipeline` is a English model originally trained by Nutanix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_mbpp_processed_pipeline_en_5.5.0_3.0_1725262901592.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_mbpp_processed_pipeline_en_5.5.0_3.0_1725262901592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_mbpp_processed_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_mbpp_processed_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_mbpp_processed_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|377.8 MB| + +## References + +https://huggingface.co/Nutanix/bge-base-mbpp-processed + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v10_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v10_en.md new file mode 100644 index 00000000000000..7ca2f7d0ee08d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v10_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v10 BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v10 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v10` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v10_en_5.5.0_3.0_1725241638223.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v10_en_5.5.0_3.0_1725241638223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v10","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v10","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v10| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|381.5 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v10_pipeline_en.md new file mode 100644 index 00000000000000..dce8c1794bbd00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v10_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v10_pipeline pipeline BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v10_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v10_pipeline` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v10_pipeline_en_5.5.0_3.0_1725241668488.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v10_pipeline_en_5.5.0_3.0_1725241668488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_securiti_dataset_1_v10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_securiti_dataset_1_v10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|381.5 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v10 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v11_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v11_en.md new file mode 100644 index 00000000000000..b0aeca2bb1499b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v11_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v11 BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v11 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v11` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v11_en_5.5.0_3.0_1725263355622.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v11_en_5.5.0_3.0_1725263355622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v11","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v11","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v11| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|381.6 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v11 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v11_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v11_pipeline_en.md new file mode 100644 index 00000000000000..7a08286b1e6de8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v11_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v11_pipeline pipeline BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v11_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v11_pipeline` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v11_pipeline_en_5.5.0_3.0_1725263385991.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v11_pipeline_en_5.5.0_3.0_1725263385991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_securiti_dataset_1_v11_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_securiti_dataset_1_v11_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v11_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|381.6 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v11 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v13_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v13_en.md new file mode 100644 index 00000000000000..621b34a08e550b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v13_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v13 BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v13 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v13` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v13_en_5.5.0_3.0_1725262662585.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v13_en_5.5.0_3.0_1725262662585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v13","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v13","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v13| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|381.3 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v13_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v13_pipeline_en.md new file mode 100644 index 00000000000000..0f312d58d91649 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v13_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v13_pipeline pipeline BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v13_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v13_pipeline` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v13_pipeline_en_5.5.0_3.0_1725262692699.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v13_pipeline_en_5.5.0_3.0_1725262692699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_securiti_dataset_1_v13_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_securiti_dataset_1_v13_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v13_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|381.4 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v13 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v16_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v16_en.md new file mode 100644 index 00000000000000..cfa6ec8d94e8da --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v16_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v16 BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v16 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v16` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v16_en_5.5.0_3.0_1725241853915.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v16_en_5.5.0_3.0_1725241853915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v16","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v16","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v16| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|388.5 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v16 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v16_pipeline_en.md new file mode 100644 index 00000000000000..5c5fc9d447cf1c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v16_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v16_pipeline pipeline BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v16_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v16_pipeline` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v16_pipeline_en_5.5.0_3.0_1725241881063.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v16_pipeline_en_5.5.0_3.0_1725241881063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_securiti_dataset_1_v16_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_securiti_dataset_1_v16_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v16_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|388.5 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v16 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v17_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v17_en.md new file mode 100644 index 00000000000000..c7c1f456e621d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v17_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v17 BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v17 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v17` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v17_en_5.5.0_3.0_1725241928326.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v17_en_5.5.0_3.0_1725241928326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v17","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v17","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v17| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|384.3 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v17 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v22_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v22_en.md new file mode 100644 index 00000000000000..4f6b118c17a1d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v22_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v22 BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v22 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v22` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v22_en_5.5.0_3.0_1725263478386.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v22_en_5.5.0_3.0_1725263478386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v22","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v22","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v22| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|384.8 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v22 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v9_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v9_en.md new file mode 100644 index 00000000000000..e83c60bafed637 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v9_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v9 BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v9 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v9` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v9_en_5.5.0_3.0_1725241940358.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v9_en_5.5.0_3.0_1725241940358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v9","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v9","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v9| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|381.5 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v9_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v9_pipeline_en.md new file mode 100644 index 00000000000000..45593aeeb3d487 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v9_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_securiti_dataset_1_v9_pipeline pipeline BGEEmbeddings from MugheesAwan11 +author: John Snow Labs +name: bge_base_securiti_dataset_1_v9_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v9_pipeline` is a English model originally trained by MugheesAwan11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v9_pipeline_en_5.5.0_3.0_1725241970887.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v9_pipeline_en_5.5.0_3.0_1725241970887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_securiti_dataset_1_v9_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_securiti_dataset_1_v9_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_securiti_dataset_1_v9_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|381.5 MB| + +## References + +https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v9 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_embedding_model2_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_embedding_model2_en.md new file mode 100644 index 00000000000000..cd296fe1e97ede --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_embedding_model2_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_embedding_model2 BGEEmbeddings from SQAI +author: John Snow Labs +name: bge_embedding_model2 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_embedding_model2` is a English model originally trained by SQAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_embedding_model2_en_5.5.0_3.0_1725263588008.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_embedding_model2_en_5.5.0_3.0_1725263588008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_embedding_model2","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_embedding_model2","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_embedding_model2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|115.2 MB| + +## References + +https://huggingface.co/SQAI/bge-embedding-model2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_embedding_model2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_embedding_model2_pipeline_en.md new file mode 100644 index 00000000000000..bbdc8884d9c50f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_embedding_model2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_embedding_model2_pipeline pipeline BGEEmbeddings from SQAI +author: John Snow Labs +name: bge_embedding_model2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_embedding_model2_pipeline` is a English model originally trained by SQAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_embedding_model2_pipeline_en_5.5.0_3.0_1725263595715.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_embedding_model2_pipeline_en_5.5.0_3.0_1725263595715.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_embedding_model2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_embedding_model2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_embedding_model2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|115.2 MB| + +## References + +https://huggingface.co/SQAI/bge-embedding-model2 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_large_chatbot_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_large_chatbot_matryoshka_pipeline_en.md new file mode 100644 index 00000000000000..0a9f84fdad00cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_large_chatbot_matryoshka_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_large_chatbot_matryoshka_pipeline pipeline BGEEmbeddings from MANMEET75 +author: John Snow Labs +name: bge_large_chatbot_matryoshka_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_chatbot_matryoshka_pipeline` is a English model originally trained by MANMEET75. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_chatbot_matryoshka_pipeline_en_5.5.0_3.0_1725241444555.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_chatbot_matryoshka_pipeline_en_5.5.0_3.0_1725241444555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_large_chatbot_matryoshka_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_large_chatbot_matryoshka_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_chatbot_matryoshka_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/MANMEET75/bge-large-Chatbot-matryoshka + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_large_english_v1_5_angleloss_25_epochs_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_large_english_v1_5_angleloss_25_epochs_en.md new file mode 100644 index 00000000000000..d9f5e4ed02f7ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_large_english_v1_5_angleloss_25_epochs_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_large_english_v1_5_angleloss_25_epochs BGEEmbeddings from Areeb-02 +author: John Snow Labs +name: bge_large_english_v1_5_angleloss_25_epochs +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_english_v1_5_angleloss_25_epochs` is a English model originally trained by Areeb-02. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_angleloss_25_epochs_en_5.5.0_3.0_1725241425373.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_angleloss_25_epochs_en_5.5.0_3.0_1725241425373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_large_english_v1_5_angleloss_25_epochs","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_large_english_v1_5_angleloss_25_epochs","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_english_v1_5_angleloss_25_epochs| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Areeb-02/bge-large-en-v1.5-AngleLoss-25-Epochs \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_large_english_v1_5_angleloss_25_epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_large_english_v1_5_angleloss_25_epochs_pipeline_en.md new file mode 100644 index 00000000000000..36e675b967d26f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_large_english_v1_5_angleloss_25_epochs_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_large_english_v1_5_angleloss_25_epochs_pipeline pipeline BGEEmbeddings from Areeb-02 +author: John Snow Labs +name: bge_large_english_v1_5_angleloss_25_epochs_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_english_v1_5_angleloss_25_epochs_pipeline` is a English model originally trained by Areeb-02. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_angleloss_25_epochs_pipeline_en_5.5.0_3.0_1725241506686.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_angleloss_25_epochs_pipeline_en_5.5.0_3.0_1725241506686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_large_english_v1_5_angleloss_25_epochs_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_large_english_v1_5_angleloss_25_epochs_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_english_v1_5_angleloss_25_epochs_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Areeb-02/bge-large-en-v1.5-AngleLoss-25-Epochs + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_small_bioasq_1epoch_batch32_100steps_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_small_bioasq_1epoch_batch32_100steps_en.md new file mode 100644 index 00000000000000..5895bdd56a19f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_small_bioasq_1epoch_batch32_100steps_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_small_bioasq_1epoch_batch32_100steps BGEEmbeddings from juanpablomesa +author: John Snow Labs +name: bge_small_bioasq_1epoch_batch32_100steps +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_bioasq_1epoch_batch32_100steps` is a English model originally trained by juanpablomesa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epoch_batch32_100steps_en_5.5.0_3.0_1725263267333.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epoch_batch32_100steps_en_5.5.0_3.0_1725263267333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_small_bioasq_1epoch_batch32_100steps","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_small_bioasq_1epoch_batch32_100steps","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_bioasq_1epoch_batch32_100steps| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|115.6 MB| + +## References + +https://huggingface.co/juanpablomesa/bge-small-bioasq-1epoch-batch32-100steps \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_small_bioasq_1epoch_batch32_100steps_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_small_bioasq_1epoch_batch32_100steps_pipeline_en.md new file mode 100644 index 00000000000000..2eabc449dd56ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_small_bioasq_1epoch_batch32_100steps_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_small_bioasq_1epoch_batch32_100steps_pipeline pipeline BGEEmbeddings from juanpablomesa +author: John Snow Labs +name: bge_small_bioasq_1epoch_batch32_100steps_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_bioasq_1epoch_batch32_100steps_pipeline` is a English model originally trained by juanpablomesa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epoch_batch32_100steps_pipeline_en_5.5.0_3.0_1725263276792.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epoch_batch32_100steps_pipeline_en_5.5.0_3.0_1725263276792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_small_bioasq_1epoch_batch32_100steps_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_small_bioasq_1epoch_batch32_100steps_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_bioasq_1epoch_batch32_100steps_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|115.6 MB| + +## References + +https://huggingface.co/juanpablomesa/bge-small-bioasq-1epoch-batch32-100steps + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_small_english_multiplrrankingloss_30_rag_paper_dataset_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_small_english_multiplrrankingloss_30_rag_paper_dataset_en.md new file mode 100644 index 00000000000000..fdf2435d4fcb86 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_small_english_multiplrrankingloss_30_rag_paper_dataset_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_small_english_multiplrrankingloss_30_rag_paper_dataset BGEEmbeddings from Areeb-02 +author: John Snow Labs +name: bge_small_english_multiplrrankingloss_30_rag_paper_dataset +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_multiplrrankingloss_30_rag_paper_dataset` is a English model originally trained by Areeb-02. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_multiplrrankingloss_30_rag_paper_dataset_en_5.5.0_3.0_1725263055594.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_multiplrrankingloss_30_rag_paper_dataset_en_5.5.0_3.0_1725263055594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_small_english_multiplrrankingloss_30_rag_paper_dataset","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_small_english_multiplrrankingloss_30_rag_paper_dataset","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_multiplrrankingloss_30_rag_paper_dataset| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|112.3 MB| + +## References + +https://huggingface.co/Areeb-02/bge-small-en-MultiplrRankingLoss-30-Rag-paper-dataset \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_small_english_multiplrrankingloss_30_rag_paper_dataset_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_small_english_multiplrrankingloss_30_rag_paper_dataset_pipeline_en.md new file mode 100644 index 00000000000000..af12a552619c1f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_small_english_multiplrrankingloss_30_rag_paper_dataset_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_small_english_multiplrrankingloss_30_rag_paper_dataset_pipeline pipeline BGEEmbeddings from Areeb-02 +author: John Snow Labs +name: bge_small_english_multiplrrankingloss_30_rag_paper_dataset_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_multiplrrankingloss_30_rag_paper_dataset_pipeline` is a English model originally trained by Areeb-02. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_multiplrrankingloss_30_rag_paper_dataset_pipeline_en_5.5.0_3.0_1725263066219.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_multiplrrankingloss_30_rag_paper_dataset_pipeline_en_5.5.0_3.0_1725263066219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_small_english_multiplrrankingloss_30_rag_paper_dataset_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_small_english_multiplrrankingloss_30_rag_paper_dataset_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_multiplrrankingloss_30_rag_paper_dataset_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|112.3 MB| + +## References + +https://huggingface.co/Areeb-02/bge-small-en-MultiplrRankingLoss-30-Rag-paper-dataset + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_small_matryoshka_fine_tuned_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_small_matryoshka_fine_tuned_en.md new file mode 100644 index 00000000000000..987fedf1c5b0aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_small_matryoshka_fine_tuned_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_small_matryoshka_fine_tuned BGEEmbeddings from rajatrc1705 +author: John Snow Labs +name: bge_small_matryoshka_fine_tuned +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_matryoshka_fine_tuned` is a English model originally trained by rajatrc1705. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_matryoshka_fine_tuned_en_5.5.0_3.0_1725262549555.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_matryoshka_fine_tuned_en_5.5.0_3.0_1725262549555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_small_matryoshka_fine_tuned","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_small_matryoshka_fine_tuned","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_matryoshka_fine_tuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|123.8 MB| + +## References + +https://huggingface.co/rajatrc1705/bge-small-matryoshka-fine-tuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_small_matryoshka_fine_tuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_small_matryoshka_fine_tuned_pipeline_en.md new file mode 100644 index 00000000000000..1aaafdc05bdf1e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_small_matryoshka_fine_tuned_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_small_matryoshka_fine_tuned_pipeline pipeline BGEEmbeddings from rajatrc1705 +author: John Snow Labs +name: bge_small_matryoshka_fine_tuned_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_matryoshka_fine_tuned_pipeline` is a English model originally trained by rajatrc1705. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_matryoshka_fine_tuned_pipeline_en_5.5.0_3.0_1725262556049.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_matryoshka_fine_tuned_pipeline_en_5.5.0_3.0_1725262556049.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_small_matryoshka_fine_tuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_small_matryoshka_fine_tuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_matryoshka_fine_tuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|123.8 MB| + +## References + +https://huggingface.co/rajatrc1705/bge-small-matryoshka-fine-tuned + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_small_method1_triplet_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_small_method1_triplet_en.md new file mode 100644 index 00000000000000..18638b78adbdcd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_small_method1_triplet_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_small_method1_triplet BGEEmbeddings from smokxy +author: John Snow Labs +name: bge_small_method1_triplet +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_method1_triplet` is a English model originally trained by smokxy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_method1_triplet_en_5.5.0_3.0_1725263599812.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_method1_triplet_en_5.5.0_3.0_1725263599812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_small_method1_triplet","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_small_method1_triplet","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_method1_triplet| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|116.3 MB| + +## References + +https://huggingface.co/smokxy/bge_small_method1_triplet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_small_method1_triplet_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_small_method1_triplet_pipeline_en.md new file mode 100644 index 00000000000000..d43d1797f4c85a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bge_small_method1_triplet_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_small_method1_triplet_pipeline pipeline BGEEmbeddings from smokxy +author: John Snow Labs +name: bge_small_method1_triplet_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_method1_triplet_pipeline` is a English model originally trained by smokxy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_method1_triplet_pipeline_en_5.5.0_3.0_1725263608363.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_method1_triplet_pipeline_en_5.5.0_3.0_1725263608363.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_small_method1_triplet_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_small_method1_triplet_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_method1_triplet_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|116.3 MB| + +## References + +https://huggingface.co/smokxy/bge_small_method1_triplet + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-binaryaugmentedcards_en.md b/docs/_posts/ahmedlone127/2024-09-02-binaryaugmentedcards_en.md new file mode 100644 index 00000000000000..cf4fbfa9a7d85a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-binaryaugmentedcards_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English binaryaugmentedcards RoBertaForSequenceClassification from crarojasca +author: John Snow Labs +name: binaryaugmentedcards +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`binaryaugmentedcards` is a English model originally trained by crarojasca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/binaryaugmentedcards_en_5.5.0_3.0_1725277855900.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/binaryaugmentedcards_en_5.5.0_3.0_1725277855900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("binaryaugmentedcards","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("binaryaugmentedcards", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|binaryaugmentedcards| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/crarojasca/BinaryAugmentedCARDS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-binaryaugmentedcards_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-binaryaugmentedcards_pipeline_en.md new file mode 100644 index 00000000000000..04c3f7470047be --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-binaryaugmentedcards_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English binaryaugmentedcards_pipeline pipeline RoBertaForSequenceClassification from crarojasca +author: John Snow Labs +name: binaryaugmentedcards_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`binaryaugmentedcards_pipeline` is a English model originally trained by crarojasca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/binaryaugmentedcards_pipeline_en_5.5.0_3.0_1725277927124.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/binaryaugmentedcards_pipeline_en_5.5.0_3.0_1725277927124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("binaryaugmentedcards_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("binaryaugmentedcards_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|binaryaugmentedcards_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/crarojasca/BinaryAugmentedCARDS + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-binitha_camembert_en.md b/docs/_posts/ahmedlone127/2024-09-02-binitha_camembert_en.md new file mode 100644 index 00000000000000..0d294ebfd1fbc7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-binitha_camembert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English binitha_camembert CamemBertEmbeddings from Binitha +author: John Snow Labs +name: binitha_camembert +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`binitha_camembert` is a English model originally trained by Binitha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/binitha_camembert_en_5.5.0_3.0_1725299514134.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/binitha_camembert_en_5.5.0_3.0_1725299514134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("binitha_camembert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("binitha_camembert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|binitha_camembert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Binitha/binitha_camembert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-binitha_camembert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-binitha_camembert_pipeline_en.md new file mode 100644 index 00000000000000..f7bdd1806dc615 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-binitha_camembert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English binitha_camembert_pipeline pipeline CamemBertEmbeddings from Binitha +author: John Snow Labs +name: binitha_camembert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`binitha_camembert_pipeline` is a English model originally trained by Binitha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/binitha_camembert_pipeline_en_5.5.0_3.0_1725299595663.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/binitha_camembert_pipeline_en_5.5.0_3.0_1725299595663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("binitha_camembert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("binitha_camembert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|binitha_camembert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Binitha/binitha_camembert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bio_roberta_base_pubmed_en.md b/docs/_posts/ahmedlone127/2024-09-02-bio_roberta_base_pubmed_en.md new file mode 100644 index 00000000000000..b80583bc8bd05c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bio_roberta_base_pubmed_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bio_roberta_base_pubmed RoBertaEmbeddings from minhpqn +author: John Snow Labs +name: bio_roberta_base_pubmed +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bio_roberta_base_pubmed` is a English model originally trained by minhpqn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bio_roberta_base_pubmed_en_5.5.0_3.0_1725265104643.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bio_roberta_base_pubmed_en_5.5.0_3.0_1725265104643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("bio_roberta_base_pubmed","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("bio_roberta_base_pubmed","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bio_roberta_base_pubmed| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|466.0 MB| + +## References + +https://huggingface.co/minhpqn/bio_roberta-base_pubmed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bio_roberta_base_pubmed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bio_roberta_base_pubmed_pipeline_en.md new file mode 100644 index 00000000000000..fd4cda615f1129 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bio_roberta_base_pubmed_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bio_roberta_base_pubmed_pipeline pipeline RoBertaEmbeddings from minhpqn +author: John Snow Labs +name: bio_roberta_base_pubmed_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bio_roberta_base_pubmed_pipeline` is a English model originally trained by minhpqn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bio_roberta_base_pubmed_pipeline_en_5.5.0_3.0_1725265128854.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bio_roberta_base_pubmed_pipeline_en_5.5.0_3.0_1725265128854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bio_roberta_base_pubmed_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bio_roberta_base_pubmed_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bio_roberta_base_pubmed_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|466.0 MB| + +## References + +https://huggingface.co/minhpqn/bio_roberta-base_pubmed + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-biolord_2023_s_en.md b/docs/_posts/ahmedlone127/2024-09-02-biolord_2023_s_en.md new file mode 100644 index 00000000000000..21741ab7219c99 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-biolord_2023_s_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English biolord_2023_s MPNetEmbeddings from FremyCompany +author: John Snow Labs +name: biolord_2023_s +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biolord_2023_s` is a English model originally trained by FremyCompany. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biolord_2023_s_en_5.5.0_3.0_1725258510787.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biolord_2023_s_en_5.5.0_3.0_1725258510787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("biolord_2023_s","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("biolord_2023_s","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biolord_2023_s| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/FremyCompany/BioLORD-2023-S \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-biolord_2023_s_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-biolord_2023_s_pipeline_en.md new file mode 100644 index 00000000000000..fc5cd0f8594c1d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-biolord_2023_s_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English biolord_2023_s_pipeline pipeline MPNetEmbeddings from FremyCompany +author: John Snow Labs +name: biolord_2023_s_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biolord_2023_s_pipeline` is a English model originally trained by FremyCompany. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biolord_2023_s_pipeline_en_5.5.0_3.0_1725258532441.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biolord_2023_s_pipeline_en_5.5.0_3.0_1725258532441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("biolord_2023_s_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("biolord_2023_s_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biolord_2023_s_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/FremyCompany/BioLORD-2023-S + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-bsc_bio_ehr_spanish_cantemist_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-02-bsc_bio_ehr_spanish_cantemist_pipeline_es.md new file mode 100644 index 00000000000000..acab6ddc29e900 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-bsc_bio_ehr_spanish_cantemist_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish bsc_bio_ehr_spanish_cantemist_pipeline pipeline RoBertaForTokenClassification from PlanTL-GOB-ES +author: John Snow Labs +name: bsc_bio_ehr_spanish_cantemist_pipeline +date: 2024-09-02 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_cantemist_pipeline` is a Castilian, Spanish model originally trained by PlanTL-GOB-ES. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_cantemist_pipeline_es_5.5.0_3.0_1725311511446.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_cantemist_pipeline_es_5.5.0_3.0_1725311511446.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bsc_bio_ehr_spanish_cantemist_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bsc_bio_ehr_spanish_cantemist_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bsc_bio_ehr_spanish_cantemist_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|434.9 MB| + +## References + +https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es-cantemist + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_eli5_mlm_model_stevhliu_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_eli5_mlm_model_stevhliu_en.md new file mode 100644 index 00000000000000..5e456e89f96585 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_eli5_mlm_model_stevhliu_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_eli5_mlm_model_stevhliu RoBertaEmbeddings from stevhliu +author: John Snow Labs +name: burmese_awesome_eli5_mlm_model_stevhliu +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_stevhliu` is a English model originally trained by stevhliu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_stevhliu_en_5.5.0_3.0_1725264915972.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_stevhliu_en_5.5.0_3.0_1725264915972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_stevhliu","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_stevhliu","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_eli5_mlm_model_stevhliu| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|306.5 MB| + +## References + +https://huggingface.co/stevhliu/my_awesome_eli5_mlm_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_eli5_mlm_model_stevhliu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_eli5_mlm_model_stevhliu_pipeline_en.md new file mode 100644 index 00000000000000..adcf15cf898dcd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_eli5_mlm_model_stevhliu_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_eli5_mlm_model_stevhliu_pipeline pipeline RoBertaEmbeddings from stevhliu +author: John Snow Labs +name: burmese_awesome_eli5_mlm_model_stevhliu_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_stevhliu_pipeline` is a English model originally trained by stevhliu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_stevhliu_pipeline_en_5.5.0_3.0_1725264932383.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_stevhliu_pipeline_en_5.5.0_3.0_1725264932383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_stevhliu_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_stevhliu_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_eli5_mlm_model_stevhliu_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|306.5 MB| + +## References + +https://huggingface.co/stevhliu/my_awesome_eli5_mlm_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_20wds_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_20wds_pipeline_en.md new file mode 100644 index 00000000000000..9f4b3ace0a0362 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_20wds_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_model_20wds_pipeline pipeline DistilBertForSequenceClassification from 20wds +author: John Snow Labs +name: burmese_awesome_model_20wds_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_20wds_pipeline` is a English model originally trained by 20wds. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_20wds_pipeline_en_5.5.0_3.0_1725305780381.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_20wds_pipeline_en_5.5.0_3.0_1725305780381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_model_20wds_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_model_20wds_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_model_20wds_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/20wds/my_awesome_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_cptkorsche_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_cptkorsche_en.md new file mode 100644 index 00000000000000..ac3a9a9a70bd6a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_cptkorsche_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_model_cptkorsche DistilBertForSequenceClassification from CptKorsche +author: John Snow Labs +name: burmese_awesome_model_cptkorsche +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_cptkorsche` is a English model originally trained by CptKorsche. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_cptkorsche_en_5.5.0_3.0_1725291861420.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_cptkorsche_en_5.5.0_3.0_1725291861420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_cptkorsche","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_cptkorsche", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_model_cptkorsche| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/CptKorsche/my_awesome_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_rdsmaia_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_rdsmaia_pipeline_en.md new file mode 100644 index 00000000000000..01eb979c6f7e7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_rdsmaia_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_model_rdsmaia_pipeline pipeline DistilBertForSequenceClassification from rdsmaia +author: John Snow Labs +name: burmese_awesome_model_rdsmaia_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_rdsmaia_pipeline` is a English model originally trained by rdsmaia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_rdsmaia_pipeline_en_5.5.0_3.0_1725306274544.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_rdsmaia_pipeline_en_5.5.0_3.0_1725306274544.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_model_rdsmaia_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_model_rdsmaia_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_model_rdsmaia_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/rdsmaia/my_awesome_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_opus_books_model_shivakanthreddy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_opus_books_model_shivakanthreddy_pipeline_en.md new file mode 100644 index 00000000000000..2dbbe2863a2bd5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_opus_books_model_shivakanthreddy_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_opus_books_model_shivakanthreddy_pipeline pipeline MarianTransformer from shivakanthreddy +author: John Snow Labs +name: burmese_awesome_opus_books_model_shivakanthreddy_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_shivakanthreddy_pipeline` is a English model originally trained by shivakanthreddy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_shivakanthreddy_pipeline_en_5.5.0_3.0_1725295447255.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_shivakanthreddy_pipeline_en_5.5.0_3.0_1725295447255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_shivakanthreddy_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_shivakanthreddy_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_opus_books_model_shivakanthreddy_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.8 MB| + +## References + +https://huggingface.co/shivakanthreddy/my_awesome_opus_books_model + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_opus_books_model_yasmineelabbar_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_opus_books_model_yasmineelabbar_en.md new file mode 100644 index 00000000000000..3511e3b3c21576 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_opus_books_model_yasmineelabbar_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_opus_books_model_yasmineelabbar MarianTransformer from yasmineelabbar +author: John Snow Labs +name: burmese_awesome_opus_books_model_yasmineelabbar +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_yasmineelabbar` is a English model originally trained by yasmineelabbar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_yasmineelabbar_en_5.5.0_3.0_1725243858007.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_yasmineelabbar_en_5.5.0_3.0_1725243858007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("burmese_awesome_opus_books_model_yasmineelabbar","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("burmese_awesome_opus_books_model_yasmineelabbar","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_opus_books_model_yasmineelabbar| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.4 MB| + +## References + +https://huggingface.co/yasmineelabbar/my_awesome_opus_books_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_setfit_model_ameer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_setfit_model_ameer_pipeline_en.md new file mode 100644 index 00000000000000..e5aefb7389e6d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_setfit_model_ameer_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English burmese_awesome_setfit_model_ameer_pipeline pipeline MPNetEmbeddings from ameerak +author: John Snow Labs +name: burmese_awesome_setfit_model_ameer_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_ameer_pipeline` is a English model originally trained by ameerak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_ameer_pipeline_en_5.5.0_3.0_1725280661793.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_ameer_pipeline_en_5.5.0_3.0_1725280661793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_setfit_model_ameer_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_setfit_model_ameer_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_setfit_model_ameer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/ameerak/my-awesome-setfit-model-ameer + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_setfit_model_martinv_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_setfit_model_martinv_en.md new file mode 100644 index 00000000000000..d7faeb4fa83098 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_setfit_model_martinv_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English burmese_awesome_setfit_model_martinv MPNetEmbeddings from MartinV +author: John Snow Labs +name: burmese_awesome_setfit_model_martinv +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_martinv` is a English model originally trained by MartinV. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_martinv_en_5.5.0_3.0_1725280358104.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_martinv_en_5.5.0_3.0_1725280358104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_martinv","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_martinv","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_setfit_model_martinv| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/MartinV/my-awesome-setfit-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_setfit_model_martinv_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_setfit_model_martinv_pipeline_en.md new file mode 100644 index 00000000000000..a3c98f4ba244af --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_setfit_model_martinv_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English burmese_awesome_setfit_model_martinv_pipeline pipeline MPNetEmbeddings from MartinV +author: John Snow Labs +name: burmese_awesome_setfit_model_martinv_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_martinv_pipeline` is a English model originally trained by MartinV. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_martinv_pipeline_en_5.5.0_3.0_1725280379251.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_martinv_pipeline_en_5.5.0_3.0_1725280379251.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_setfit_model_martinv_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_setfit_model_martinv_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_setfit_model_martinv_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/MartinV/my-awesome-setfit-model + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_all_us_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_all_us_en.md new file mode 100644 index 00000000000000..031d89919a892c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_all_us_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_wnut_all_us DistilBertForTokenClassification from gonzalezrostani +author: John Snow Labs +name: burmese_awesome_wnut_all_us +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_all_us` is a English model originally trained by gonzalezrostani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_us_en_5.5.0_3.0_1725267313715.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_us_en_5.5.0_3.0_1725267313715.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_all_us","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_all_us", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_all_us| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/gonzalezrostani/my_awesome_wnut_all_US \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_all_us_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_all_us_pipeline_en.md new file mode 100644 index 00000000000000..ce2193d5355a96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_all_us_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_wnut_all_us_pipeline pipeline DistilBertForTokenClassification from gonzalezrostani +author: John Snow Labs +name: burmese_awesome_wnut_all_us_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_all_us_pipeline` is a English model originally trained by gonzalezrostani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_us_pipeline_en_5.5.0_3.0_1725267327039.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_us_pipeline_en_5.5.0_3.0_1725267327039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_wnut_all_us_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_wnut_all_us_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_all_us_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/gonzalezrostani/my_awesome_wnut_all_US + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_arunaramm7_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_arunaramm7_en.md new file mode 100644 index 00000000000000..9fb6616a5cf415 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_arunaramm7_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_wnut_model_arunaramm7 DistilBertForTokenClassification from arunaramm7 +author: John Snow Labs +name: burmese_awesome_wnut_model_arunaramm7 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_arunaramm7` is a English model originally trained by arunaramm7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_arunaramm7_en_5.5.0_3.0_1725267645629.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_arunaramm7_en_5.5.0_3.0_1725267645629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_arunaramm7","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_arunaramm7", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_model_arunaramm7| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/arunaramm7/my_awesome_wnut_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_costadomar_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_costadomar_pipeline_en.md new file mode 100644 index 00000000000000..d8bbe4d165106c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_costadomar_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_wnut_model_costadomar_pipeline pipeline DistilBertForTokenClassification from costadomar +author: John Snow Labs +name: burmese_awesome_wnut_model_costadomar_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_costadomar_pipeline` is a English model originally trained by costadomar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_costadomar_pipeline_en_5.5.0_3.0_1725268048682.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_costadomar_pipeline_en_5.5.0_3.0_1725268048682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_wnut_model_costadomar_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_costadomar_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_model_costadomar_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/costadomar/my_awesome_wnut_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_insa_ad_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_insa_ad_en.md new file mode 100644 index 00000000000000..9196c5e9b3199f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_insa_ad_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_wnut_model_insa_ad DistilBertForTokenClassification from insa-ad +author: John Snow Labs +name: burmese_awesome_wnut_model_insa_ad +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_insa_ad` is a English model originally trained by insa-ad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_insa_ad_en_5.5.0_3.0_1725267505084.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_insa_ad_en_5.5.0_3.0_1725267505084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_insa_ad","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_insa_ad", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_model_insa_ad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/insa-ad/my_awesome_wnut_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_insa_ad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_insa_ad_pipeline_en.md new file mode 100644 index 00000000000000..67b52ef77c5c6e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_insa_ad_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_wnut_model_insa_ad_pipeline pipeline DistilBertForTokenClassification from insa-ad +author: John Snow Labs +name: burmese_awesome_wnut_model_insa_ad_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_insa_ad_pipeline` is a English model originally trained by insa-ad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_insa_ad_pipeline_en_5.5.0_3.0_1725267518801.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_insa_ad_pipeline_en_5.5.0_3.0_1725267518801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_wnut_model_insa_ad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_insa_ad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_model_insa_ad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/insa-ad/my_awesome_wnut_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_mohamedfasil_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_mohamedfasil_pipeline_en.md new file mode 100644 index 00000000000000..9af6c29d47422f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_mohamedfasil_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_wnut_model_mohamedfasil_pipeline pipeline DistilBertForTokenClassification from Mohamedfasil +author: John Snow Labs +name: burmese_awesome_wnut_model_mohamedfasil_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_mohamedfasil_pipeline` is a English model originally trained by Mohamedfasil. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_mohamedfasil_pipeline_en_5.5.0_3.0_1725267547021.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_mohamedfasil_pipeline_en_5.5.0_3.0_1725267547021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_wnut_model_mohamedfasil_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_mohamedfasil_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_model_mohamedfasil_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/Mohamedfasil/my_awesome_wnut_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_ymgong_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_ymgong_en.md new file mode 100644 index 00000000000000..ac36ad8cc36000 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_ymgong_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_wnut_model_ymgong DistilBertForTokenClassification from ymgong +author: John Snow Labs +name: burmese_awesome_wnut_model_ymgong +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_ymgong` is a English model originally trained by ymgong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_ymgong_en_5.5.0_3.0_1725267944000.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_ymgong_en_5.5.0_3.0_1725267944000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_ymgong","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_ymgong", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_model_ymgong| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/ymgong/my_awesome_wnut_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_ymgong_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_ymgong_pipeline_en.md new file mode 100644 index 00000000000000..9fc5eaaa28222f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_ymgong_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_wnut_model_ymgong_pipeline pipeline DistilBertForTokenClassification from ymgong +author: John Snow Labs +name: burmese_awesome_wnut_model_ymgong_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_ymgong_pipeline` is a English model originally trained by ymgong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_ymgong_pipeline_en_5.5.0_3.0_1725267957412.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_ymgong_pipeline_en_5.5.0_3.0_1725267957412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_wnut_model_ymgong_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_ymgong_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_wnut_model_ymgong_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/ymgong/my_awesome_wnut_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_english_tonga_tonga_islands_german_model_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_english_tonga_tonga_islands_german_model_en.md new file mode 100644 index 00000000000000..b70c7027dba990 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_english_tonga_tonga_islands_german_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_english_tonga_tonga_islands_german_model MarianTransformer from shivakanthreddy +author: John Snow Labs +name: burmese_english_tonga_tonga_islands_german_model +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_english_tonga_tonga_islands_german_model` is a English model originally trained by shivakanthreddy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_english_tonga_tonga_islands_german_model_en_5.5.0_3.0_1725243094548.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_english_tonga_tonga_islands_german_model_en_5.5.0_3.0_1725243094548.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("burmese_english_tonga_tonga_islands_german_model","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("burmese_english_tonga_tonga_islands_german_model","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_english_tonga_tonga_islands_german_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.2 MB| + +## References + +https://huggingface.co/shivakanthreddy/my_english_to_german_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_english_tonga_tonga_islands_german_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_english_tonga_tonga_islands_german_model_pipeline_en.md new file mode 100644 index 00000000000000..9e5f8da3a5fa4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_english_tonga_tonga_islands_german_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_english_tonga_tonga_islands_german_model_pipeline pipeline MarianTransformer from shivakanthreddy +author: John Snow Labs +name: burmese_english_tonga_tonga_islands_german_model_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_english_tonga_tonga_islands_german_model_pipeline` is a English model originally trained by shivakanthreddy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_english_tonga_tonga_islands_german_model_pipeline_en_5.5.0_3.0_1725243121520.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_english_tonga_tonga_islands_german_model_pipeline_en_5.5.0_3.0_1725243121520.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_english_tonga_tonga_islands_german_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_english_tonga_tonga_islands_german_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_english_tonga_tonga_islands_german_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.8 MB| + +## References + +https://huggingface.co/shivakanthreddy/my_english_to_german_model + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_great_model_haltincay_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_great_model_haltincay_en.md new file mode 100644 index 00000000000000..eca6a07daf10b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_great_model_haltincay_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_great_model_haltincay DistilBertForSequenceClassification from haltincay +author: John Snow Labs +name: burmese_great_model_haltincay +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_great_model_haltincay` is a English model originally trained by haltincay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_great_model_haltincay_en_5.5.0_3.0_1725291611533.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_great_model_haltincay_en_5.5.0_3.0_1725291611533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_great_model_haltincay","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_great_model_haltincay", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_great_model_haltincay| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/haltincay/my_great_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_nepal_bhasa_ner_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_nepal_bhasa_ner_en.md new file mode 100644 index 00000000000000..a60bb53c2992aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_nepal_bhasa_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_nepal_bhasa_ner DistilBertForTokenClassification from hcy5561 +author: John Snow Labs +name: burmese_nepal_bhasa_ner +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_nepal_bhasa_ner` is a English model originally trained by hcy5561. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_nepal_bhasa_ner_en_5.5.0_3.0_1725267706421.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_nepal_bhasa_ner_en_5.5.0_3.0_1725267706421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_nepal_bhasa_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_nepal_bhasa_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_nepal_bhasa_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/hcy5561/my_new_ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_test_repo_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_test_repo_en.md new file mode 100644 index 00000000000000..8dd1d2a3af0abc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_test_repo_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_test_repo CamemBertEmbeddings from martindevoto +author: John Snow Labs +name: burmese_test_repo +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_test_repo` is a English model originally trained by martindevoto. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_test_repo_en_5.5.0_3.0_1725302499494.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_test_repo_en_5.5.0_3.0_1725302499494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("burmese_test_repo","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("burmese_test_repo","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_test_repo| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/martindevoto/my-test-repo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-camembert_base_legacy_fr.md b/docs/_posts/ahmedlone127/2024-09-02-camembert_base_legacy_fr.md new file mode 100644 index 00000000000000..2cfceb184f63b7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-camembert_base_legacy_fr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: French camembert_base_legacy CamemBertEmbeddings from almanach +author: John Snow Labs +name: camembert_base_legacy +date: 2024-09-02 +tags: [fr, open_source, onnx, embeddings, camembert] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_base_legacy` is a French model originally trained by almanach. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_base_legacy_fr_5.5.0_3.0_1725320173666.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_base_legacy_fr_5.5.0_3.0_1725320173666.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("camembert_base_legacy","fr") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("camembert_base_legacy","fr") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_base_legacy| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|fr| +|Size:|264.0 MB| + +## References + +https://huggingface.co/almanach/camembert-base-legacy \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-camembert_base_legacy_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-camembert_base_legacy_pipeline_fr.md new file mode 100644 index 00000000000000..339c089d430a0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-camembert_base_legacy_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French camembert_base_legacy_pipeline pipeline CamemBertEmbeddings from almanach +author: John Snow Labs +name: camembert_base_legacy_pipeline +date: 2024-09-02 +tags: [fr, open_source, pipeline, onnx] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_base_legacy_pipeline` is a French model originally trained by almanach. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_base_legacy_pipeline_fr_5.5.0_3.0_1725320251552.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_base_legacy_pipeline_fr_5.5.0_3.0_1725320251552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("camembert_base_legacy_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("camembert_base_legacy_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_base_legacy_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|264.0 MB| + +## References + +https://huggingface.co/almanach/camembert-base-legacy + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-camembert_embeddings_dummy_model_fr.md b/docs/_posts/ahmedlone127/2024-09-02-camembert_embeddings_dummy_model_fr.md new file mode 100644 index 00000000000000..d16a0cf0ef7df8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-camembert_embeddings_dummy_model_fr.md @@ -0,0 +1,100 @@ +--- +layout: model +title: French Camembert Embeddings model (from winterdawn) +author: John Snow Labs +name: camembert_embeddings_dummy_model +date: 2024-09-02 +tags: [camembert, open_source, camembert_embeddings, camembertformaskedlm, fr, onnx] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamembertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `dummy-model` is a French model originally trained by `winterdawn`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_embeddings_dummy_model_fr_5.5.0_3.0_1725296700561.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_embeddings_dummy_model_fr_5.5.0_3.0_1725296700561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("camembert_embeddings_dummy_model","fr") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") \ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings]) + +data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("camembert_embeddings_dummy_model","fr") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) + +val data = Seq("I love Spark NLP").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_embeddings_dummy_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|fr| +|Size:|264.0 MB| + +## References + +References + +https://huggingface.co/winterdawn/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-camembert_embeddings_dummy_model_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-camembert_embeddings_dummy_model_pipeline_fr.md new file mode 100644 index 00000000000000..ca7d9bbce68f7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-camembert_embeddings_dummy_model_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French camembert_embeddings_dummy_model_pipeline pipeline CamemBertEmbeddings from winterdawn +author: John Snow Labs +name: camembert_embeddings_dummy_model_pipeline +date: 2024-09-02 +tags: [fr, open_source, pipeline, onnx] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_embeddings_dummy_model_pipeline` is a French model originally trained by winterdawn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_embeddings_dummy_model_pipeline_fr_5.5.0_3.0_1725296780101.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_embeddings_dummy_model_pipeline_fr_5.5.0_3.0_1725296780101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("camembert_embeddings_dummy_model_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("camembert_embeddings_dummy_model_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_embeddings_dummy_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|264.0 MB| + +## References + +https://huggingface.co/winterdawn/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-camembert_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2024-09-02-camembert_finetuned_ner_en.md new file mode 100644 index 00000000000000..9e7d5a4d7b08fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-camembert_finetuned_ner_en.md @@ -0,0 +1,100 @@ +--- +layout: model +title: English camembert_finetuned_ner CamemBertForTokenClassification from jcr987 +author: John Snow Labs +name: camembert_finetuned_ner +date: 2024-09-02 +tags: [camembert, en, open_source, token_classification, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_finetuned_ner` is a English model originally trained by jcr987. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_finetuned_ner_en_5.5.0_3.0_1725266524584.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_finetuned_ner_en_5.5.0_3.0_1725266524584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols(["document"]) \ + .setOutputCol("token") + + +tokenClassifier = CamemBertForTokenClassification.pretrained("camembert_finetuned_ner","en") \ + .setInputCols(["document","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = Tokenizer() \ + .setInputCols(Array("document")) \ + .setOutputCol("token") + +val tokenClassifier = CamemBertForTokenClassification + .pretrained("camembert_finetuned_ner", "en") + .setInputCols(Array("document","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_finetuned_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|399.3 MB| + +## References + +References + +https://huggingface.co/jcr987/camembert-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-camembert_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-camembert_finetuned_ner_pipeline_en.md new file mode 100644 index 00000000000000..c1562958542b95 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-camembert_finetuned_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English camembert_finetuned_ner_pipeline pipeline CamemBertForTokenClassification from ManoloMtl +author: John Snow Labs +name: camembert_finetuned_ner_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_finetuned_ner_pipeline` is a English model originally trained by ManoloMtl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_finetuned_ner_pipeline_en_5.5.0_3.0_1725266556355.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_finetuned_ner_pipeline_en_5.5.0_3.0_1725266556355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("camembert_finetuned_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("camembert_finetuned_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_finetuned_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|399.4 MB| + +## References + +https://huggingface.co/ManoloMtl/camembert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-camembert_ner_loc_en.md b/docs/_posts/ahmedlone127/2024-09-02-camembert_ner_loc_en.md new file mode 100644 index 00000000000000..9246d82b08f136 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-camembert_ner_loc_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English camembert_ner_loc CamemBertForTokenClassification from konverner +author: John Snow Labs +name: camembert_ner_loc +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, camembert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_ner_loc` is a English model originally trained by konverner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_ner_loc_en_5.5.0_3.0_1725266403205.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_ner_loc_en_5.5.0_3.0_1725266403205.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = CamemBertForTokenClassification.pretrained("camembert_ner_loc","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = CamemBertForTokenClassification.pretrained("camembert_ner_loc", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_ner_loc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/konverner/camembert-ner-loc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-camembert_ner_loc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-camembert_ner_loc_pipeline_en.md new file mode 100644 index 00000000000000..c56a216002efec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-camembert_ner_loc_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English camembert_ner_loc_pipeline pipeline CamemBertForTokenClassification from konverner +author: John Snow Labs +name: camembert_ner_loc_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_ner_loc_pipeline` is a English model originally trained by konverner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_ner_loc_pipeline_en_5.5.0_3.0_1725266425125.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_ner_loc_pipeline_en_5.5.0_3.0_1725266425125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("camembert_ner_loc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("camembert_ner_loc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_ner_loc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/konverner/camembert-ner-loc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-cat_ner_xlmr_3_en.md b/docs/_posts/ahmedlone127/2024-09-02-cat_ner_xlmr_3_en.md new file mode 100644 index 00000000000000..f302d0aa38abad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-cat_ner_xlmr_3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cat_ner_xlmr_3 XlmRoBertaForTokenClassification from homersimpson +author: John Snow Labs +name: cat_ner_xlmr_3 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cat_ner_xlmr_3` is a English model originally trained by homersimpson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cat_ner_xlmr_3_en_5.5.0_3.0_1725321572119.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cat_ner_xlmr_3_en_5.5.0_3.0_1725321572119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("cat_ner_xlmr_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("cat_ner_xlmr_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cat_ner_xlmr_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|814.3 MB| + +## References + +https://huggingface.co/homersimpson/cat-ner-xlmr-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-cat_sayula_popoluca_italian_4_en.md b/docs/_posts/ahmedlone127/2024-09-02-cat_sayula_popoluca_italian_4_en.md new file mode 100644 index 00000000000000..8d7fcf54f25a83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-cat_sayula_popoluca_italian_4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cat_sayula_popoluca_italian_4 CamemBertForTokenClassification from homersimpson +author: John Snow Labs +name: cat_sayula_popoluca_italian_4 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, camembert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cat_sayula_popoluca_italian_4` is a English model originally trained by homersimpson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_italian_4_en_5.5.0_3.0_1725266143788.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_italian_4_en_5.5.0_3.0_1725266143788.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = CamemBertForTokenClassification.pretrained("cat_sayula_popoluca_italian_4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = CamemBertForTokenClassification.pretrained("cat_sayula_popoluca_italian_4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cat_sayula_popoluca_italian_4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|391.7 MB| + +## References + +https://huggingface.co/homersimpson/cat-pos-it-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-cat_sayula_popoluca_italian_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-cat_sayula_popoluca_italian_4_pipeline_en.md new file mode 100644 index 00000000000000..e23c10c35ccfe3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-cat_sayula_popoluca_italian_4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cat_sayula_popoluca_italian_4_pipeline pipeline CamemBertForTokenClassification from homersimpson +author: John Snow Labs +name: cat_sayula_popoluca_italian_4_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cat_sayula_popoluca_italian_4_pipeline` is a English model originally trained by homersimpson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_italian_4_pipeline_en_5.5.0_3.0_1725266172052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_italian_4_pipeline_en_5.5.0_3.0_1725266172052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cat_sayula_popoluca_italian_4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cat_sayula_popoluca_italian_4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cat_sayula_popoluca_italian_4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|391.7 MB| + +## References + +https://huggingface.co/homersimpson/cat-pos-it-4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-catalan_spanish_en.md b/docs/_posts/ahmedlone127/2024-09-02-catalan_spanish_en.md new file mode 100644 index 00000000000000..ac781c7d1bdc00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-catalan_spanish_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English catalan_spanish MarianTransformer from Ife +author: John Snow Labs +name: catalan_spanish +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`catalan_spanish` is a English model originally trained by Ife. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/catalan_spanish_en_5.5.0_3.0_1725304644326.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/catalan_spanish_en_5.5.0_3.0_1725304644326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("catalan_spanish","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("catalan_spanish","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|catalan_spanish| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|452.2 MB| + +## References + +https://huggingface.co/Ife/CA-ES \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-catalan_spanish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-catalan_spanish_pipeline_en.md new file mode 100644 index 00000000000000..7365b568f817bc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-catalan_spanish_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English catalan_spanish_pipeline pipeline MarianTransformer from Ife +author: John Snow Labs +name: catalan_spanish_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`catalan_spanish_pipeline` is a English model originally trained by Ife. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/catalan_spanish_pipeline_en_5.5.0_3.0_1725304668012.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/catalan_spanish_pipeline_en_5.5.0_3.0_1725304668012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("catalan_spanish_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("catalan_spanish_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|catalan_spanish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|452.7 MB| + +## References + +https://huggingface.co/Ife/CA-ES + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-category_cleaning_clip_clip_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-category_cleaning_clip_clip_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..4e7964e439ac70 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-category_cleaning_clip_clip_finetuned_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English category_cleaning_clip_clip_finetuned_pipeline pipeline CLIPForZeroShotClassification from kpalczewski-displate +author: John Snow Labs +name: category_cleaning_clip_clip_finetuned_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`category_cleaning_clip_clip_finetuned_pipeline` is a English model originally trained by kpalczewski-displate. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/category_cleaning_clip_clip_finetuned_pipeline_en_5.5.0_3.0_1725275234697.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/category_cleaning_clip_clip_finetuned_pipeline_en_5.5.0_3.0_1725275234697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("category_cleaning_clip_clip_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("category_cleaning_clip_clip_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|category_cleaning_clip_clip_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/kpalczewski-displate/category-cleaning-clip-clip-finetuned + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-checkpoint_21200_en.md b/docs/_posts/ahmedlone127/2024-09-02-checkpoint_21200_en.md new file mode 100644 index 00000000000000..0ede8770aa4811 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-checkpoint_21200_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English checkpoint_21200 XlmRoBertaEmbeddings from yemen2016 +author: John Snow Labs +name: checkpoint_21200 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`checkpoint_21200` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/checkpoint_21200_en_5.5.0_3.0_1725271661142.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checkpoint_21200_en_5.5.0_3.0_1725271661142.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("checkpoint_21200","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("checkpoint_21200","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|checkpoint_21200| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/checkpoint-21200 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-checkpoint_21200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-checkpoint_21200_pipeline_en.md new file mode 100644 index 00000000000000..495f067b53ef0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-checkpoint_21200_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English checkpoint_21200_pipeline pipeline XlmRoBertaEmbeddings from yemen2016 +author: John Snow Labs +name: checkpoint_21200_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`checkpoint_21200_pipeline` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/checkpoint_21200_pipeline_en_5.5.0_3.0_1725271717680.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checkpoint_21200_pipeline_en_5.5.0_3.0_1725271717680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("checkpoint_21200_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("checkpoint_21200_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|checkpoint_21200_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/checkpoint-21200 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-checkpoint_23200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-checkpoint_23200_pipeline_en.md new file mode 100644 index 00000000000000..4564462cd96bee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-checkpoint_23200_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English checkpoint_23200_pipeline pipeline XlmRoBertaEmbeddings from yemen2016 +author: John Snow Labs +name: checkpoint_23200_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`checkpoint_23200_pipeline` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/checkpoint_23200_pipeline_en_5.5.0_3.0_1725270972456.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checkpoint_23200_pipeline_en_5.5.0_3.0_1725270972456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("checkpoint_23200_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("checkpoint_23200_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|checkpoint_23200_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/checkpoint-23200 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-choubert_8_fr.md b/docs/_posts/ahmedlone127/2024-09-02-choubert_8_fr.md new file mode 100644 index 00000000000000..a26e383553c64e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-choubert_8_fr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: French choubert_8 CamemBertEmbeddings from ChouBERT +author: John Snow Labs +name: choubert_8 +date: 2024-09-02 +tags: [fr, open_source, onnx, embeddings, camembert] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`choubert_8` is a French model originally trained by ChouBERT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/choubert_8_fr_5.5.0_3.0_1725319729612.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/choubert_8_fr_5.5.0_3.0_1725319729612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("choubert_8","fr") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("choubert_8","fr") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|choubert_8| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|fr| +|Size:|412.8 MB| + +## References + +https://huggingface.co/ChouBERT/ChouBERT-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-classifier__generated_data_only__potencialsdetection_albert_en.md b/docs/_posts/ahmedlone127/2024-09-02-classifier__generated_data_only__potencialsdetection_albert_en.md new file mode 100644 index 00000000000000..56d88ede0be597 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-classifier__generated_data_only__potencialsdetection_albert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English classifier__generated_data_only__potencialsdetection_albert AlbertForSequenceClassification from yevhenkost +author: John Snow Labs +name: classifier__generated_data_only__potencialsdetection_albert +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classifier__generated_data_only__potencialsdetection_albert` is a English model originally trained by yevhenkost. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classifier__generated_data_only__potencialsdetection_albert_en_5.5.0_3.0_1725278994354.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classifier__generated_data_only__potencialsdetection_albert_en_5.5.0_3.0_1725278994354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("classifier__generated_data_only__potencialsdetection_albert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("classifier__generated_data_only__potencialsdetection_albert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|classifier__generated_data_only__potencialsdetection_albert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/yevhenkost/classifier__generated_data_only__potencialsdetection_albert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-classifier__generated_data_only__potencialsdetection_albert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-classifier__generated_data_only__potencialsdetection_albert_pipeline_en.md new file mode 100644 index 00000000000000..71ca3d6a7e4fbc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-classifier__generated_data_only__potencialsdetection_albert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English classifier__generated_data_only__potencialsdetection_albert_pipeline pipeline AlbertForSequenceClassification from yevhenkost +author: John Snow Labs +name: classifier__generated_data_only__potencialsdetection_albert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classifier__generated_data_only__potencialsdetection_albert_pipeline` is a English model originally trained by yevhenkost. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classifier__generated_data_only__potencialsdetection_albert_pipeline_en_5.5.0_3.0_1725278996844.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classifier__generated_data_only__potencialsdetection_albert_pipeline_en_5.5.0_3.0_1725278996844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("classifier__generated_data_only__potencialsdetection_albert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("classifier__generated_data_only__potencialsdetection_albert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|classifier__generated_data_only__potencialsdetection_albert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/yevhenkost/classifier__generated_data_only__potencialsdetection_albert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-classifier__generated_data_only__purposesdetection_albert_en.md b/docs/_posts/ahmedlone127/2024-09-02-classifier__generated_data_only__purposesdetection_albert_en.md new file mode 100644 index 00000000000000..66522ff1c25a31 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-classifier__generated_data_only__purposesdetection_albert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English classifier__generated_data_only__purposesdetection_albert AlbertForSequenceClassification from yevhenkost +author: John Snow Labs +name: classifier__generated_data_only__purposesdetection_albert +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classifier__generated_data_only__purposesdetection_albert` is a English model originally trained by yevhenkost. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classifier__generated_data_only__purposesdetection_albert_en_5.5.0_3.0_1725279013761.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classifier__generated_data_only__purposesdetection_albert_en_5.5.0_3.0_1725279013761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("classifier__generated_data_only__purposesdetection_albert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("classifier__generated_data_only__purposesdetection_albert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|classifier__generated_data_only__purposesdetection_albert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/yevhenkost/classifier__generated_data_only__purposesdetection_albert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-classifier__generated_data_only__purposesdetection_albert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-classifier__generated_data_only__purposesdetection_albert_pipeline_en.md new file mode 100644 index 00000000000000..1715e11bd3b7e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-classifier__generated_data_only__purposesdetection_albert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English classifier__generated_data_only__purposesdetection_albert_pipeline pipeline AlbertForSequenceClassification from yevhenkost +author: John Snow Labs +name: classifier__generated_data_only__purposesdetection_albert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classifier__generated_data_only__purposesdetection_albert_pipeline` is a English model originally trained by yevhenkost. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classifier__generated_data_only__purposesdetection_albert_pipeline_en_5.5.0_3.0_1725279016261.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classifier__generated_data_only__purposesdetection_albert_pipeline_en_5.5.0_3.0_1725279016261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("classifier__generated_data_only__purposesdetection_albert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("classifier__generated_data_only__purposesdetection_albert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|classifier__generated_data_only__purposesdetection_albert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/yevhenkost/classifier__generated_data_only__purposesdetection_albert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-classifier_camembert_en.md b/docs/_posts/ahmedlone127/2024-09-02-classifier_camembert_en.md new file mode 100644 index 00000000000000..def4f0fc924944 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-classifier_camembert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English classifier_camembert CamemBertForSequenceClassification from DioulaD +author: John Snow Labs +name: classifier_camembert +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classifier_camembert` is a English model originally trained by DioulaD. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classifier_camembert_en_5.5.0_3.0_1725298980277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classifier_camembert_en_5.5.0_3.0_1725298980277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("classifier_camembert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("classifier_camembert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|classifier_camembert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|389.1 MB| + +## References + +https://huggingface.co/DioulaD/classifier-camembert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-classify_clickbait_titles_en.md b/docs/_posts/ahmedlone127/2024-09-02-classify_clickbait_titles_en.md new file mode 100644 index 00000000000000..94d79ee18d3c25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-classify_clickbait_titles_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English classify_clickbait_titles AlbertForSequenceClassification from ilsilfverskiold +author: John Snow Labs +name: classify_clickbait_titles +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classify_clickbait_titles` is a English model originally trained by ilsilfverskiold. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classify_clickbait_titles_en_5.5.0_3.0_1725279062266.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classify_clickbait_titles_en_5.5.0_3.0_1725279062266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("classify_clickbait_titles","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("classify_clickbait_titles", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|classify_clickbait_titles| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/ilsilfverskiold/classify-clickbait-titles \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-classify_clickbait_titles_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-classify_clickbait_titles_pipeline_en.md new file mode 100644 index 00000000000000..ea7282640a7e30 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-classify_clickbait_titles_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English classify_clickbait_titles_pipeline pipeline AlbertForSequenceClassification from ilsilfverskiold +author: John Snow Labs +name: classify_clickbait_titles_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classify_clickbait_titles_pipeline` is a English model originally trained by ilsilfverskiold. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classify_clickbait_titles_pipeline_en_5.5.0_3.0_1725279064757.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classify_clickbait_titles_pipeline_en_5.5.0_3.0_1725279064757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("classify_clickbait_titles_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("classify_clickbait_titles_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|classify_clickbait_titles_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/ilsilfverskiold/classify-clickbait-titles + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-cleaned_e5_base_unsupervised_test_en.md b/docs/_posts/ahmedlone127/2024-09-02-cleaned_e5_base_unsupervised_test_en.md new file mode 100644 index 00000000000000..8d9c9d88e13a1c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-cleaned_e5_base_unsupervised_test_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English cleaned_e5_base_unsupervised_test E5Embeddings from rithwik-db +author: John Snow Labs +name: cleaned_e5_base_unsupervised_test +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_e5_base_unsupervised_test` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_unsupervised_test_en_5.5.0_3.0_1725259270103.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_unsupervised_test_en_5.5.0_3.0_1725259270103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("cleaned_e5_base_unsupervised_test","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("cleaned_e5_base_unsupervised_test","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cleaned_e5_base_unsupervised_test| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|386.2 MB| + +## References + +https://huggingface.co/rithwik-db/cleaned-e5-base-unsupervised-test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-cleaned_e5_base_unsupervised_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-cleaned_e5_base_unsupervised_test_pipeline_en.md new file mode 100644 index 00000000000000..964fc307f1c188 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-cleaned_e5_base_unsupervised_test_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English cleaned_e5_base_unsupervised_test_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: cleaned_e5_base_unsupervised_test_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_e5_base_unsupervised_test_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_unsupervised_test_pipeline_en_5.5.0_3.0_1725259297791.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_unsupervised_test_pipeline_en_5.5.0_3.0_1725259297791.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cleaned_e5_base_unsupervised_test_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cleaned_e5_base_unsupervised_test_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cleaned_e5_base_unsupervised_test_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|386.2 MB| + +## References + +https://huggingface.co/rithwik-db/cleaned-e5-base-unsupervised-test + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-cline_emanuals_s10_arabic_en.md b/docs/_posts/ahmedlone127/2024-09-02-cline_emanuals_s10_arabic_en.md new file mode 100644 index 00000000000000..f441e37c881a51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-cline_emanuals_s10_arabic_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cline_emanuals_s10_arabic RoBertaForSequenceClassification from AnonymousSub +author: John Snow Labs +name: cline_emanuals_s10_arabic +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cline_emanuals_s10_arabic` is a English model originally trained by AnonymousSub. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cline_emanuals_s10_arabic_en_5.5.0_3.0_1725238265166.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cline_emanuals_s10_arabic_en_5.5.0_3.0_1725238265166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("cline_emanuals_s10_arabic","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("cline_emanuals_s10_arabic", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cline_emanuals_s10_arabic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|467.9 MB| + +## References + +https://huggingface.co/AnonymousSub/cline-emanuals-s10-AR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-cline_emanuals_s10_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-cline_emanuals_s10_arabic_pipeline_en.md new file mode 100644 index 00000000000000..a2e1d74a375bc3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-cline_emanuals_s10_arabic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cline_emanuals_s10_arabic_pipeline pipeline RoBertaForSequenceClassification from AnonymousSub +author: John Snow Labs +name: cline_emanuals_s10_arabic_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cline_emanuals_s10_arabic_pipeline` is a English model originally trained by AnonymousSub. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cline_emanuals_s10_arabic_pipeline_en_5.5.0_3.0_1725238290308.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cline_emanuals_s10_arabic_pipeline_en_5.5.0_3.0_1725238290308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cline_emanuals_s10_arabic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cline_emanuals_s10_arabic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cline_emanuals_s10_arabic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|467.9 MB| + +## References + +https://huggingface.co/AnonymousSub/cline-emanuals-s10-AR + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clinicalbertprqab_280_54_czech_en.md b/docs/_posts/ahmedlone127/2024-09-02-clinicalbertprqab_280_54_czech_en.md new file mode 100644 index 00000000000000..2a45031bbd19c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clinicalbertprqab_280_54_czech_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English clinicalbertprqab_280_54_czech BertForQuestionAnswering from lanzv +author: John Snow Labs +name: clinicalbertprqab_280_54_czech +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbertprqab_280_54_czech` is a English model originally trained by lanzv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbertprqab_280_54_czech_en_5.5.0_3.0_1725313132849.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbertprqab_280_54_czech_en_5.5.0_3.0_1725313132849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("clinicalbertprqab_280_54_czech","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("clinicalbertprqab_280_54_czech", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clinicalbertprqab_280_54_czech| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/lanzv/ClinicalBERTPRQAB_280_54_CS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clinicalbertprqab_280_54_czech_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clinicalbertprqab_280_54_czech_pipeline_en.md new file mode 100644 index 00000000000000..08c188b10e10b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clinicalbertprqab_280_54_czech_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clinicalbertprqab_280_54_czech_pipeline pipeline BertForQuestionAnswering from lanzv +author: John Snow Labs +name: clinicalbertprqab_280_54_czech_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbertprqab_280_54_czech_pipeline` is a English model originally trained by lanzv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbertprqab_280_54_czech_pipeline_en_5.5.0_3.0_1725313164887.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbertprqab_280_54_czech_pipeline_en_5.5.0_3.0_1725313164887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clinicalbertprqab_280_54_czech_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clinicalbertprqab_280_54_czech_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clinicalbertprqab_280_54_czech_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/lanzv/ClinicalBERTPRQAB_280_54_CS + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_clip_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_clip_finetuned_en.md new file mode 100644 index 00000000000000..ea34eae14c0318 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_clip_finetuned_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_clip_finetuned CLIPForZeroShotClassification from kpalczewski-displate +author: John Snow Labs +name: clip_clip_finetuned +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_clip_finetuned` is a English model originally trained by kpalczewski-displate. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_clip_finetuned_en_5.5.0_3.0_1725275403878.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_clip_finetuned_en_5.5.0_3.0_1725275403878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_clip_finetuned","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_clip_finetuned","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_clip_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/kpalczewski-displate/clip-clip-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_clip_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_clip_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..156cf2ca3885e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_clip_finetuned_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_clip_finetuned_pipeline pipeline CLIPForZeroShotClassification from kpalczewski-displate +author: John Snow Labs +name: clip_clip_finetuned_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_clip_finetuned_pipeline` is a English model originally trained by kpalczewski-displate. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_clip_finetuned_pipeline_en_5.5.0_3.0_1725275435795.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_clip_finetuned_pipeline_en_5.5.0_3.0_1725275435795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_clip_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_clip_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_clip_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/kpalczewski-displate/clip-clip-finetuned + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_fashion_attribute_model_try_3_base32_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_fashion_attribute_model_try_3_base32_en.md new file mode 100644 index 00000000000000..a297341333f7bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_fashion_attribute_model_try_3_base32_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_fashion_attribute_model_try_3_base32 CLIPForZeroShotClassification from Geetansh13 +author: John Snow Labs +name: clip_fashion_attribute_model_try_3_base32 +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_fashion_attribute_model_try_3_base32` is a English model originally trained by Geetansh13. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_fashion_attribute_model_try_3_base32_en_5.5.0_3.0_1725256427610.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_fashion_attribute_model_try_3_base32_en_5.5.0_3.0_1725256427610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_fashion_attribute_model_try_3_base32","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_fashion_attribute_model_try_3_base32","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_fashion_attribute_model_try_3_base32| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|587.0 MB| + +## References + +https://huggingface.co/Geetansh13/clip-fashion-attribute-model-try-3-base32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_fashion_attribute_model_try_3_base32_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_fashion_attribute_model_try_3_base32_pipeline_en.md new file mode 100644 index 00000000000000..e5a4b5f4c64745 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_fashion_attribute_model_try_3_base32_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_fashion_attribute_model_try_3_base32_pipeline pipeline CLIPForZeroShotClassification from Geetansh13 +author: John Snow Labs +name: clip_fashion_attribute_model_try_3_base32_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_fashion_attribute_model_try_3_base32_pipeline` is a English model originally trained by Geetansh13. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_fashion_attribute_model_try_3_base32_pipeline_en_5.5.0_3.0_1725256454435.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_fashion_attribute_model_try_3_base32_pipeline_en_5.5.0_3.0_1725256454435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_fashion_attribute_model_try_3_base32_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_fashion_attribute_model_try_3_base32_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_fashion_attribute_model_try_3_base32_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|587.1 MB| + +## References + +https://huggingface.co/Geetansh13/clip-fashion-attribute-model-try-3-base32 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_ft_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_ft_en.md new file mode 100644 index 00000000000000..1663ed81ae5665 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_ft_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_ft CLIPForZeroShotClassification from masterhaniwa +author: John Snow Labs +name: clip_ft +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_ft` is a English model originally trained by masterhaniwa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_ft_en_5.5.0_3.0_1725256776504.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_ft_en_5.5.0_3.0_1725256776504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_ft","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_ft","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_ft| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|561.2 MB| + +## References + +https://huggingface.co/masterhaniwa/CLIP_ft \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_ft_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_ft_pipeline_en.md new file mode 100644 index 00000000000000..114eb8e721c0f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_ft_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_ft_pipeline pipeline CLIPForZeroShotClassification from masterhaniwa +author: John Snow Labs +name: clip_ft_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_ft_pipeline` is a English model originally trained by masterhaniwa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_ft_pipeline_en_5.5.0_3.0_1725256806179.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_ft_pipeline_en_5.5.0_3.0_1725256806179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_ft_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_ft_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_ft_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|561.2 MB| + +## References + +https://huggingface.co/masterhaniwa/CLIP_ft + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_samim2024_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_samim2024_pipeline_en.md new file mode 100644 index 00000000000000..24733897c50f46 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_samim2024_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_samim2024_pipeline pipeline CLIPForZeroShotClassification from samim2024 +author: John Snow Labs +name: clip_samim2024_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_samim2024_pipeline` is a English model originally trained by samim2024. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_samim2024_pipeline_en_5.5.0_3.0_1725257315429.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_samim2024_pipeline_en_5.5.0_3.0_1725257315429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_samim2024_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_samim2024_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_samim2024_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/samim2024/clip + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_seed_vit_4_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_seed_vit_4_en.md new file mode 100644 index 00000000000000..3d213568955449 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_seed_vit_4_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_seed_vit_4 CLIPForZeroShotClassification from zabir735 +author: John Snow Labs +name: clip_seed_vit_4 +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_seed_vit_4` is a English model originally trained by zabir735. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_seed_vit_4_en_5.5.0_3.0_1725275853866.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_seed_vit_4_en_5.5.0_3.0_1725275853866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_seed_vit_4","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_seed_vit_4","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_seed_vit_4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|561.2 MB| + +## References + +https://huggingface.co/zabir735/clip-seed-vit-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_seed_vit_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_seed_vit_4_pipeline_en.md new file mode 100644 index 00000000000000..22efd60d6a9c72 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_seed_vit_4_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_seed_vit_4_pipeline pipeline CLIPForZeroShotClassification from zabir735 +author: John Snow Labs +name: clip_seed_vit_4_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_seed_vit_4_pipeline` is a English model originally trained by zabir735. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_seed_vit_4_pipeline_en_5.5.0_3.0_1725275883077.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_seed_vit_4_pipeline_en_5.5.0_3.0_1725275883077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_seed_vit_4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_seed_vit_4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_seed_vit_4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|561.2 MB| + +## References + +https://huggingface.co/zabir735/clip-seed-vit-4 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_seed_vit_noval_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_seed_vit_noval_en.md new file mode 100644 index 00000000000000..575e135e57e984 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_seed_vit_noval_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_seed_vit_noval CLIPForZeroShotClassification from zabir735 +author: John Snow Labs +name: clip_seed_vit_noval +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_seed_vit_noval` is a English model originally trained by zabir735. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_seed_vit_noval_en_5.5.0_3.0_1725276058438.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_seed_vit_noval_en_5.5.0_3.0_1725276058438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_seed_vit_noval","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_seed_vit_noval","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_seed_vit_noval| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|561.2 MB| + +## References + +https://huggingface.co/zabir735/clip-seed-vit-noval \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_seed_vit_noval_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_seed_vit_noval_pipeline_en.md new file mode 100644 index 00000000000000..9ee0fb59b9cb1f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_seed_vit_noval_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_seed_vit_noval_pipeline pipeline CLIPForZeroShotClassification from zabir735 +author: John Snow Labs +name: clip_seed_vit_noval_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_seed_vit_noval_pipeline` is a English model originally trained by zabir735. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_seed_vit_noval_pipeline_en_5.5.0_3.0_1725276092986.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_seed_vit_noval_pipeline_en_5.5.0_3.0_1725276092986.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_seed_vit_noval_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_seed_vit_noval_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_seed_vit_noval_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|561.2 MB| + +## References + +https://huggingface.co/zabir735/clip-seed-vit-noval + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_b_32_laion2b_s34b_b79k_laion_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_b_32_laion2b_s34b_b79k_laion_en.md new file mode 100644 index 00000000000000..cb7d0c5895a97c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_b_32_laion2b_s34b_b79k_laion_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_b_32_laion2b_s34b_b79k_laion CLIPForZeroShotClassification from laion +author: John Snow Labs +name: clip_vit_b_32_laion2b_s34b_b79k_laion +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_b_32_laion2b_s34b_b79k_laion` is a English model originally trained by laion. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_b_32_laion2b_s34b_b79k_laion_en_5.5.0_3.0_1725276498788.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_b_32_laion2b_s34b_b79k_laion_en_5.5.0_3.0_1725276498788.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_b_32_laion2b_s34b_b79k_laion","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_b_32_laion2b_s34b_b79k_laion","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_b_32_laion2b_s34b_b79k_laion| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|567.6 MB| + +## References + +https://huggingface.co/laion/CLIP-ViT-B-32-laion2B-s34B-b79K \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_b_32_laion2b_s34b_b79k_laion_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_b_32_laion2b_s34b_b79k_laion_pipeline_en.md new file mode 100644 index 00000000000000..b4e6b857e39469 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_b_32_laion2b_s34b_b79k_laion_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_vit_b_32_laion2b_s34b_b79k_laion_pipeline pipeline CLIPForZeroShotClassification from laion +author: John Snow Labs +name: clip_vit_b_32_laion2b_s34b_b79k_laion_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_b_32_laion2b_s34b_b79k_laion_pipeline` is a English model originally trained by laion. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_b_32_laion2b_s34b_b79k_laion_pipeline_en_5.5.0_3.0_1725276527958.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_b_32_laion2b_s34b_b79k_laion_pipeline_en_5.5.0_3.0_1725276527958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_vit_b_32_laion2b_s34b_b79k_laion_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_vit_b_32_laion2b_s34b_b79k_laion_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_b_32_laion2b_s34b_b79k_laion_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.6 MB| + +## References + +https://huggingface.co/laion/CLIP-ViT-B-32-laion2B-s34B-b79K + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patch32_demo_fluffypotato_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patch32_demo_fluffypotato_en.md new file mode 100644 index 00000000000000..14558fa568f63f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patch32_demo_fluffypotato_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_base_patch32_demo_fluffypotato CLIPForZeroShotClassification from fluffypotato +author: John Snow Labs +name: clip_vit_base_patch32_demo_fluffypotato +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_demo_fluffypotato` is a English model originally trained by fluffypotato. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_fluffypotato_en_5.5.0_3.0_1725275221231.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_fluffypotato_en_5.5.0_3.0_1725275221231.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo_fluffypotato","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo_fluffypotato","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_demo_fluffypotato| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/fluffypotato/clip-vit-base-patch32-demo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patch32_korean_ko.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patch32_korean_ko.md new file mode 100644 index 00000000000000..be8e19691d2190 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patch32_korean_ko.md @@ -0,0 +1,120 @@ +--- +layout: model +title: Korean clip_vit_base_patch32_korean CLIPForZeroShotClassification from Bingsu +author: John Snow Labs +name: clip_vit_base_patch32_korean +date: 2024-09-02 +tags: [ko, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: ko +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_korean` is a Korean model originally trained by Bingsu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_korean_ko_5.5.0_3.0_1725256919711.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_korean_ko_5.5.0_3.0_1725256919711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_korean","ko") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_korean","ko") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_korean| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|ko| +|Size:|449.1 MB| + +## References + +https://huggingface.co/Bingsu/clip-vit-base-patch32-ko \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patch32_korean_pipeline_ko.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patch32_korean_pipeline_ko.md new file mode 100644 index 00000000000000..2d498105690379 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patch32_korean_pipeline_ko.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Korean clip_vit_base_patch32_korean_pipeline pipeline CLIPForZeroShotClassification from Bingsu +author: John Snow Labs +name: clip_vit_base_patch32_korean_pipeline +date: 2024-09-02 +tags: [ko, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: ko +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_korean_pipeline` is a Korean model originally trained by Bingsu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_korean_pipeline_ko_5.5.0_3.0_1725256998602.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_korean_pipeline_ko_5.5.0_3.0_1725256998602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_vit_base_patch32_korean_pipeline", lang = "ko") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_vit_base_patch32_korean_pipeline", lang = "ko") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patch32_korean_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ko| +|Size:|449.1 MB| + +## References + +https://huggingface.co/Bingsu/clip-vit-base-patch32-ko + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patche32_demo_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patche32_demo_en.md new file mode 100644 index 00000000000000..418064ef6dbb47 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patche32_demo_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_base_patche32_demo CLIPForZeroShotClassification from nhatpth +author: John Snow Labs +name: clip_vit_base_patche32_demo +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patche32_demo` is a English model originally trained by nhatpth. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patche32_demo_en_5.5.0_3.0_1725256498558.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patche32_demo_en_5.5.0_3.0_1725256498558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patche32_demo","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patche32_demo","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patche32_demo| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/nhatpth/clip-vit-base-patche32-demo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patche32_demo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patche32_demo_pipeline_en.md new file mode 100644 index 00000000000000..6d42a45716f267 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patche32_demo_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_vit_base_patche32_demo_pipeline pipeline CLIPForZeroShotClassification from nhatpth +author: John Snow Labs +name: clip_vit_base_patche32_demo_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patche32_demo_pipeline` is a English model originally trained by nhatpth. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patche32_demo_pipeline_en_5.5.0_3.0_1725256597591.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patche32_demo_pipeline_en_5.5.0_3.0_1725256597591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_vit_base_patche32_demo_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_vit_base_patche32_demo_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_base_patche32_demo_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/nhatpth/clip-vit-base-patche32-demo + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_en.md new file mode 100644 index 00000000000000..f82a7adad0a1f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_l_14_datacomp_xl_s13b_b90k_aixile CLIPForZeroShotClassification from Aixile +author: John Snow Labs +name: clip_vit_l_14_datacomp_xl_s13b_b90k_aixile +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_l_14_datacomp_xl_s13b_b90k_aixile` is a English model originally trained by Aixile. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_en_5.5.0_3.0_1725276176265.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_en_5.5.0_3.0_1725276176265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_l_14_datacomp_xl_s13b_b90k_aixile","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_l_14_datacomp_xl_s13b_b90k_aixile","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_l_14_datacomp_xl_s13b_b90k_aixile| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/Aixile/CLIP-ViT-L-14-DataComp.XL-s13B-b90K \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_pipeline_en.md new file mode 100644 index 00000000000000..924bc47ac9a3da --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_pipeline pipeline CLIPForZeroShotClassification from Aixile +author: John Snow Labs +name: clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_pipeline` is a English model originally trained by Aixile. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_pipeline_en_5.5.0_3.0_1725276263511.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_pipeline_en_5.5.0_3.0_1725276263511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_l_14_datacomp_xl_s13b_b90k_aixile_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/Aixile/CLIP-ViT-L-14-DataComp.XL-s13B-b90K + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_large_patch14_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_large_patch14_finetuned_en.md new file mode 100644 index 00000000000000..878e29216656ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_large_patch14_finetuned_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_large_patch14_finetuned CLIPForZeroShotClassification from vinluvie +author: John Snow Labs +name: clip_vit_large_patch14_finetuned +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_finetuned` is a English model originally trained by vinluvie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_finetuned_en_5.5.0_3.0_1725275254849.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_finetuned_en_5.5.0_3.0_1725275254849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_finetuned","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_finetuned","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_large_patch14_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/vinluvie/clip-vit-large-patch14-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_large_patch14_rbanfield_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_large_patch14_rbanfield_en.md new file mode 100644 index 00000000000000..87e096fc4a1455 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_large_patch14_rbanfield_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_large_patch14_rbanfield CLIPForZeroShotClassification from rbanfield +author: John Snow Labs +name: clip_vit_large_patch14_rbanfield +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_rbanfield` is a English model originally trained by rbanfield. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_rbanfield_en_5.5.0_3.0_1725256911923.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_rbanfield_en_5.5.0_3.0_1725256911923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_rbanfield","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_rbanfield","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_large_patch14_rbanfield| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/rbanfield/clip-vit-large-patch14 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_large_patch14_rbanfield_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_large_patch14_rbanfield_pipeline_en.md new file mode 100644 index 00000000000000..c96d634fbc62fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_large_patch14_rbanfield_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_vit_large_patch14_rbanfield_pipeline pipeline CLIPForZeroShotClassification from rbanfield +author: John Snow Labs +name: clip_vit_large_patch14_rbanfield_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_rbanfield_pipeline` is a English model originally trained by rbanfield. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_rbanfield_pipeline_en_5.5.0_3.0_1725257204247.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_rbanfield_pipeline_en_5.5.0_3.0_1725257204247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_vit_large_patch14_rbanfield_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_vit_large_patch14_rbanfield_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_large_patch14_rbanfield_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/rbanfield/clip-vit-large-patch14 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_zabir_3_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_zabir_3_en.md new file mode 100644 index 00000000000000..916af4c8576860 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_zabir_3_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_zabir_3 CLIPForZeroShotClassification from zabir735 +author: John Snow Labs +name: clip_zabir_3 +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_zabir_3` is a English model originally trained by zabir735. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_zabir_3_en_5.5.0_3.0_1725257650004.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_zabir_3_en_5.5.0_3.0_1725257650004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_zabir_3","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_zabir_3","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_zabir_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|561.2 MB| + +## References + +https://huggingface.co/zabir735/clip-zabir-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_zabir_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_zabir_3_pipeline_en.md new file mode 100644 index 00000000000000..9597d20ce698cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-clip_zabir_3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_zabir_3_pipeline pipeline CLIPForZeroShotClassification from zabir735 +author: John Snow Labs +name: clip_zabir_3_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_zabir_3_pipeline` is a English model originally trained by zabir735. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_zabir_3_pipeline_en_5.5.0_3.0_1725257679504.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_zabir_3_pipeline_en_5.5.0_3.0_1725257679504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_zabir_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_zabir_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_zabir_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|561.2 MB| + +## References + +https://huggingface.co/zabir735/clip-zabir-3 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-column_model_en.md b/docs/_posts/ahmedlone127/2024-09-02-column_model_en.md new file mode 100644 index 00000000000000..626d656efee55d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-column_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English column_model DistilBertForSequenceClassification from coggpt +author: John Snow Labs +name: column_model +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`column_model` is a English model originally trained by coggpt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/column_model_en_5.5.0_3.0_1725305564583.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/column_model_en_5.5.0_3.0_1725305564583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("column_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("column_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|column_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/coggpt/column_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-column_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-column_model_pipeline_en.md new file mode 100644 index 00000000000000..76d91366ce5b1e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-column_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English column_model_pipeline pipeline DistilBertForSequenceClassification from coggpt +author: John Snow Labs +name: column_model_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`column_model_pipeline` is a English model originally trained by coggpt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/column_model_pipeline_en_5.5.0_3.0_1725305576874.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/column_model_pipeline_en_5.5.0_3.0_1725305576874.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("column_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("column_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|column_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/coggpt/column_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-commitments_classification_model_en.md b/docs/_posts/ahmedlone127/2024-09-02-commitments_classification_model_en.md new file mode 100644 index 00000000000000..86296f71b55fd8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-commitments_classification_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English commitments_classification_model RoBertaForSequenceClassification from nkc98 +author: John Snow Labs +name: commitments_classification_model +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`commitments_classification_model` is a English model originally trained by nkc98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/commitments_classification_model_en_5.5.0_3.0_1725238037904.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/commitments_classification_model_en_5.5.0_3.0_1725238037904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("commitments_classification_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("commitments_classification_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|commitments_classification_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|309.6 MB| + +## References + +https://huggingface.co/nkc98/commitments-classification-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-commitments_classification_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-commitments_classification_model_pipeline_en.md new file mode 100644 index 00000000000000..bbfad90d2b781e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-commitments_classification_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English commitments_classification_model_pipeline pipeline RoBertaForSequenceClassification from nkc98 +author: John Snow Labs +name: commitments_classification_model_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`commitments_classification_model_pipeline` is a English model originally trained by nkc98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/commitments_classification_model_pipeline_en_5.5.0_3.0_1725238054025.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/commitments_classification_model_pipeline_en_5.5.0_3.0_1725238054025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("commitments_classification_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("commitments_classification_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|commitments_classification_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|309.7 MB| + +## References + +https://huggingface.co/nkc98/commitments-classification-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_en.md b/docs/_posts/ahmedlone127/2024-09-02-cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_en.md new file mode 100644 index 00000000000000..33b0238e930470 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average MPNetEmbeddings from teven +author: John Snow Labs +name: cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average` is a English model originally trained by teven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_en_5.5.0_3.0_1725280714610.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_en_5.5.0_3.0_1725280714610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/teven/cross_all_bs192_hardneg_finetuned_WebNLG2020_metric_average \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_pipeline_en.md new file mode 100644 index 00000000000000..586c54ee0fd638 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_pipeline pipeline MPNetEmbeddings from teven +author: John Snow Labs +name: cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_pipeline` is a English model originally trained by teven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_pipeline_en_5.5.0_3.0_1725280742644.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_pipeline_en_5.5.0_3.0_1725280742644.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cross_all_bs192_hardneg_finetuned_webnlg2020_metric_average_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/teven/cross_all_bs192_hardneg_finetuned_WebNLG2020_metric_average + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-crossencoder_camembert_l6_mmarcofr_fr.md b/docs/_posts/ahmedlone127/2024-09-02-crossencoder_camembert_l6_mmarcofr_fr.md new file mode 100644 index 00000000000000..c65914ac0f8997 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-crossencoder_camembert_l6_mmarcofr_fr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: French crossencoder_camembert_l6_mmarcofr CamemBertForSequenceClassification from antoinelouis +author: John Snow Labs +name: crossencoder_camembert_l6_mmarcofr +date: 2024-09-02 +tags: [fr, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_camembert_l6_mmarcofr` is a French model originally trained by antoinelouis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l6_mmarcofr_fr_5.5.0_3.0_1725299117949.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l6_mmarcofr_fr_5.5.0_3.0_1725299117949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("crossencoder_camembert_l6_mmarcofr","fr") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("crossencoder_camembert_l6_mmarcofr", "fr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|crossencoder_camembert_l6_mmarcofr| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|fr| +|Size:|255.3 MB| + +## References + +https://huggingface.co/antoinelouis/crossencoder-camembert-L6-mmarcoFR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-crossencoder_camembert_l8_mmarcofr_fr.md b/docs/_posts/ahmedlone127/2024-09-02-crossencoder_camembert_l8_mmarcofr_fr.md new file mode 100644 index 00000000000000..e9357d822d0e25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-crossencoder_camembert_l8_mmarcofr_fr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: French crossencoder_camembert_l8_mmarcofr CamemBertForSequenceClassification from antoinelouis +author: John Snow Labs +name: crossencoder_camembert_l8_mmarcofr +date: 2024-09-02 +tags: [fr, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_camembert_l8_mmarcofr` is a French model originally trained by antoinelouis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l8_mmarcofr_fr_5.5.0_3.0_1725298313848.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l8_mmarcofr_fr_5.5.0_3.0_1725298313848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("crossencoder_camembert_l8_mmarcofr","fr") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("crossencoder_camembert_l8_mmarcofr", "fr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|crossencoder_camembert_l8_mmarcofr| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|fr| +|Size:|308.5 MB| + +## References + +https://huggingface.co/antoinelouis/crossencoder-camembert-L8-mmarcoFR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-crossencoder_camembert_l8_mmarcofr_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-crossencoder_camembert_l8_mmarcofr_pipeline_fr.md new file mode 100644 index 00000000000000..909a11f1e5c75f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-crossencoder_camembert_l8_mmarcofr_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French crossencoder_camembert_l8_mmarcofr_pipeline pipeline CamemBertForSequenceClassification from antoinelouis +author: John Snow Labs +name: crossencoder_camembert_l8_mmarcofr_pipeline +date: 2024-09-02 +tags: [fr, open_source, pipeline, onnx] +task: Text Classification +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_camembert_l8_mmarcofr_pipeline` is a French model originally trained by antoinelouis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l8_mmarcofr_pipeline_fr_5.5.0_3.0_1725298329326.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l8_mmarcofr_pipeline_fr_5.5.0_3.0_1725298329326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("crossencoder_camembert_l8_mmarcofr_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("crossencoder_camembert_l8_mmarcofr_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|crossencoder_camembert_l8_mmarcofr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|308.5 MB| + +## References + +https://huggingface.co/antoinelouis/crossencoder-camembert-L8-mmarcoFR + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ct_kld_mdeberta_idkmrc_en.md b/docs/_posts/ahmedlone127/2024-09-02-ct_kld_mdeberta_idkmrc_en.md new file mode 100644 index 00000000000000..67debd5e65ec92 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ct_kld_mdeberta_idkmrc_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English ct_kld_mdeberta_idkmrc DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_kld_mdeberta_idkmrc +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_kld_mdeberta_idkmrc` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_kld_mdeberta_idkmrc_en_5.5.0_3.0_1725239361639.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_kld_mdeberta_idkmrc_en_5.5.0_3.0_1725239361639.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_kld_mdeberta_idkmrc","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_kld_mdeberta_idkmrc", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_kld_mdeberta_idkmrc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|867.7 MB| + +## References + +https://huggingface.co/intanm/ct-kld-mdeberta-idkmrc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ct_kld_mdeberta_idkmrc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ct_kld_mdeberta_idkmrc_pipeline_en.md new file mode 100644 index 00000000000000..582f1fd22ac76b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ct_kld_mdeberta_idkmrc_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ct_kld_mdeberta_idkmrc_pipeline pipeline DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_kld_mdeberta_idkmrc_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_kld_mdeberta_idkmrc_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_kld_mdeberta_idkmrc_pipeline_en_5.5.0_3.0_1725239462806.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_kld_mdeberta_idkmrc_pipeline_en_5.5.0_3.0_1725239462806.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ct_kld_mdeberta_idkmrc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ct_kld_mdeberta_idkmrc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_kld_mdeberta_idkmrc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|867.7 MB| + +## References + +https://huggingface.co/intanm/ct-kld-mdeberta-idkmrc + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ct_kld_mdeberta_webis_en.md b/docs/_posts/ahmedlone127/2024-09-02-ct_kld_mdeberta_webis_en.md new file mode 100644 index 00000000000000..ff944a3d31d9df --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ct_kld_mdeberta_webis_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English ct_kld_mdeberta_webis DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_kld_mdeberta_webis +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_kld_mdeberta_webis` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_kld_mdeberta_webis_en_5.5.0_3.0_1725240545552.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_kld_mdeberta_webis_en_5.5.0_3.0_1725240545552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_kld_mdeberta_webis","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_kld_mdeberta_webis", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_kld_mdeberta_webis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|841.9 MB| + +## References + +https://huggingface.co/intanm/ct-kld-mdeberta-webis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ct_kld_mdeberta_webis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ct_kld_mdeberta_webis_pipeline_en.md new file mode 100644 index 00000000000000..d948b60638605b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ct_kld_mdeberta_webis_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ct_kld_mdeberta_webis_pipeline pipeline DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_kld_mdeberta_webis_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_kld_mdeberta_webis_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_kld_mdeberta_webis_pipeline_en_5.5.0_3.0_1725240659804.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_kld_mdeberta_webis_pipeline_en_5.5.0_3.0_1725240659804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ct_kld_mdeberta_webis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ct_kld_mdeberta_webis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_kld_mdeberta_webis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|841.9 MB| + +## References + +https://huggingface.co/intanm/ct-kld-mdeberta-webis + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ct_kld_xlmr_20230912_1_en.md b/docs/_posts/ahmedlone127/2024-09-02-ct_kld_xlmr_20230912_1_en.md new file mode 100644 index 00000000000000..b14a0bb1d61703 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ct_kld_xlmr_20230912_1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English ct_kld_xlmr_20230912_1 XlmRoBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_kld_xlmr_20230912_1 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_kld_xlmr_20230912_1` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_kld_xlmr_20230912_1_en_5.5.0_3.0_1725254552629.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_kld_xlmr_20230912_1_en_5.5.0_3.0_1725254552629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_kld_xlmr_20230912_1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_kld_xlmr_20230912_1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_kld_xlmr_20230912_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|876.1 MB| + +## References + +https://huggingface.co/intanm/ct-kld-xlmr-20230912-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ct_kld_xlmr_20230912_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ct_kld_xlmr_20230912_1_pipeline_en.md new file mode 100644 index 00000000000000..fe49fa2330d5c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ct_kld_xlmr_20230912_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ct_kld_xlmr_20230912_1_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_kld_xlmr_20230912_1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_kld_xlmr_20230912_1_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_kld_xlmr_20230912_1_pipeline_en_5.5.0_3.0_1725254621679.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_kld_xlmr_20230912_1_pipeline_en_5.5.0_3.0_1725254621679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ct_kld_xlmr_20230912_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ct_kld_xlmr_20230912_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_kld_xlmr_20230912_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|876.1 MB| + +## References + +https://huggingface.co/intanm/ct-kld-xlmr-20230912-1 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ct_mse_mdeberta_idkmrc_en.md b/docs/_posts/ahmedlone127/2024-09-02-ct_mse_mdeberta_idkmrc_en.md new file mode 100644 index 00000000000000..c069469e209e13 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ct_mse_mdeberta_idkmrc_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English ct_mse_mdeberta_idkmrc DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_mse_mdeberta_idkmrc +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_mse_mdeberta_idkmrc` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_mse_mdeberta_idkmrc_en_5.5.0_3.0_1725239552435.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_mse_mdeberta_idkmrc_en_5.5.0_3.0_1725239552435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_mse_mdeberta_idkmrc","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("ct_mse_mdeberta_idkmrc", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_mse_mdeberta_idkmrc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|867.7 MB| + +## References + +https://huggingface.co/intanm/ct-mse-mdeberta-idkmrc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ct_mse_mdeberta_idkmrc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ct_mse_mdeberta_idkmrc_pipeline_en.md new file mode 100644 index 00000000000000..cfef789dad3e29 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ct_mse_mdeberta_idkmrc_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ct_mse_mdeberta_idkmrc_pipeline pipeline DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_mse_mdeberta_idkmrc_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_mse_mdeberta_idkmrc_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_mse_mdeberta_idkmrc_pipeline_en_5.5.0_3.0_1725239656620.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_mse_mdeberta_idkmrc_pipeline_en_5.5.0_3.0_1725239656620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ct_mse_mdeberta_idkmrc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ct_mse_mdeberta_idkmrc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_mse_mdeberta_idkmrc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|867.7 MB| + +## References + +https://huggingface.co/intanm/ct-mse-mdeberta-idkmrc + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ct_mse_xlmr_squadv2_en.md b/docs/_posts/ahmedlone127/2024-09-02-ct_mse_xlmr_squadv2_en.md new file mode 100644 index 00000000000000..f1e8d201f1e932 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ct_mse_xlmr_squadv2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English ct_mse_xlmr_squadv2 XlmRoBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_mse_xlmr_squadv2 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_mse_xlmr_squadv2` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_mse_xlmr_squadv2_en_5.5.0_3.0_1725235670550.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_mse_xlmr_squadv2_en_5.5.0_3.0_1725235670550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_mse_xlmr_squadv2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_mse_xlmr_squadv2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_mse_xlmr_squadv2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|876.0 MB| + +## References + +https://huggingface.co/intanm/ct-mse-xlmr-squadv2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ct_mse_xlmr_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ct_mse_xlmr_squadv2_pipeline_en.md new file mode 100644 index 00000000000000..7f1dd3f45d27b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ct_mse_xlmr_squadv2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ct_mse_xlmr_squadv2_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm +author: John Snow Labs +name: ct_mse_xlmr_squadv2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_mse_xlmr_squadv2_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_mse_xlmr_squadv2_pipeline_en_5.5.0_3.0_1725235742545.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_mse_xlmr_squadv2_pipeline_en_5.5.0_3.0_1725235742545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ct_mse_xlmr_squadv2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ct_mse_xlmr_squadv2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ct_mse_xlmr_squadv2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|876.0 MB| + +## References + +https://huggingface.co/intanm/ct-mse-xlmr-squadv2 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-cuad_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-02-cuad_roberta_base_en.md new file mode 100644 index 00000000000000..edb9815316e43a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-cuad_roberta_base_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English cuad_roberta_base RoBertaForQuestionAnswering from kallam +author: John Snow Labs +name: cuad_roberta_base +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cuad_roberta_base` is a English model originally trained by kallam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cuad_roberta_base_en_5.5.0_3.0_1725252199283.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cuad_roberta_base_en_5.5.0_3.0_1725252199283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("cuad_roberta_base","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("cuad_roberta_base", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cuad_roberta_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|447.4 MB| + +## References + +https://huggingface.co/kallam/cuad_roberta_base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-cuad_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-cuad_roberta_base_pipeline_en.md new file mode 100644 index 00000000000000..0d67edf93e2914 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-cuad_roberta_base_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English cuad_roberta_base_pipeline pipeline RoBertaForQuestionAnswering from kallam +author: John Snow Labs +name: cuad_roberta_base_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cuad_roberta_base_pipeline` is a English model originally trained by kallam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cuad_roberta_base_pipeline_en_5.5.0_3.0_1725252232603.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cuad_roberta_base_pipeline_en_5.5.0_3.0_1725252232603.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cuad_roberta_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cuad_roberta_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cuad_roberta_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|447.4 MB| + +## References + +https://huggingface.co/kallam/cuad_roberta_base + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-darija_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-darija_tonga_tonga_islands_english_en.md new file mode 100644 index 00000000000000..653d052ac0c6dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-darija_tonga_tonga_islands_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English darija_tonga_tonga_islands_english MarianTransformer from centino00 +author: John Snow Labs +name: darija_tonga_tonga_islands_english +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darija_tonga_tonga_islands_english` is a English model originally trained by centino00. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darija_tonga_tonga_islands_english_en_5.5.0_3.0_1725294441511.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darija_tonga_tonga_islands_english_en_5.5.0_3.0_1725294441511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("darija_tonga_tonga_islands_english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("darija_tonga_tonga_islands_english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|darija_tonga_tonga_islands_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|527.6 MB| + +## References + +https://huggingface.co/centino00/darija-to-english \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-darija_tonga_tonga_islands_english_full_en.md b/docs/_posts/ahmedlone127/2024-09-02-darija_tonga_tonga_islands_english_full_en.md new file mode 100644 index 00000000000000..92b659fb06516f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-darija_tonga_tonga_islands_english_full_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English darija_tonga_tonga_islands_english_full MarianTransformer from centino00 +author: John Snow Labs +name: darija_tonga_tonga_islands_english_full +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darija_tonga_tonga_islands_english_full` is a English model originally trained by centino00. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darija_tonga_tonga_islands_english_full_en_5.5.0_3.0_1725295993536.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darija_tonga_tonga_islands_english_full_en_5.5.0_3.0_1725295993536.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("darija_tonga_tonga_islands_english_full","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("darija_tonga_tonga_islands_english_full","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|darija_tonga_tonga_islands_english_full| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|503.8 MB| + +## References + +https://huggingface.co/centino00/darija-to-english-full \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-darija_tonga_tonga_islands_english_full_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-darija_tonga_tonga_islands_english_full_pipeline_en.md new file mode 100644 index 00000000000000..b214acd2f0c6bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-darija_tonga_tonga_islands_english_full_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English darija_tonga_tonga_islands_english_full_pipeline pipeline MarianTransformer from centino00 +author: John Snow Labs +name: darija_tonga_tonga_islands_english_full_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darija_tonga_tonga_islands_english_full_pipeline` is a English model originally trained by centino00. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darija_tonga_tonga_islands_english_full_pipeline_en_5.5.0_3.0_1725296024259.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darija_tonga_tonga_islands_english_full_pipeline_en_5.5.0_3.0_1725296024259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("darija_tonga_tonga_islands_english_full_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("darija_tonga_tonga_islands_english_full_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|darija_tonga_tonga_islands_english_full_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|504.4 MB| + +## References + +https://huggingface.co/centino00/darija-to-english-full + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-darija_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-darija_tonga_tonga_islands_english_pipeline_en.md new file mode 100644 index 00000000000000..9f7f99dd15a508 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-darija_tonga_tonga_islands_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English darija_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from centino00 +author: John Snow Labs +name: darija_tonga_tonga_islands_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darija_tonga_tonga_islands_english_pipeline` is a English model originally trained by centino00. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darija_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725294483394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darija_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725294483394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("darija_tonga_tonga_islands_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("darija_tonga_tonga_islands_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|darija_tonga_tonga_islands_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|528.1 MB| + +## References + +https://huggingface.co/centino00/darija-to-english + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-das22_10_camembert_pretrained_en.md b/docs/_posts/ahmedlone127/2024-09-02-das22_10_camembert_pretrained_en.md new file mode 100644 index 00000000000000..ea04dd75bd2b77 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-das22_10_camembert_pretrained_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English das22_10_camembert_pretrained CamemBertEmbeddings from HueyNemud +author: John Snow Labs +name: das22_10_camembert_pretrained +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`das22_10_camembert_pretrained` is a English model originally trained by HueyNemud. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/das22_10_camembert_pretrained_en_5.5.0_3.0_1725320278521.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/das22_10_camembert_pretrained_en_5.5.0_3.0_1725320278521.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("das22_10_camembert_pretrained","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("das22_10_camembert_pretrained","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|das22_10_camembert_pretrained| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|412.8 MB| + +## References + +https://huggingface.co/HueyNemud/das22-10-camembert_pretrained \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-datosw_v1_1_en.md b/docs/_posts/ahmedlone127/2024-09-02-datosw_v1_1_en.md new file mode 100644 index 00000000000000..4654834f917ada --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-datosw_v1_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English datosw_v1_1 MarianTransformer from ZcepZtar +author: John Snow Labs +name: datosw_v1_1 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`datosw_v1_1` is a English model originally trained by ZcepZtar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/datosw_v1_1_en_5.5.0_3.0_1725304930981.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/datosw_v1_1_en_5.5.0_3.0_1725304930981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("datosw_v1_1","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("datosw_v1_1","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|datosw_v1_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|504.4 MB| + +## References + +https://huggingface.co/ZcepZtar/DaToSw_V1.1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-datosw_v1_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-datosw_v1_1_pipeline_en.md new file mode 100644 index 00000000000000..6143414dc43d51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-datosw_v1_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English datosw_v1_1_pipeline pipeline MarianTransformer from ZcepZtar +author: John Snow Labs +name: datosw_v1_1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`datosw_v1_1_pipeline` is a English model originally trained by ZcepZtar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/datosw_v1_1_pipeline_en_5.5.0_3.0_1725304958261.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/datosw_v1_1_pipeline_en_5.5.0_3.0_1725304958261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("datosw_v1_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("datosw_v1_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|datosw_v1_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|504.9 MB| + +## References + +https://huggingface.co/ZcepZtar/DaToSw_V1.1 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dbg_myriade_10k_mots_all_sens_multilabel_3phrases_en.md b/docs/_posts/ahmedlone127/2024-09-02-dbg_myriade_10k_mots_all_sens_multilabel_3phrases_en.md new file mode 100644 index 00000000000000..01940ccbfb8e5b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dbg_myriade_10k_mots_all_sens_multilabel_3phrases_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dbg_myriade_10k_mots_all_sens_multilabel_3phrases CamemBertForTokenClassification from Easter-Island +author: John Snow Labs +name: dbg_myriade_10k_mots_all_sens_multilabel_3phrases +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, camembert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbg_myriade_10k_mots_all_sens_multilabel_3phrases` is a English model originally trained by Easter-Island. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dbg_myriade_10k_mots_all_sens_multilabel_3phrases_en_5.5.0_3.0_1725266881093.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbg_myriade_10k_mots_all_sens_multilabel_3phrases_en_5.5.0_3.0_1725266881093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = CamemBertForTokenClassification.pretrained("dbg_myriade_10k_mots_all_sens_multilabel_3phrases","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = CamemBertForTokenClassification.pretrained("dbg_myriade_10k_mots_all_sens_multilabel_3phrases", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dbg_myriade_10k_mots_all_sens_multilabel_3phrases| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Easter-Island/dbg_myriade_10k_mots_all_sens_multilabel_3phrases \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deadloack_model_en.md b/docs/_posts/ahmedlone127/2024-09-02-deadloack_model_en.md new file mode 100644 index 00000000000000..6c376ca89b11c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deadloack_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deadloack_model RoBertaForSequenceClassification from moazx +author: John Snow Labs +name: deadloack_model +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deadloack_model` is a English model originally trained by moazx. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deadloack_model_en_5.5.0_3.0_1725277532101.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deadloack_model_en_5.5.0_3.0_1725277532101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("deadloack_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("deadloack_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deadloack_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/moazx/deadloack_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deadloack_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deadloack_model_pipeline_en.md new file mode 100644 index 00000000000000..18722180db1840 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deadloack_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deadloack_model_pipeline pipeline RoBertaForSequenceClassification from moazx +author: John Snow Labs +name: deadloack_model_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deadloack_model_pipeline` is a English model originally trained by moazx. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deadloack_model_pipeline_en_5.5.0_3.0_1725277556895.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deadloack_model_pipeline_en_5.5.0_3.0_1725277556895.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deadloack_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deadloack_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deadloack_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.4 MB| + +## References + +https://huggingface.co/moazx/deadloack_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_amazon_reviews_v1_michael_karoo_ai_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_amazon_reviews_v1_michael_karoo_ai_en.md new file mode 100644 index 00000000000000..18cf1beae972d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_amazon_reviews_v1_michael_karoo_ai_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_amazon_reviews_v1_michael_karoo_ai DeBertaForSequenceClassification from michael-karoo-ai +author: John Snow Labs +name: deberta_amazon_reviews_v1_michael_karoo_ai +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_amazon_reviews_v1_michael_karoo_ai` is a English model originally trained by michael-karoo-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v1_michael_karoo_ai_en_5.5.0_3.0_1725282965369.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v1_michael_karoo_ai_en_5.5.0_3.0_1725282965369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_amazon_reviews_v1_michael_karoo_ai","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_amazon_reviews_v1_michael_karoo_ai", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_amazon_reviews_v1_michael_karoo_ai| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|594.6 MB| + +## References + +https://huggingface.co/michael-karoo-ai/deberta_amazon_reviews_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_amazon_reviews_v1_michael_karoo_ai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_amazon_reviews_v1_michael_karoo_ai_pipeline_en.md new file mode 100644 index 00000000000000..9e2f4ab24c4a5e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_amazon_reviews_v1_michael_karoo_ai_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_amazon_reviews_v1_michael_karoo_ai_pipeline pipeline DeBertaForSequenceClassification from michael-karoo-ai +author: John Snow Labs +name: deberta_amazon_reviews_v1_michael_karoo_ai_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_amazon_reviews_v1_michael_karoo_ai_pipeline` is a English model originally trained by michael-karoo-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v1_michael_karoo_ai_pipeline_en_5.5.0_3.0_1725283035326.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v1_michael_karoo_ai_pipeline_en_5.5.0_3.0_1725283035326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_amazon_reviews_v1_michael_karoo_ai_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_amazon_reviews_v1_michael_karoo_ai_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_amazon_reviews_v1_michael_karoo_ai_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|594.6 MB| + +## References + +https://huggingface.co/michael-karoo-ai/deberta_amazon_reviews_v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_base_multi_label_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_base_multi_label_classifier_en.md new file mode 100644 index 00000000000000..b62432c4b82da8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_base_multi_label_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_base_multi_label_classifier DeBertaForSequenceClassification from Azma-AI +author: John Snow Labs +name: deberta_base_multi_label_classifier +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_base_multi_label_classifier` is a English model originally trained by Azma-AI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_base_multi_label_classifier_en_5.5.0_3.0_1725281735348.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_base_multi_label_classifier_en_5.5.0_3.0_1725281735348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_base_multi_label_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_base_multi_label_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_base_multi_label_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|688.9 MB| + +## References + +https://huggingface.co/Azma-AI/deberta-base-multi-label-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_base_multi_label_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_base_multi_label_classifier_pipeline_en.md new file mode 100644 index 00000000000000..8dc0169a8c2b9e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_base_multi_label_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_base_multi_label_classifier_pipeline pipeline DeBertaForSequenceClassification from Azma-AI +author: John Snow Labs +name: deberta_base_multi_label_classifier_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_base_multi_label_classifier_pipeline` is a English model originally trained by Azma-AI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_base_multi_label_classifier_pipeline_en_5.5.0_3.0_1725281772532.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_base_multi_label_classifier_pipeline_en_5.5.0_3.0_1725281772532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_base_multi_label_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_base_multi_label_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_base_multi_label_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|688.9 MB| + +## References + +https://huggingface.co/Azma-AI/deberta-base-multi-label-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_embeddings_m5_mlm_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_embeddings_m5_mlm_en.md new file mode 100644 index 00000000000000..9836b520c91fad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_embeddings_m5_mlm_en.md @@ -0,0 +1,100 @@ +--- +layout: model +title: English Deberta Embeddings model (from S2312dal) +author: John Snow Labs +name: deberta_embeddings_m5_mlm +date: 2024-09-02 +tags: [deberta, open_source, deberta_embeddings, debertav2formaskedlm, en, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DebertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `M5_MLM` is a English model originally trained by `S2312dal`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_m5_mlm_en_5.5.0_3.0_1725261092487.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_m5_mlm_en_5.5.0_3.0_1725261092487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_m5_mlm","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") \ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings]) + +data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_m5_mlm","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) + +val data = Seq("I love Spark NLP").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_m5_mlm| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|689.7 MB| + +## References + +References + +https://huggingface.co/S2312dal/M5_MLM \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_embeddings_m5_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_embeddings_m5_mlm_pipeline_en.md new file mode 100644 index 00000000000000..d2b08972ffb7ef --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_embeddings_m5_mlm_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_embeddings_m5_mlm_pipeline pipeline DeBertaEmbeddings from S2312dal +author: John Snow Labs +name: deberta_embeddings_m5_mlm_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_embeddings_m5_mlm_pipeline` is a English model originally trained by S2312dal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_m5_mlm_pipeline_en_5.5.0_3.0_1725261128263.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_m5_mlm_pipeline_en_5.5.0_3.0_1725261128263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_embeddings_m5_mlm_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_embeddings_m5_mlm_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_m5_mlm_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|689.7 MB| + +## References + +https://huggingface.co/S2312dal/M5_MLM + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_large_hallucination_eval_v3_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_large_hallucination_eval_v3_en.md new file mode 100644 index 00000000000000..c696eb7aa0359a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_large_hallucination_eval_v3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_large_hallucination_eval_v3 DeBertaForSequenceClassification from mathislucka +author: John Snow Labs +name: deberta_large_hallucination_eval_v3 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_large_hallucination_eval_v3` is a English model originally trained by mathislucka. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_large_hallucination_eval_v3_en_5.5.0_3.0_1725281707028.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_large_hallucination_eval_v3_en_5.5.0_3.0_1725281707028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_large_hallucination_eval_v3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_large_hallucination_eval_v3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_large_hallucination_eval_v3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/mathislucka/deberta-large-hallucination-eval-v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_large_hallucination_eval_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_large_hallucination_eval_v3_pipeline_en.md new file mode 100644 index 00000000000000..b6159f697c0748 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_large_hallucination_eval_v3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_large_hallucination_eval_v3_pipeline pipeline DeBertaForSequenceClassification from mathislucka +author: John Snow Labs +name: deberta_large_hallucination_eval_v3_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_large_hallucination_eval_v3_pipeline` is a English model originally trained by mathislucka. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_large_hallucination_eval_v3_pipeline_en_5.5.0_3.0_1725281789178.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_large_hallucination_eval_v3_pipeline_en_5.5.0_3.0_1725281789178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_large_hallucination_eval_v3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_large_hallucination_eval_v3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_large_hallucination_eval_v3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/mathislucka/deberta-large-hallucination-eval-v3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_question_answering_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_question_answering_en.md new file mode 100644 index 00000000000000..f9005a1958a780 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_question_answering_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_question_answering DeBertaForQuestionAnswering from seenuvasanfoss +author: John Snow Labs +name: deberta_question_answering +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_question_answering` is a English model originally trained by seenuvasanfoss. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_question_answering_en_5.5.0_3.0_1725240150294.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_question_answering_en_5.5.0_3.0_1725240150294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_question_answering","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_question_answering", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_question_answering| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/seenuvasanfoss/deberta_question_answering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_question_answering_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_question_answering_pipeline_en.md new file mode 100644 index 00000000000000..e1601ee5870686 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_question_answering_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_question_answering_pipeline pipeline DeBertaForQuestionAnswering from seenuvasanfoss +author: John Snow Labs +name: deberta_question_answering_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_question_answering_pipeline` is a English model originally trained by seenuvasanfoss. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_question_answering_pipeline_en_5.5.0_3.0_1725240251547.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_question_answering_pipeline_en_5.5.0_3.0_1725240251547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_question_answering_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_question_answering_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_question_answering_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/seenuvasanfoss/deberta_question_answering + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v2_tiny_japanese_ja.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v2_tiny_japanese_ja.md new file mode 100644 index 00000000000000..1d0a4ce910dc6e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v2_tiny_japanese_ja.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Japanese deberta_v2_tiny_japanese DeBertaEmbeddings from ku-nlp +author: John Snow Labs +name: deberta_v2_tiny_japanese +date: 2024-09-02 +tags: [ja, open_source, onnx, embeddings, deberta] +task: Embeddings +language: ja +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_tiny_japanese` is a Japanese model originally trained by ku-nlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_tiny_japanese_ja_5.5.0_3.0_1725261105609.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_tiny_japanese_ja_5.5.0_3.0_1725261105609.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_v2_tiny_japanese","ja") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_v2_tiny_japanese","ja") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v2_tiny_japanese| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|ja| +|Size:|29.3 MB| + +## References + +https://huggingface.co/ku-nlp/deberta-v2-tiny-japanese \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v2_tiny_japanese_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v2_tiny_japanese_pipeline_ja.md new file mode 100644 index 00000000000000..86c2d11b5bfd02 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v2_tiny_japanese_pipeline_ja.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Japanese deberta_v2_tiny_japanese_pipeline pipeline DeBertaEmbeddings from ku-nlp +author: John Snow Labs +name: deberta_v2_tiny_japanese_pipeline +date: 2024-09-02 +tags: [ja, open_source, pipeline, onnx] +task: Embeddings +language: ja +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_tiny_japanese_pipeline` is a Japanese model originally trained by ku-nlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_tiny_japanese_pipeline_ja_5.5.0_3.0_1725261107407.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_tiny_japanese_pipeline_ja_5.5.0_3.0_1725261107407.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v2_tiny_japanese_pipeline", lang = "ja") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v2_tiny_japanese_pipeline", lang = "ja") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v2_tiny_japanese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ja| +|Size:|29.3 MB| + +## References + +https://huggingface.co/ku-nlp/deberta-v2-tiny-japanese + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_devrev_data_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_devrev_data_en.md new file mode 100644 index 00000000000000..e03d6f42705058 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_devrev_data_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_base_devrev_data DeBertaForQuestionAnswering from devpranjal +author: John Snow Labs +name: deberta_v3_base_devrev_data +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_devrev_data` is a English model originally trained by devpranjal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_devrev_data_en_5.5.0_3.0_1725269564725.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_devrev_data_en_5.5.0_3.0_1725269564725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_devrev_data","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_devrev_data", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_devrev_data| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|651.0 MB| + +## References + +https://huggingface.co/devpranjal/deberta-v3-base-devrev-data \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_devrev_data_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_devrev_data_pipeline_en.md new file mode 100644 index 00000000000000..7fafc11a58d2fa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_devrev_data_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_base_devrev_data_pipeline pipeline DeBertaForQuestionAnswering from devpranjal +author: John Snow Labs +name: deberta_v3_base_devrev_data_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_devrev_data_pipeline` is a English model originally trained by devpranjal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_devrev_data_pipeline_en_5.5.0_3.0_1725269610428.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_devrev_data_pipeline_en_5.5.0_3.0_1725269610428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_devrev_data_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_devrev_data_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_devrev_data_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|651.1 MB| + +## References + +https://huggingface.co/devpranjal/deberta-v3-base-devrev-data + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_domain_adapted_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_domain_adapted_en.md new file mode 100644 index 00000000000000..e8bdbb53e7dd5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_domain_adapted_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_base_domain_adapted DeBertaForQuestionAnswering from devpranjal +author: John Snow Labs +name: deberta_v3_base_domain_adapted +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_domain_adapted` is a English model originally trained by devpranjal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_domain_adapted_en_5.5.0_3.0_1725290887485.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_domain_adapted_en_5.5.0_3.0_1725290887485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_domain_adapted","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_domain_adapted", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_domain_adapted| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|651.0 MB| + +## References + +https://huggingface.co/devpranjal/deberta-v3-base-domain-adapted \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_domain_adapted_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_domain_adapted_pipeline_en.md new file mode 100644 index 00000000000000..6dff563c606869 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_domain_adapted_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_base_domain_adapted_pipeline pipeline DeBertaForQuestionAnswering from devpranjal +author: John Snow Labs +name: deberta_v3_base_domain_adapted_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_domain_adapted_pipeline` is a English model originally trained by devpranjal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_domain_adapted_pipeline_en_5.5.0_3.0_1725290931164.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_domain_adapted_pipeline_en_5.5.0_3.0_1725290931164.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_domain_adapted_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_domain_adapted_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_domain_adapted_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|651.1 MB| + +## References + +https://huggingface.co/devpranjal/deberta-v3-base-domain-adapted + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_en.md new file mode 100644 index 00000000000000..096271c857494e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_en.md @@ -0,0 +1,77 @@ +--- +layout: model +title: DeBERTa base model +author: John Snow Labs +name: deberta_v3_base +date: 2024-09-02 +tags: [en, english, open_source, embeddings, deberta, v3, base, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +The DeBERTa model was proposed in [[https://arxiv.org/abs/2006.03654 DeBERTa: Decoding-enhanced BERT with Disentangled Attention]] by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen It is based on Google’s BERT model released in 2018 and Facebook’s RoBERTa model released in 2019. Compared to RoBERTa-Large, a DeBERTa model trained on half of the training data performs consistently better on a wide range of NLP tasks, achieving improvements on MNLI by +0.9% (90.2% vs. 91.1%), on SQuAD v2.0 by +2.3% (88.4% vs. 90.7%) and RACE by +3.6% (83.2% vs. 86.8%). + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_en_5.5.0_3.0_1725261194036.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_en_5.5.0_3.0_1725261194036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +embeddings = DeBertaEmbeddings.pretrained("deberta_v3_base", "en") \ +.setInputCols("sentence", "token") \ +.setOutputCol("embeddings") +``` +```scala +val embeddings = DeBertaEmbeddings.pretrained("deberta_v3_base", "en") +.setInputCols("sentence", "token") +.setOutputCol("embeddings") +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.embed.deberta_v3_base").predict("""Put your text here.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|435.2 MB| + +## Benchmarking + +```bash + +Benchmarking +``` \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_finetuned_squad2_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_finetuned_squad2_en.md new file mode 100644 index 00000000000000..e8eec9285794b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_finetuned_squad2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_base_finetuned_squad2 DeBertaForQuestionAnswering from IProject-10 +author: John Snow Labs +name: deberta_v3_base_finetuned_squad2 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_squad2` is a English model originally trained by IProject-10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_squad2_en_5.5.0_3.0_1725240186393.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_squad2_en_5.5.0_3.0_1725240186393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_finetuned_squad2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_finetuned_squad2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_finetuned_squad2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|658.8 MB| + +## References + +https://huggingface.co/IProject-10/deberta-v3-base-finetuned-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_glue_mrpc_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_glue_mrpc_en.md new file mode 100644 index 00000000000000..f436dae162a149 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_glue_mrpc_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_glue_mrpc DeBertaForSequenceClassification from ficsort +author: John Snow Labs +name: deberta_v3_base_glue_mrpc +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_glue_mrpc` is a English model originally trained by ficsort. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_glue_mrpc_en_5.5.0_3.0_1725282777995.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_glue_mrpc_en_5.5.0_3.0_1725282777995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_glue_mrpc","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_glue_mrpc", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_glue_mrpc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|582.8 MB| + +## References + +https://huggingface.co/ficsort/deberta-v3-base-glue-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_glue_mrpc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_glue_mrpc_pipeline_en.md new file mode 100644 index 00000000000000..a1da08f63a75dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_glue_mrpc_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_glue_mrpc_pipeline pipeline DeBertaForSequenceClassification from ficsort +author: John Snow Labs +name: deberta_v3_base_glue_mrpc_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_glue_mrpc_pipeline` is a English model originally trained by ficsort. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_glue_mrpc_pipeline_en_5.5.0_3.0_1725282853506.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_glue_mrpc_pipeline_en_5.5.0_3.0_1725282853506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_glue_mrpc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_glue_mrpc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_glue_mrpc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|582.9 MB| + +## References + +https://huggingface.co/ficsort/deberta-v3-base-glue-mrpc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_glue_qnli_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_glue_qnli_en.md new file mode 100644 index 00000000000000..52dca605139c55 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_glue_qnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_glue_qnli DeBertaForSequenceClassification from ficsort +author: John Snow Labs +name: deberta_v3_base_glue_qnli +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_glue_qnli` is a English model originally trained by ficsort. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_glue_qnli_en_5.5.0_3.0_1725283607413.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_glue_qnli_en_5.5.0_3.0_1725283607413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_glue_qnli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_glue_qnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_glue_qnli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|642.9 MB| + +## References + +https://huggingface.co/ficsort/deberta-v3-base-glue-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_glue_qnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_glue_qnli_pipeline_en.md new file mode 100644 index 00000000000000..951aba3bbd4686 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_glue_qnli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_glue_qnli_pipeline pipeline DeBertaForSequenceClassification from ficsort +author: John Snow Labs +name: deberta_v3_base_glue_qnli_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_glue_qnli_pipeline` is a English model originally trained by ficsort. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_glue_qnli_pipeline_en_5.5.0_3.0_1725283656658.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_glue_qnli_pipeline_en_5.5.0_3.0_1725283656658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_glue_qnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_glue_qnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_glue_qnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|642.9 MB| + +## References + +https://huggingface.co/ficsort/deberta-v3-base-glue-qnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_injection_jasperls_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_injection_jasperls_en.md new file mode 100644 index 00000000000000..7cd4fcfe2480e3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_injection_jasperls_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_injection_jasperls DeBertaForSequenceClassification from JasperLS +author: John Snow Labs +name: deberta_v3_base_injection_jasperls +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_injection_jasperls` is a English model originally trained by JasperLS. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_injection_jasperls_en_5.5.0_3.0_1725282195871.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_injection_jasperls_en_5.5.0_3.0_1725282195871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_injection_jasperls","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_injection_jasperls", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_injection_jasperls| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|578.9 MB| + +## References + +https://huggingface.co/JasperLS/deberta-v3-base-injection \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_injection_jasperls_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_injection_jasperls_pipeline_en.md new file mode 100644 index 00000000000000..f69fa8b2bb9549 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_injection_jasperls_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_injection_jasperls_pipeline pipeline DeBertaForSequenceClassification from JasperLS +author: John Snow Labs +name: deberta_v3_base_injection_jasperls_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_injection_jasperls_pipeline` is a English model originally trained by JasperLS. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_injection_jasperls_pipeline_en_5.5.0_3.0_1725282246389.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_injection_jasperls_pipeline_en_5.5.0_3.0_1725282246389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_injection_jasperls_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_injection_jasperls_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_injection_jasperls_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|578.9 MB| + +## References + +https://huggingface.co/JasperLS/deberta-v3-base-injection + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_mnli_uf_ner_1019_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_mnli_uf_ner_1019_v1_pipeline_en.md new file mode 100644 index 00000000000000..fe0ff7d423bb38 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_mnli_uf_ner_1019_v1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_mnli_uf_ner_1019_v1_pipeline pipeline DeBertaForSequenceClassification from mariolinml +author: John Snow Labs +name: deberta_v3_base_mnli_uf_ner_1019_v1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_mnli_uf_ner_1019_v1_pipeline` is a English model originally trained by mariolinml. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mnli_uf_ner_1019_v1_pipeline_en_5.5.0_3.0_1725283238346.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mnli_uf_ner_1019_v1_pipeline_en_5.5.0_3.0_1725283238346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_mnli_uf_ner_1019_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_mnli_uf_ner_1019_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_mnli_uf_ner_1019_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|639.1 MB| + +## References + +https://huggingface.co/mariolinml/deberta-v3-base_mnli_uf_ner_1019_v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_pipeline_en.md new file mode 100644 index 00000000000000..2424f71b7692cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_pipeline pipeline DeBertaEmbeddings from microsoft +author: John Snow Labs +name: deberta_v3_base_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_pipeline` is a English model originally trained by microsoft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_pipeline_en_5.5.0_3.0_1725261324983.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_pipeline_en_5.5.0_3.0_1725261324983.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|435.2 MB| + +## References + +https://huggingface.co/microsoft/deberta-v3-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_reward_model_0112_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_reward_model_0112_en.md new file mode 100644 index 00000000000000..622d8e15473767 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_reward_model_0112_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_reward_model_0112 DeBertaForSequenceClassification from decem +author: John Snow Labs +name: deberta_v3_base_reward_model_0112 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_reward_model_0112` is a English model originally trained by decem. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_reward_model_0112_en_5.5.0_3.0_1725282545644.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_reward_model_0112_en_5.5.0_3.0_1725282545644.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_reward_model_0112","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_reward_model_0112", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_reward_model_0112| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|644.3 MB| + +## References + +https://huggingface.co/decem/deberta-v3-base-reward-model-0112 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_reward_model_0112_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_reward_model_0112_pipeline_en.md new file mode 100644 index 00000000000000..0674f73e4de50b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_reward_model_0112_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_reward_model_0112_pipeline pipeline DeBertaForSequenceClassification from decem +author: John Snow Labs +name: deberta_v3_base_reward_model_0112_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_reward_model_0112_pipeline` is a English model originally trained by decem. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_reward_model_0112_pipeline_en_5.5.0_3.0_1725282595841.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_reward_model_0112_pipeline_en_5.5.0_3.0_1725282595841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_reward_model_0112_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_reward_model_0112_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_reward_model_0112_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|644.3 MB| + +## References + +https://huggingface.co/decem/deberta-v3-base-reward-model-0112 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_deepset_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_deepset_en.md new file mode 100644 index 00000000000000..bdedc254e6043f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_deepset_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_base_squad2_deepset DeBertaForQuestionAnswering from deepset +author: John Snow Labs +name: deberta_v3_base_squad2_deepset +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_squad2_deepset` is a English model originally trained by deepset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_deepset_en_5.5.0_3.0_1725268762025.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_deepset_en_5.5.0_3.0_1725268762025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_squad2_deepset","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_squad2_deepset", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_squad2_deepset| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|651.0 MB| + +## References + +https://huggingface.co/deepset/deberta-v3-base-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_deepset_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_deepset_pipeline_en.md new file mode 100644 index 00000000000000..47cfcdef399a61 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_deepset_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_base_squad2_deepset_pipeline pipeline DeBertaForQuestionAnswering from deepset +author: John Snow Labs +name: deberta_v3_base_squad2_deepset_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_squad2_deepset_pipeline` is a English model originally trained by deepset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_deepset_pipeline_en_5.5.0_3.0_1725268816718.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_deepset_pipeline_en_5.5.0_3.0_1725268816718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_squad2_deepset_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_squad2_deepset_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_squad2_deepset_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|651.1 MB| + +## References + +https://huggingface.co/deepset/deberta-v3-base-squad2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_ext_v1_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_ext_v1_en.md new file mode 100644 index 00000000000000..42361b4feeb46b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_ext_v1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_base_squad2_ext_v1 DeBertaForQuestionAnswering from sjrhuschlee +author: John Snow Labs +name: deberta_v3_base_squad2_ext_v1 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_squad2_ext_v1` is a English model originally trained by sjrhuschlee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_ext_v1_en_5.5.0_3.0_1725268473300.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_ext_v1_en_5.5.0_3.0_1725268473300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_squad2_ext_v1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_squad2_ext_v1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_squad2_ext_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|686.9 MB| + +## References + +https://huggingface.co/sjrhuschlee/deberta-v3-base-squad2-ext-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_sjrhuschlee_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_sjrhuschlee_en.md new file mode 100644 index 00000000000000..40df81ec933b52 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_sjrhuschlee_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_base_squad2_sjrhuschlee DeBertaForQuestionAnswering from sjrhuschlee +author: John Snow Labs +name: deberta_v3_base_squad2_sjrhuschlee +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_squad2_sjrhuschlee` is a English model originally trained by sjrhuschlee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_sjrhuschlee_en_5.5.0_3.0_1725239072339.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_sjrhuschlee_en_5.5.0_3.0_1725239072339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_squad2_sjrhuschlee","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_base_squad2_sjrhuschlee", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_squad2_sjrhuschlee| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|645.3 MB| + +## References + +https://huggingface.co/sjrhuschlee/deberta-v3-base-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_sjrhuschlee_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_sjrhuschlee_pipeline_en.md new file mode 100644 index 00000000000000..9ad745c84a2e88 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_sjrhuschlee_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_base_squad2_sjrhuschlee_pipeline pipeline DeBertaForQuestionAnswering from sjrhuschlee +author: John Snow Labs +name: deberta_v3_base_squad2_sjrhuschlee_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_squad2_sjrhuschlee_pipeline` is a English model originally trained by sjrhuschlee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_sjrhuschlee_pipeline_en_5.5.0_3.0_1725239121391.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_sjrhuschlee_pipeline_en_5.5.0_3.0_1725239121391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_squad2_sjrhuschlee_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_squad2_sjrhuschlee_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_squad2_sjrhuschlee_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|645.3 MB| + +## References + +https://huggingface.co/sjrhuschlee/deberta-v3-base-squad2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large__sst2__train_16_2_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large__sst2__train_16_2_en.md new file mode 100644 index 00000000000000..32e53e07d7f39b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large__sst2__train_16_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large__sst2__train_16_2 DeBertaForSequenceClassification from SetFit +author: John Snow Labs +name: deberta_v3_large__sst2__train_16_2 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_16_2` is a English model originally trained by SetFit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_2_en_5.5.0_3.0_1725282746259.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_2_en_5.5.0_3.0_1725282746259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_16_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_16_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large__sst2__train_16_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/SetFit/deberta-v3-large__sst2__train-16-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large__sst2__train_16_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large__sst2__train_16_2_pipeline_en.md new file mode 100644 index 00000000000000..527f2cc07ae94c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large__sst2__train_16_2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large__sst2__train_16_2_pipeline pipeline DeBertaForSequenceClassification from SetFit +author: John Snow Labs +name: deberta_v3_large__sst2__train_16_2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_16_2_pipeline` is a English model originally trained by SetFit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_2_pipeline_en_5.5.0_3.0_1725282880646.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_2_pipeline_en_5.5.0_3.0_1725282880646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large__sst2__train_16_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large__sst2__train_16_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large__sst2__train_16_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/SetFit/deberta-v3-large__sst2__train-16-2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large__sst2__train_8_7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large__sst2__train_8_7_pipeline_en.md new file mode 100644 index 00000000000000..27fc203295e009 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large__sst2__train_8_7_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large__sst2__train_8_7_pipeline pipeline DeBertaForSequenceClassification from SetFit +author: John Snow Labs +name: deberta_v3_large__sst2__train_8_7_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_8_7_pipeline` is a English model originally trained by SetFit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_7_pipeline_en_5.5.0_3.0_1725282324345.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_7_pipeline_en_5.5.0_3.0_1725282324345.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large__sst2__train_8_7_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large__sst2__train_8_7_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large__sst2__train_8_7_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/SetFit/deberta-v3-large__sst2__train-8-7 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_en.md new file mode 100644 index 00000000000000..f6ead6194a8496 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large DeBertaEmbeddings from microsoft +author: John Snow Labs +name: deberta_v3_large +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large` is a English model originally trained by microsoft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_en_5.5.0_3.0_1725261964402.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_en_5.5.0_3.0_1725261964402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_v3_large","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/microsoft/deberta-v3-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_finetuned_abm_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_finetuned_abm_en.md new file mode 100644 index 00000000000000..f1779cf182ca6a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_finetuned_abm_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_abm DeBertaForQuestionAnswering from bradleyg223 +author: John Snow Labs +name: deberta_v3_large_finetuned_abm +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_abm` is a English model originally trained by bradleyg223. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_abm_en_5.5.0_3.0_1725239499667.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_abm_en_5.5.0_3.0_1725239499667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_finetuned_abm","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_finetuned_abm", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_abm| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.4 GB| + +## References + +https://huggingface.co/bradleyg223/deberta-v3-large-finetuned-abm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_finetuned_abm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_finetuned_abm_pipeline_en.md new file mode 100644 index 00000000000000..e9cd55929ce722 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_finetuned_abm_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_large_finetuned_abm_pipeline pipeline DeBertaForQuestionAnswering from bradleyg223 +author: John Snow Labs +name: deberta_v3_large_finetuned_abm_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_abm_pipeline` is a English model originally trained by bradleyg223. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_abm_pipeline_en_5.5.0_3.0_1725239650772.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_abm_pipeline_en_5.5.0_3.0_1725239650772.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_finetuned_abm_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_finetuned_abm_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_finetuned_abm_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.4 GB| + +## References + +https://huggingface.co/bradleyg223/deberta-v3-large-finetuned-abm + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_pipeline_en.md new file mode 100644 index 00000000000000..bae89f59c90ac4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_pipeline pipeline DeBertaEmbeddings from microsoft +author: John Snow Labs +name: deberta_v3_large_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_pipeline` is a English model originally trained by microsoft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_pipeline_en_5.5.0_3.0_1725262263123.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_pipeline_en_5.5.0_3.0_1725262263123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/microsoft/deberta-v3-large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_reram_qa_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_reram_qa_en.md new file mode 100644 index 00000000000000..b0b4999bc6b79f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_reram_qa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_large_reram_qa DeBertaForQuestionAnswering from GuakGuak +author: John Snow Labs +name: deberta_v3_large_reram_qa +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_reram_qa` is a English model originally trained by GuakGuak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_reram_qa_en_5.5.0_3.0_1725240321464.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_reram_qa_en_5.5.0_3.0_1725240321464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_reram_qa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_reram_qa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_reram_qa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/GuakGuak/deberta-v3-large-reram-qa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_en.md new file mode 100644 index 00000000000000..7efd42286014ee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli DeBertaForSequenceClassification from Joelzhang +author: John Snow Labs +name: deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli` is a English model originally trained by Joelzhang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_en_5.5.0_3.0_1725283681494.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_en_5.5.0_3.0_1725283681494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/Joelzhang/deberta-v3-large-snli_mnli_fever_anli_R1_R2_R3-nli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_pipeline_en.md new file mode 100644 index 00000000000000..85545297bbf0de --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_pipeline pipeline DeBertaForSequenceClassification from Joelzhang +author: John Snow Labs +name: deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_pipeline` is a English model originally trained by Joelzhang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_pipeline_en_5.5.0_3.0_1725283773733.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_pipeline_en_5.5.0_3.0_1725283773733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_snli_mnli_fever_anli_r1_r2_r3_nli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/Joelzhang/deberta-v3-large-snli_mnli_fever_anli_R1_R2_R3-nli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_squad2_clickbait_spoiling_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_squad2_clickbait_spoiling_en.md new file mode 100644 index 00000000000000..fe91943ac79dc0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_squad2_clickbait_spoiling_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_large_squad2_clickbait_spoiling DeBertaForQuestionAnswering from Grzgrz +author: John Snow Labs +name: deberta_v3_large_squad2_clickbait_spoiling +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_squad2_clickbait_spoiling` is a English model originally trained by Grzgrz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_clickbait_spoiling_en_5.5.0_3.0_1725239231151.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_clickbait_spoiling_en_5.5.0_3.0_1725239231151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_squad2_clickbait_spoiling","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_squad2_clickbait_spoiling", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_squad2_clickbait_spoiling| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/Grzgrz/deberta-v3-large-squad2-clickbait-spoiling \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_squad2_clickbait_spoiling_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_squad2_clickbait_spoiling_pipeline_en.md new file mode 100644 index 00000000000000..650a99b10e93c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_squad2_clickbait_spoiling_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_large_squad2_clickbait_spoiling_pipeline pipeline DeBertaForQuestionAnswering from Grzgrz +author: John Snow Labs +name: deberta_v3_large_squad2_clickbait_spoiling_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_squad2_clickbait_spoiling_pipeline` is a English model originally trained by Grzgrz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_clickbait_spoiling_pipeline_en_5.5.0_3.0_1725239328979.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_clickbait_spoiling_pipeline_en_5.5.0_3.0_1725239328979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_squad2_clickbait_spoiling_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_squad2_clickbait_spoiling_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_squad2_clickbait_spoiling_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/Grzgrz/deberta-v3-large-squad2-clickbait-spoiling + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_squad2_navteca_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_squad2_navteca_en.md new file mode 100644 index 00000000000000..c7a8a02699f4a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_squad2_navteca_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English deberta_v3_large_squad2_navteca DeBertaForQuestionAnswering from navteca +author: John Snow Labs +name: deberta_v3_large_squad2_navteca +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_squad2_navteca` is a English model originally trained by navteca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_navteca_en_5.5.0_3.0_1725239936677.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_navteca_en_5.5.0_3.0_1725239936677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_squad2_navteca","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_large_squad2_navteca", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_squad2_navteca| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/navteca/deberta-v3-large-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_fluency_rater_gpt4_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_fluency_rater_gpt4_en.md new file mode 100644 index 00000000000000..419625fbd8d564 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_fluency_rater_gpt4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_survey_fluency_rater_gpt4 DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_fluency_rater_gpt4 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_fluency_rater_gpt4` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_fluency_rater_gpt4_en_5.5.0_3.0_1725283023083.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_fluency_rater_gpt4_en_5.5.0_3.0_1725283023083.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_fluency_rater_gpt4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_fluency_rater_gpt4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_fluency_rater_gpt4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-fluency-rater-gpt4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_fluency_rater_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_fluency_rater_gpt4_pipeline_en.md new file mode 100644 index 00000000000000..d822063a984cfb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_fluency_rater_gpt4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_survey_fluency_rater_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_fluency_rater_gpt4_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_fluency_rater_gpt4_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_fluency_rater_gpt4_pipeline_en_5.5.0_3.0_1725283151607.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_fluency_rater_gpt4_pipeline_en_5.5.0_3.0_1725283151607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_survey_fluency_rater_gpt4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_survey_fluency_rater_gpt4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_fluency_rater_gpt4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-fluency-rater-gpt4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_en.md new file mode 100644 index 00000000000000..469631a90493d8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4 DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_en_5.5.0_3.0_1725282600835.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_en_5.5.0_3.0_1725282600835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-main_passage_consistency-rater-half-gpt4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_pipeline_en.md new file mode 100644 index 00000000000000..99cf7f8bb81fd2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_pipeline_en_5.5.0_3.0_1725282716669.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_pipeline_en_5.5.0_3.0_1725282716669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_main_passage_consistency_rater_half_gpt4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-main_passage_consistency-rater-half-gpt4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_en.md new file mode 100644 index 00000000000000..dea12e45b68b62 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4 DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_en_5.5.0_3.0_1725282016389.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_en_5.5.0_3.0_1725282016389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-new_fact_related_passage-rater-all-gpt4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_pipeline_en.md new file mode 100644 index 00000000000000..fc65edc5725567 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_pipeline_en_5.5.0_3.0_1725282106277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_pipeline_en_5.5.0_3.0_1725282106277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_all_gpt4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-new_fact_related_passage-rater-all-gpt4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_en.md new file mode 100644 index 00000000000000..b935d36638dc15 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_survey_related_passage_old_facts_rater_gpt4 DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_related_passage_old_facts_rater_gpt4 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_related_passage_old_facts_rater_gpt4` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_en_5.5.0_3.0_1725283245391.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_en_5.5.0_3.0_1725283245391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_related_passage_old_facts_rater_gpt4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_related_passage_old_facts_rater_gpt4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_related_passage_old_facts_rater_gpt4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-related_passage_old_facts-rater-gpt4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_pipeline_en.md new file mode 100644 index 00000000000000..1ec02d27b33088 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati +author: John Snow Labs +name: deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_pipeline_en_5.5.0_3.0_1725283334634.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_pipeline_en_5.5.0_3.0_1725283334634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_survey_related_passage_old_facts_rater_gpt4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-survey-related_passage_old_facts-rater-gpt4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_small_finetuned_sst2_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_small_finetuned_sst2_en.md new file mode 100644 index 00000000000000..cc4a7e55f44b76 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_small_finetuned_sst2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_small_finetuned_sst2 DeBertaForSequenceClassification from mrm8488 +author: John Snow Labs +name: deberta_v3_small_finetuned_sst2 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_sst2` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_sst2_en_5.5.0_3.0_1725281965561.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_sst2_en_5.5.0_3.0_1725281965561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_finetuned_sst2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_finetuned_sst2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_finetuned_sst2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|415.2 MB| + +## References + +https://huggingface.co/mrm8488/deberta-v3-small-finetuned-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_small_finetuned_sst2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_small_finetuned_sst2_pipeline_en.md new file mode 100644 index 00000000000000..b8cc4af460a988 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_small_finetuned_sst2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_small_finetuned_sst2_pipeline pipeline DeBertaForSequenceClassification from mrm8488 +author: John Snow Labs +name: deberta_v3_small_finetuned_sst2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_sst2_pipeline` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_sst2_pipeline_en_5.5.0_3.0_1725282034899.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_sst2_pipeline_en_5.5.0_3.0_1725282034899.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_small_finetuned_sst2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_small_finetuned_sst2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_small_finetuned_sst2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|415.2 MB| + +## References + +https://huggingface.co/mrm8488/deberta-v3-small-finetuned-sst2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_xsmall_squad2_fungi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_xsmall_squad2_fungi_pipeline_en.md new file mode 100644 index 00000000000000..e619c078c7a014 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_xsmall_squad2_fungi_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deberta_v3_xsmall_squad2_fungi_pipeline pipeline DeBertaForQuestionAnswering from fungi +author: John Snow Labs +name: deberta_v3_xsmall_squad2_fungi_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_squad2_fungi_pipeline` is a English model originally trained by fungi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_squad2_fungi_pipeline_en_5.5.0_3.0_1725268898804.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_squad2_fungi_pipeline_en_5.5.0_3.0_1725268898804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_xsmall_squad2_fungi_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_xsmall_squad2_fungi_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_xsmall_squad2_fungi_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|244.4 MB| + +## References + +https://huggingface.co/fungi/deberta-v3-xsmall-squad2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-debertav3_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-02-debertav3_finetuned_squad_en.md new file mode 100644 index 00000000000000..da325ad32f21cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-debertav3_finetuned_squad_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English debertav3_finetuned_squad DeBertaForQuestionAnswering from jasscr +author: John Snow Labs +name: debertav3_finetuned_squad +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debertav3_finetuned_squad` is a English model originally trained by jasscr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debertav3_finetuned_squad_en_5.5.0_3.0_1725239841087.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debertav3_finetuned_squad_en_5.5.0_3.0_1725239841087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("debertav3_finetuned_squad","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("debertav3_finetuned_squad", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|debertav3_finetuned_squad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|588.5 MB| + +## References + +https://huggingface.co/jasscr/debertav3-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-debertav3_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-debertav3_finetuned_squad_pipeline_en.md new file mode 100644 index 00000000000000..2a6c2f950b8832 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-debertav3_finetuned_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English debertav3_finetuned_squad_pipeline pipeline DeBertaForQuestionAnswering from jasscr +author: John Snow Labs +name: debertav3_finetuned_squad_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debertav3_finetuned_squad_pipeline` is a English model originally trained by jasscr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debertav3_finetuned_squad_pipeline_en_5.5.0_3.0_1725239907685.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debertav3_finetuned_squad_pipeline_en_5.5.0_3.0_1725239907685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("debertav3_finetuned_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("debertav3_finetuned_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|debertav3_finetuned_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|588.5 MB| + +## References + +https://huggingface.co/jasscr/debertav3-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deepchemoberta_reg_en.md b/docs/_posts/ahmedlone127/2024-09-02-deepchemoberta_reg_en.md new file mode 100644 index 00000000000000..60dc22acedb003 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deepchemoberta_reg_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deepchemoberta_reg RoBertaForSequenceClassification from Chettaniiay +author: John Snow Labs +name: deepchemoberta_reg +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepchemoberta_reg` is a English model originally trained by Chettaniiay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepchemoberta_reg_en_5.5.0_3.0_1725277219461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepchemoberta_reg_en_5.5.0_3.0_1725277219461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("deepchemoberta_reg","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("deepchemoberta_reg", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deepchemoberta_reg| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|323.6 MB| + +## References + +https://huggingface.co/Chettaniiay/DeepChemoBERTA_Reg \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-deepchemoberta_reg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deepchemoberta_reg_pipeline_en.md new file mode 100644 index 00000000000000..018dc7de0cbdb4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-deepchemoberta_reg_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deepchemoberta_reg_pipeline pipeline RoBertaForSequenceClassification from Chettaniiay +author: John Snow Labs +name: deepchemoberta_reg_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepchemoberta_reg_pipeline` is a English model originally trained by Chettaniiay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepchemoberta_reg_pipeline_en_5.5.0_3.0_1725277236618.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepchemoberta_reg_pipeline_en_5.5.0_3.0_1725277236618.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deepchemoberta_reg_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deepchemoberta_reg_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deepchemoberta_reg_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|323.6 MB| + +## References + +https://huggingface.co/Chettaniiay/DeepChemoBERTA_Reg + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-def_and_notat_token_classification_model_en.md b/docs/_posts/ahmedlone127/2024-09-02-def_and_notat_token_classification_model_en.md new file mode 100644 index 00000000000000..75556e77d06df0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-def_and_notat_token_classification_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English def_and_notat_token_classification_model DistilBertForTokenClassification from hyunjongkimmath +author: John Snow Labs +name: def_and_notat_token_classification_model +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`def_and_notat_token_classification_model` is a English model originally trained by hyunjongkimmath. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/def_and_notat_token_classification_model_en_5.5.0_3.0_1725267377567.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/def_and_notat_token_classification_model_en_5.5.0_3.0_1725267377567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("def_and_notat_token_classification_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("def_and_notat_token_classification_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|def_and_notat_token_classification_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|248.6 MB| + +## References + +https://huggingface.co/hyunjongkimmath/def_and_notat_token_classification_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-def_and_notat_token_classification_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-def_and_notat_token_classification_model_pipeline_en.md new file mode 100644 index 00000000000000..5dd55a641bd1c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-def_and_notat_token_classification_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English def_and_notat_token_classification_model_pipeline pipeline DistilBertForTokenClassification from hyunjongkimmath +author: John Snow Labs +name: def_and_notat_token_classification_model_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`def_and_notat_token_classification_model_pipeline` is a English model originally trained by hyunjongkimmath. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/def_and_notat_token_classification_model_pipeline_en_5.5.0_3.0_1725267392003.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/def_and_notat_token_classification_model_pipeline_en_5.5.0_3.0_1725267392003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("def_and_notat_token_classification_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("def_and_notat_token_classification_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|def_and_notat_token_classification_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|248.7 MB| + +## References + +https://huggingface.co/hyunjongkimmath/def_and_notat_token_classification_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-diana_camembert_en.md b/docs/_posts/ahmedlone127/2024-09-02-diana_camembert_en.md new file mode 100644 index 00000000000000..e3b5509876d8ef --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-diana_camembert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English diana_camembert CamemBertEmbeddings from dianamathew +author: John Snow Labs +name: diana_camembert +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`diana_camembert` is a English model originally trained by dianamathew. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/diana_camembert_en_5.5.0_3.0_1725299887562.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/diana_camembert_en_5.5.0_3.0_1725299887562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("diana_camembert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("diana_camembert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|diana_camembert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/dianamathew/diana_camembert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-diana_camembert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-diana_camembert_pipeline_en.md new file mode 100644 index 00000000000000..e4850e71031ae7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-diana_camembert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English diana_camembert_pipeline pipeline CamemBertEmbeddings from dianamathew +author: John Snow Labs +name: diana_camembert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`diana_camembert_pipeline` is a English model originally trained by dianamathew. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/diana_camembert_pipeline_en_5.5.0_3.0_1725299966284.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/diana_camembert_pipeline_en_5.5.0_3.0_1725299966284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("diana_camembert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("diana_camembert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|diana_camembert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/dianamathew/diana_camembert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-disaster_request_distil_en.md b/docs/_posts/ahmedlone127/2024-09-02-disaster_request_distil_en.md new file mode 100644 index 00000000000000..f4acaa0809a470 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-disaster_request_distil_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English disaster_request_distil DistilBertForSequenceClassification from RescueSight +author: John Snow Labs +name: disaster_request_distil +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disaster_request_distil` is a English model originally trained by RescueSight. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disaster_request_distil_en_5.5.0_3.0_1725305734651.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disaster_request_distil_en_5.5.0_3.0_1725305734651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("disaster_request_distil","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("disaster_request_distil", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|disaster_request_distil| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.6 MB| + +## References + +https://huggingface.co/RescueSight/Disaster-Request-DISTIL \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-disaster_request_distil_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-disaster_request_distil_pipeline_en.md new file mode 100644 index 00000000000000..8ebcce81d080eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-disaster_request_distil_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English disaster_request_distil_pipeline pipeline DistilBertForSequenceClassification from RescueSight +author: John Snow Labs +name: disaster_request_distil_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disaster_request_distil_pipeline` is a English model originally trained by RescueSight. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disaster_request_distil_pipeline_en_5.5.0_3.0_1725305747335.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disaster_request_distil_pipeline_en_5.5.0_3.0_1725305747335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("disaster_request_distil_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("disaster_request_distil_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|disaster_request_distil_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.6 MB| + +## References + +https://huggingface.co/RescueSight/Disaster-Request-DISTIL + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distil_task_b_2_en.md b/docs/_posts/ahmedlone127/2024-09-02-distil_task_b_2_en.md new file mode 100644 index 00000000000000..f90153962849e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distil_task_b_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distil_task_b_2 DistilBertForSequenceClassification from sheduele +author: John Snow Labs +name: distil_task_b_2 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_task_b_2` is a English model originally trained by sheduele. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_task_b_2_en_5.5.0_3.0_1725291656544.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_task_b_2_en_5.5.0_3.0_1725291656544.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distil_task_b_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distil_task_b_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distil_task_b_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/sheduele/distil_task_B_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distil_whisper_small_cantonese_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-02-distil_whisper_small_cantonese_pipeline_zh.md new file mode 100644 index 00000000000000..e56572c4da7a30 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distil_whisper_small_cantonese_pipeline_zh.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Chinese distil_whisper_small_cantonese_pipeline pipeline WhisperForCTC from alvanlii +author: John Snow Labs +name: distil_whisper_small_cantonese_pipeline +date: 2024-09-02 +tags: [zh, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_whisper_small_cantonese_pipeline` is a Chinese model originally trained by alvanlii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_whisper_small_cantonese_pipeline_zh_5.5.0_3.0_1725244929504.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_whisper_small_cantonese_pipeline_zh_5.5.0_3.0_1725244929504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distil_whisper_small_cantonese_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distil_whisper_small_cantonese_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distil_whisper_small_cantonese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|1.1 GB| + +## References + +https://huggingface.co/alvanlii/distil-whisper-small-cantonese + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distil_whisper_small_cantonese_zh.md b/docs/_posts/ahmedlone127/2024-09-02-distil_whisper_small_cantonese_zh.md new file mode 100644 index 00000000000000..9bad0e282a2598 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distil_whisper_small_cantonese_zh.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Chinese distil_whisper_small_cantonese WhisperForCTC from alvanlii +author: John Snow Labs +name: distil_whisper_small_cantonese +date: 2024-09-02 +tags: [zh, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_whisper_small_cantonese` is a Chinese model originally trained by alvanlii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_whisper_small_cantonese_zh_5.5.0_3.0_1725244864635.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_whisper_small_cantonese_zh_5.5.0_3.0_1725244864635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("distil_whisper_small_cantonese","zh") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("distil_whisper_small_cantonese", "zh") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distil_whisper_small_cantonese| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|zh| +|Size:|1.1 GB| + +## References + +https://huggingface.co/alvanlii/distil-whisper-small-cantonese \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_cased_jayr7_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_cased_jayr7_en.md new file mode 100644 index 00000000000000..5ad75f6b394c16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_cased_jayr7_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_cased_jayr7 DistilBertForTokenClassification from JayR7 +author: John Snow Labs +name: distilbert_base_cased_jayr7 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_jayr7` is a English model originally trained by JayR7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_jayr7_en_5.5.0_3.0_1725267852991.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_jayr7_en_5.5.0_3.0_1725267852991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_cased_jayr7","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_cased_jayr7", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_cased_jayr7| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/JayR7/distilbert-base-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_cased_jayr7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_cased_jayr7_pipeline_en.md new file mode 100644 index 00000000000000..94bf0eb72b092b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_cased_jayr7_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_cased_jayr7_pipeline pipeline DistilBertForTokenClassification from JayR7 +author: John Snow Labs +name: distilbert_base_cased_jayr7_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_jayr7_pipeline` is a English model originally trained by JayR7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_jayr7_pipeline_en_5.5.0_3.0_1725267866391.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_jayr7_pipeline_en_5.5.0_3.0_1725267866391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_cased_jayr7_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_cased_jayr7_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_cased_jayr7_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.9 MB| + +## References + +https://huggingface.co/JayR7/distilbert-base-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_multilingual_cased_pii_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_multilingual_cased_pii_pipeline_xx.md new file mode 100644 index 00000000000000..c1da81140245c3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_multilingual_cased_pii_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual distilbert_base_multilingual_cased_pii_pipeline pipeline DistilBertForTokenClassification from yonigo +author: John Snow Labs +name: distilbert_base_multilingual_cased_pii_pipeline +date: 2024-09-02 +tags: [xx, open_source, pipeline, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_pii_pipeline` is a Multilingual model originally trained by yonigo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_pii_pipeline_xx_5.5.0_3.0_1725267595461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_pii_pipeline_xx_5.5.0_3.0_1725267595461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_multilingual_cased_pii_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_multilingual_cased_pii_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_multilingual_cased_pii_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|505.6 MB| + +## References + +https://huggingface.co/yonigo/distilbert-base-multilingual-cased-pii + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_multilingual_cased_pii_xx.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_multilingual_cased_pii_xx.md new file mode 100644 index 00000000000000..18d7572a62729e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_multilingual_cased_pii_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual distilbert_base_multilingual_cased_pii DistilBertForTokenClassification from yonigo +author: John Snow Labs +name: distilbert_base_multilingual_cased_pii +date: 2024-09-02 +tags: [xx, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_pii` is a Multilingual model originally trained by yonigo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_pii_xx_5.5.0_3.0_1725267568487.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_pii_xx_5.5.0_3.0_1725267568487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_multilingual_cased_pii","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_multilingual_cased_pii", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_multilingual_cased_pii| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|xx| +|Size:|505.6 MB| + +## References + +https://huggingface.co/yonigo/distilbert-base-multilingual-cased-pii \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_edithram23_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_edithram23_en.md new file mode 100644 index 00000000000000..7a32b69924527b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_edithram23_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_edithram23 DistilBertForTokenClassification from edithram23 +author: John Snow Labs +name: distilbert_base_uncased_edithram23 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_edithram23` is a English model originally trained by edithram23. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_edithram23_en_5.5.0_3.0_1725267875778.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_edithram23_en_5.5.0_3.0_1725267875778.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_edithram23","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_edithram23", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_edithram23| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/edithram23/distilbert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_edithram23_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_edithram23_pipeline_en.md new file mode 100644 index 00000000000000..969480bca7908b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_edithram23_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_edithram23_pipeline pipeline DistilBertForTokenClassification from edithram23 +author: John Snow Labs +name: distilbert_base_uncased_edithram23_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_edithram23_pipeline` is a English model originally trained by edithram23. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_edithram23_pipeline_en_5.5.0_3.0_1725267889379.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_edithram23_pipeline_en_5.5.0_3.0_1725267889379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_edithram23_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_edithram23_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_edithram23_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/edithram23/distilbert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_en.md new file mode 100644 index 00000000000000..1e8afc4c12b946 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0 DistilBertForSequenceClassification from LeBruse +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0` is a English model originally trained by LeBruse. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_en_5.5.0_3.0_1725305519585.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_en_5.5.0_3.0_1725305519585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/LeBruse/distilbert-base-uncased-finetuned-emotion-english-sarcasm-1.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_en.md new file mode 100644 index 00000000000000..edb1875353f232 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0 DistilBertForSequenceClassification from LeBruse +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0` is a English model originally trained by LeBruse. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_en_5.5.0_3.0_1725291646244.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_en_5.5.0_3.0_1725291646244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/LeBruse/distilbert-base-uncased-finetuned-emotion-overall-sarcasm-1.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_pipeline_en.md new file mode 100644 index 00000000000000..b68a1f54525b13 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_pipeline pipeline DistilBertForSequenceClassification from LeBruse +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_pipeline` is a English model originally trained by LeBruse. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_pipeline_en_5.5.0_3.0_1725291658808.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_pipeline_en_5.5.0_3.0_1725291658808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotion_overall_sarcasm_1_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/LeBruse/distilbert-base-uncased-finetuned-emotion-overall-sarcasm-1.0 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotions_dataset_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotions_dataset_en.md new file mode 100644 index 00000000000000..93b29344b8d5f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotions_dataset_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotions_dataset DistilBertForSequenceClassification from dasaprakashk +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotions_dataset +date: 2024-09-02 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotions_dataset` is a English model originally trained by dasaprakashk. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_dataset_en_5.5.0_3.0_1725305621158.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_dataset_en_5.5.0_3.0_1725305621158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotions_dataset","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotions_dataset","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotions_dataset| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +References + +https://huggingface.co/dasaprakashk/distilbert-base-uncased-finetuned-emotions-dataset \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotions_jakeclark_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotions_jakeclark_en.md new file mode 100644 index 00000000000000..39946d8f58ef96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotions_jakeclark_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotions_jakeclark DistilBertForSequenceClassification from JakeClark +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotions_jakeclark +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotions_jakeclark` is a English model originally trained by JakeClark. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_jakeclark_en_5.5.0_3.0_1725292324076.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_jakeclark_en_5.5.0_3.0_1725292324076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotions_jakeclark","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotions_jakeclark", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotions_jakeclark| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/JakeClark/distilbert-base-uncased-finetuned-emotions \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_0uz2z_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_0uz2z_en.md new file mode 100644 index 00000000000000..3ce8a6209a83f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_0uz2z_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_0uz2z DistilBertForTokenClassification from 0uz2z +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_0uz2z +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_0uz2z` is a English model originally trained by 0uz2z. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_0uz2z_en_5.5.0_3.0_1725267285819.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_0uz2z_en_5.5.0_3.0_1725267285819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_0uz2z","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_0uz2z", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_0uz2z| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/0uz2z/distilbert-base-uncased-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_0uz2z_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_0uz2z_pipeline_en.md new file mode 100644 index 00000000000000..8dc48083572f00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_0uz2z_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_0uz2z_pipeline pipeline DistilBertForTokenClassification from 0uz2z +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_0uz2z_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_0uz2z_pipeline` is a English model originally trained by 0uz2z. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_0uz2z_pipeline_en_5.5.0_3.0_1725267303441.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_0uz2z_pipeline_en_5.5.0_3.0_1725267303441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_0uz2z_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_0uz2z_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_0uz2z_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/0uz2z/distilbert-base-uncased-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_kanansharmaa_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_kanansharmaa_en.md new file mode 100644 index 00000000000000..47ccf0b8cf24b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_kanansharmaa_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_kanansharmaa DistilBertForTokenClassification from kanansharmaa +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_kanansharmaa +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_kanansharmaa` is a English model originally trained by kanansharmaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_kanansharmaa_en_5.5.0_3.0_1725267427582.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_kanansharmaa_en_5.5.0_3.0_1725267427582.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_kanansharmaa","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_kanansharmaa", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_kanansharmaa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/kanansharmaa/distilbert-base-uncased-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_kanansharmaa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_kanansharmaa_pipeline_en.md new file mode 100644 index 00000000000000..bd8475189ac8f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_kanansharmaa_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_kanansharmaa_pipeline pipeline DistilBertForTokenClassification from kanansharmaa +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_kanansharmaa_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_kanansharmaa_pipeline` is a English model originally trained by kanansharmaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_kanansharmaa_pipeline_en_5.5.0_3.0_1725267447084.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_kanansharmaa_pipeline_en_5.5.0_3.0_1725267447084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_kanansharmaa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_kanansharmaa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_kanansharmaa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/kanansharmaa/distilbert-base-uncased-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_keitharogo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_keitharogo_pipeline_en.md new file mode 100644 index 00000000000000..fa1958500cc3ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_keitharogo_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_keitharogo_pipeline pipeline DistilBertForTokenClassification from KeithArogo +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_keitharogo_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_keitharogo_pipeline` is a English model originally trained by KeithArogo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_keitharogo_pipeline_en_5.5.0_3.0_1725267671267.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_keitharogo_pipeline_en_5.5.0_3.0_1725267671267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_keitharogo_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_keitharogo_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_keitharogo_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/KeithArogo/distilbert-base-uncased-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_senthil2002_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_senthil2002_pipeline_en.md new file mode 100644 index 00000000000000..5fd818ad33ecb4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_senthil2002_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_ner_senthil2002_pipeline pipeline DistilBertForTokenClassification from senthil2002 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_ner_senthil2002_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_senthil2002_pipeline` is a English model originally trained by senthil2002. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_senthil2002_pipeline_en_5.5.0_3.0_1725267786307.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_senthil2002_pipeline_en_5.5.0_3.0_1725267786307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_senthil2002_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_senthil2002_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_ner_senthil2002_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/senthil2002/distilbert-base-uncased-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_norwegian_perturb_cria111_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_norwegian_perturb_cria111_en.md new file mode 100644 index 00000000000000..e005b09d5323be --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_norwegian_perturb_cria111_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_norwegian_perturb_cria111 DistilBertForTokenClassification from cria111 +author: John Snow Labs +name: distilbert_base_uncased_norwegian_perturb_cria111 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_norwegian_perturb_cria111` is a English model originally trained by cria111. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_norwegian_perturb_cria111_en_5.5.0_3.0_1725267286651.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_norwegian_perturb_cria111_en_5.5.0_3.0_1725267286651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_norwegian_perturb_cria111","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_norwegian_perturb_cria111", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_norwegian_perturb_cria111| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/cria111/distilbert-base-uncased-no-perturb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_norwegian_perturb_cria111_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_norwegian_perturb_cria111_pipeline_en.md new file mode 100644 index 00000000000000..ed9cfc54f62231 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_norwegian_perturb_cria111_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_norwegian_perturb_cria111_pipeline pipeline DistilBertForTokenClassification from cria111 +author: John Snow Labs +name: distilbert_base_uncased_norwegian_perturb_cria111_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_norwegian_perturb_cria111_pipeline` is a English model originally trained by cria111. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_norwegian_perturb_cria111_pipeline_en_5.5.0_3.0_1725267302561.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_norwegian_perturb_cria111_pipeline_en_5.5.0_3.0_1725267302561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_norwegian_perturb_cria111_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_norwegian_perturb_cria111_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_norwegian_perturb_cria111_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/cria111/distilbert-base-uncased-no-perturb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_pii300k_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_pii300k_en.md new file mode 100644 index 00000000000000..c657e2a105ef79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_pii300k_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_pii300k DistilBertForTokenClassification from devtibo +author: John Snow Labs +name: distilbert_base_uncased_pii300k +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_pii300k` is a English model originally trained by devtibo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_pii300k_en_5.5.0_3.0_1725267404627.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_pii300k_en_5.5.0_3.0_1725267404627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_pii300k","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_pii300k", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_pii300k| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.6 MB| + +## References + +https://huggingface.co/devtibo/distilbert-base-uncased-pii300k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_pii300k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_pii300k_pipeline_en.md new file mode 100644 index 00000000000000..3a53962292726f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_pii300k_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_pii300k_pipeline pipeline DistilBertForTokenClassification from devtibo +author: John Snow Labs +name: distilbert_base_uncased_pii300k_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_pii300k_pipeline` is a English model originally trained by devtibo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_pii300k_pipeline_en_5.5.0_3.0_1725267418438.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_pii300k_pipeline_en_5.5.0_3.0_1725267418438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_pii300k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_pii300k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_pii300k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.6 MB| + +## References + +https://huggingface.co/devtibo/distilbert-base-uncased-pii300k + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_travel_zphr_0st_refine_ck10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_travel_zphr_0st_refine_ck10_pipeline_en.md new file mode 100644 index 00000000000000..395c0fffb8f55c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_travel_zphr_0st_refine_ck10_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_travel_zphr_0st_refine_ck10_pipeline pipeline DistilBertForSequenceClassification from tom192180 +author: John Snow Labs +name: distilbert_base_uncased_travel_zphr_0st_refine_ck10_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_travel_zphr_0st_refine_ck10_pipeline` is a English model originally trained by tom192180. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_travel_zphr_0st_refine_ck10_pipeline_en_5.5.0_3.0_1725305711118.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_travel_zphr_0st_refine_ck10_pipeline_en_5.5.0_3.0_1725305711118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_travel_zphr_0st_refine_ck10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_travel_zphr_0st_refine_ck10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_travel_zphr_0st_refine_ck10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/tom192180/distilbert-base-uncased_travel_zphr_0st_refine_ck10 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_emotion_narapuram_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_emotion_narapuram_en.md new file mode 100644 index 00000000000000..15e42584e312a4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_emotion_narapuram_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_emotion_narapuram DistilBertForSequenceClassification from Narapuram +author: John Snow Labs +name: distilbert_emotion_narapuram +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_narapuram` is a English model originally trained by Narapuram. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_narapuram_en_5.5.0_3.0_1725292165581.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_narapuram_en_5.5.0_3.0_1725292165581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_emotion_narapuram","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_emotion_narapuram", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_emotion_narapuram| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Narapuram/distilbert-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_fine_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_fine_en.md new file mode 100644 index 00000000000000..10a1c25b4193e7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_fine_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_fine DistilBertForSequenceClassification from michael0218 +author: John Snow Labs +name: distilbert_fine +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_fine` is a English model originally trained by michael0218. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_fine_en_5.5.0_3.0_1725306054579.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_fine_en_5.5.0_3.0_1725306054579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_fine","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_fine", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_fine| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/michael0218/distilbert_fine \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_emotion_hemanthkotaprolu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_emotion_hemanthkotaprolu_pipeline_en.md new file mode 100644 index 00000000000000..4fbbc25aac5d4d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_emotion_hemanthkotaprolu_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_finetuned_emotion_hemanthkotaprolu_pipeline pipeline DistilBertForSequenceClassification from hemanthkotaprolu +author: John Snow Labs +name: distilbert_finetuned_emotion_hemanthkotaprolu_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_emotion_hemanthkotaprolu_pipeline` is a English model originally trained by hemanthkotaprolu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_emotion_hemanthkotaprolu_pipeline_en_5.5.0_3.0_1725292115857.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_emotion_hemanthkotaprolu_pipeline_en_5.5.0_3.0_1725292115857.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_finetuned_emotion_hemanthkotaprolu_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_finetuned_emotion_hemanthkotaprolu_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_finetuned_emotion_hemanthkotaprolu_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/hemanthkotaprolu/distilbert-finetuned-emotion + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_emowoz_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_emowoz_en.md new file mode 100644 index 00000000000000..2226f422d45504 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_emowoz_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_finetuned_emowoz DistilBertForSequenceClassification from mh0122 +author: John Snow Labs +name: distilbert_finetuned_emowoz +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_emowoz` is a English model originally trained by mh0122. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_emowoz_en_5.5.0_3.0_1725292119085.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_emowoz_en_5.5.0_3.0_1725292119085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_emowoz","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_emowoz", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_finetuned_emowoz| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/mh0122/distilbert-finetuned-emowoz \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_resumes_sections_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_resumes_sections_en.md new file mode 100644 index 00000000000000..adad8cf6955236 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_resumes_sections_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_finetuned_resumes_sections DistilBertForSequenceClassification from has-abi +author: John Snow Labs +name: distilbert_finetuned_resumes_sections +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_resumes_sections` is a English model originally trained by has-abi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_resumes_sections_en_5.5.0_3.0_1725291745322.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_resumes_sections_en_5.5.0_3.0_1725291745322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_resumes_sections","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_resumes_sections", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_finetuned_resumes_sections| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|259.2 MB| + +## References + +https://huggingface.co/has-abi/distilBERT-finetuned-resumes-sections \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_resumes_sections_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_resumes_sections_pipeline_en.md new file mode 100644 index 00000000000000..cd7e189b07a25f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_resumes_sections_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_finetuned_resumes_sections_pipeline pipeline DistilBertForSequenceClassification from has-abi +author: John Snow Labs +name: distilbert_finetuned_resumes_sections_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_resumes_sections_pipeline` is a English model originally trained by has-abi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_resumes_sections_pipeline_en_5.5.0_3.0_1725291759600.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_resumes_sections_pipeline_en_5.5.0_3.0_1725291759600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_finetuned_resumes_sections_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_finetuned_resumes_sections_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_finetuned_resumes_sections_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|259.2 MB| + +## References + +https://huggingface.co/has-abi/distilBERT-finetuned-resumes-sections + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_dslim_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_dslim_en.md new file mode 100644 index 00000000000000..e84482025b0e68 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_dslim_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_ner_dslim DistilBertForTokenClassification from dslim +author: John Snow Labs +name: distilbert_ner_dslim +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_dslim` is a English model originally trained by dslim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_dslim_en_5.5.0_3.0_1725267670721.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_dslim_en_5.5.0_3.0_1725267670721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_dslim","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_dslim", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_ner_dslim| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/dslim/distilbert-NER \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_dslim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_dslim_pipeline_en.md new file mode 100644 index 00000000000000..ecf04bad8a087d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_dslim_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_ner_dslim_pipeline pipeline DistilBertForTokenClassification from dslim +author: John Snow Labs +name: distilbert_ner_dslim_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_dslim_pipeline` is a English model originally trained by dslim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_dslim_pipeline_en_5.5.0_3.0_1725267687095.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_dslim_pipeline_en_5.5.0_3.0_1725267687095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_ner_dslim_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_ner_dslim_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_ner_dslim_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/dslim/distilbert-NER + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_finer_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_finer_en.md new file mode 100644 index 00000000000000..7280cde122da31 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_finer_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_ner_finer DistilBertForTokenClassification from jishnunair +author: John Snow Labs +name: distilbert_ner_finer +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_finer` is a English model originally trained by jishnunair. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_finer_en_5.5.0_3.0_1725267895537.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_finer_en_5.5.0_3.0_1725267895537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_finer","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_finer", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_ner_finer| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|244.6 MB| + +## References + +https://huggingface.co/jishnunair/distilBert_NER_finer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_wnut_model_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_wnut_model_en.md new file mode 100644 index 00000000000000..c1e9aa849774ea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_wnut_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_ner_wnut_model DistilBertForTokenClassification from geshijoker +author: John Snow Labs +name: distilbert_ner_wnut_model +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_wnut_model` is a English model originally trained by geshijoker. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_wnut_model_en_5.5.0_3.0_1725267747399.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_wnut_model_en_5.5.0_3.0_1725267747399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_wnut_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_wnut_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_ner_wnut_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/geshijoker/distilbert_ner_wnut_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_wnut_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_wnut_model_pipeline_en.md new file mode 100644 index 00000000000000..1a2e0e5dcf531d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_wnut_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_ner_wnut_model_pipeline pipeline DistilBertForTokenClassification from geshijoker +author: John Snow Labs +name: distilbert_ner_wnut_model_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_wnut_model_pipeline` is a English model originally trained by geshijoker. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_wnut_model_pipeline_en_5.5.0_3.0_1725267761501.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_wnut_model_pipeline_en_5.5.0_3.0_1725267761501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_ner_wnut_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_ner_wnut_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_ner_wnut_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/geshijoker/distilbert_ner_wnut_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_phish_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_phish_en.md new file mode 100644 index 00000000000000..79048589eb7836 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_phish_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_phish DistilBertForSequenceClassification from bgspaditya +author: John Snow Labs +name: distilbert_phish +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_phish` is a English model originally trained by bgspaditya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_phish_en_5.5.0_3.0_1725291939461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_phish_en_5.5.0_3.0_1725291939461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_phish","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_phish", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_phish| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|246.0 MB| + +## References + +https://huggingface.co/bgspaditya/distilbert-phish \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_en.md new file mode 100644 index 00000000000000..c77b9f2bcac293 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_sequence_classifier_distilbert_base_uncased_agnews_student DistilBertForSequenceClassification from joeddav +author: John Snow Labs +name: distilbert_sequence_classifier_distilbert_base_uncased_agnews_student +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sequence_classifier_distilbert_base_uncased_agnews_student` is a English model originally trained by joeddav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_en_5.5.0_3.0_1725292290987.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_en_5.5.0_3.0_1725292290987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sequence_classifier_distilbert_base_uncased_agnews_student","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sequence_classifier_distilbert_base_uncased_agnews_student", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_sequence_classifier_distilbert_base_uncased_agnews_student| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/joeddav/distilbert-base-uncased-agnews-student \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_token_classifier_autotrain_final_784824218_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_token_classifier_autotrain_final_784824218_en.md new file mode 100644 index 00000000000000..cbcf40372af5fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_token_classifier_autotrain_final_784824218_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English DistilBertForTokenClassification Cased model (from Lucifermorningstar011) +author: John Snow Labs +name: distilbert_token_classifier_autotrain_final_784824218 +date: 2024-09-02 +tags: [en, open_source, distilbert, token_classification, ner, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autotrain-final-784824218` is a English model originally trained by `Lucifermorningstar011`. + +## Predicted Entities + +`0`, `9` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_token_classifier_autotrain_final_784824218_en_5.5.0_3.0_1725268037640.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_token_classifier_autotrain_final_784824218_en_5.5.0_3.0_1725268037640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_token_classifier_autotrain_final_784824218","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, tokenClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_token_classifier_autotrain_final_784824218","en") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_token_classifier_autotrain_final_784824218| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.2 MB| + +## References + +References + +- https://huggingface.co/Lucifermorningstar011/autotrain-final-784824218 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_token_classifier_autotrain_final_784824218_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_token_classifier_autotrain_final_784824218_pipeline_en.md new file mode 100644 index 00000000000000..707b187e570203 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_token_classifier_autotrain_final_784824218_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_token_classifier_autotrain_final_784824218_pipeline pipeline DistilBertForTokenClassification from Lucifermorningstar011 +author: John Snow Labs +name: distilbert_token_classifier_autotrain_final_784824218_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_token_classifier_autotrain_final_784824218_pipeline` is a English model originally trained by Lucifermorningstar011. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_token_classifier_autotrain_final_784824218_pipeline_en_5.5.0_3.0_1725268054317.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_token_classifier_autotrain_final_784824218_pipeline_en_5.5.0_3.0_1725268054317.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_token_classifier_autotrain_final_784824218_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_token_classifier_autotrain_final_784824218_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_token_classifier_autotrain_final_784824218_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/Lucifermorningstar011/autotrain-final-784824218 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_token_classifier_persian_ner_fa.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_token_classifier_persian_ner_fa.md new file mode 100644 index 00000000000000..443dec99576753 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_token_classifier_persian_ner_fa.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Persian distilbert_token_classifier_persian_ner DistilBertForTokenClassification from HooshvareLab +author: John Snow Labs +name: distilbert_token_classifier_persian_ner +date: 2024-09-02 +tags: [fa, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: fa +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_token_classifier_persian_ner` is a Persian model originally trained by HooshvareLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_token_classifier_persian_ner_fa_5.5.0_3.0_1725267589286.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_token_classifier_persian_ner_fa_5.5.0_3.0_1725267589286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_token_classifier_persian_ner","fa") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_token_classifier_persian_ner", "fa") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_token_classifier_persian_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|fa| +|Size:|282.3 MB| + +## References + +https://huggingface.co/HooshvareLab/distilbert-fa-zwnj-base-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_token_classifier_persian_ner_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_token_classifier_persian_ner_pipeline_fa.md new file mode 100644 index 00000000000000..ca6aabf6cf5545 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_token_classifier_persian_ner_pipeline_fa.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Persian distilbert_token_classifier_persian_ner_pipeline pipeline DistilBertForTokenClassification from HooshvareLab +author: John Snow Labs +name: distilbert_token_classifier_persian_ner_pipeline +date: 2024-09-02 +tags: [fa, open_source, pipeline, onnx] +task: Named Entity Recognition +language: fa +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_token_classifier_persian_ner_pipeline` is a Persian model originally trained by HooshvareLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_token_classifier_persian_ner_pipeline_fa_5.5.0_3.0_1725267604406.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_token_classifier_persian_ner_pipeline_fa_5.5.0_3.0_1725267604406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_token_classifier_persian_ner_pipeline", lang = "fa") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_token_classifier_persian_ner_pipeline", lang = "fa") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_token_classifier_persian_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fa| +|Size:|282.4 MB| + +## References + +https://huggingface.co/HooshvareLab/distilbert-fa-zwnj-base-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_uncased_finetuned_cyberbullying_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_uncased_finetuned_cyberbullying_en.md new file mode 100644 index 00000000000000..f1b776b8f8eaae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_uncased_finetuned_cyberbullying_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_uncased_finetuned_cyberbullying DistilBertForSequenceClassification from SSEF-HG-AC +author: John Snow Labs +name: distilbert_uncased_finetuned_cyberbullying +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_uncased_finetuned_cyberbullying` is a English model originally trained by SSEF-HG-AC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_uncased_finetuned_cyberbullying_en_5.5.0_3.0_1725305519575.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_uncased_finetuned_cyberbullying_en_5.5.0_3.0_1725305519575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_uncased_finetuned_cyberbullying","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_uncased_finetuned_cyberbullying", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_uncased_finetuned_cyberbullying| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/SSEF-HG-AC/distilbert-uncased-finetuned-cyberbullying \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_uncased_names_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_uncased_names_pipeline_en.md new file mode 100644 index 00000000000000..9f7937453bdb41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_uncased_names_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_uncased_names_pipeline pipeline DistilBertForTokenClassification from jackfriedson +author: John Snow Labs +name: distilbert_uncased_names_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_uncased_names_pipeline` is a English model originally trained by jackfriedson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_uncased_names_pipeline_en_5.5.0_3.0_1725267790267.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_uncased_names_pipeline_en_5.5.0_3.0_1725267790267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_uncased_names_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_uncased_names_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_uncased_names_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/jackfriedson/distilbert-uncased-names + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilroberta_base_rejection_v1_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilroberta_base_rejection_v1_en.md new file mode 100644 index 00000000000000..f398e1f21e4d49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilroberta_base_rejection_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilroberta_base_rejection_v1 RoBertaForSequenceClassification from protectai +author: John Snow Labs +name: distilroberta_base_rejection_v1 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_rejection_v1` is a English model originally trained by protectai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_rejection_v1_en_5.5.0_3.0_1725237579984.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_rejection_v1_en_5.5.0_3.0_1725237579984.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_base_rejection_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_base_rejection_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilroberta_base_rejection_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|309.0 MB| + +## References + +https://huggingface.co/protectai/distilroberta-base-rejection-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilroberta_base_rejection_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilroberta_base_rejection_v1_pipeline_en.md new file mode 100644 index 00000000000000..3a231df97e758b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilroberta_base_rejection_v1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilroberta_base_rejection_v1_pipeline pipeline RoBertaForSequenceClassification from protectai +author: John Snow Labs +name: distilroberta_base_rejection_v1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_rejection_v1_pipeline` is a English model originally trained by protectai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_rejection_v1_pipeline_en_5.5.0_3.0_1725237596395.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_rejection_v1_pipeline_en_5.5.0_3.0_1725237596395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilroberta_base_rejection_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilroberta_base_rejection_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilroberta_base_rejection_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|309.1 MB| + +## References + +https://huggingface.co/protectai/distilroberta-base-rejection-v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilroberta_finetuned_eli5_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilroberta_finetuned_eli5_en.md new file mode 100644 index 00000000000000..dbf755a3a02306 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilroberta_finetuned_eli5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilroberta_finetuned_eli5 RoBertaEmbeddings from ashaduzzaman +author: John Snow Labs +name: distilroberta_finetuned_eli5 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_finetuned_eli5` is a English model originally trained by ashaduzzaman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_finetuned_eli5_en_5.5.0_3.0_1725264739485.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_finetuned_eli5_en_5.5.0_3.0_1725264739485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("distilroberta_finetuned_eli5","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("distilroberta_finetuned_eli5","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilroberta_finetuned_eli5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|306.5 MB| + +## References + +https://huggingface.co/ashaduzzaman/distilroberta-finetuned-eli5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilroberta_finetuned_eli5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilroberta_finetuned_eli5_pipeline_en.md new file mode 100644 index 00000000000000..46a95c34114360 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-distilroberta_finetuned_eli5_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilroberta_finetuned_eli5_pipeline pipeline RoBertaEmbeddings from ashaduzzaman +author: John Snow Labs +name: distilroberta_finetuned_eli5_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_finetuned_eli5_pipeline` is a English model originally trained by ashaduzzaman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_finetuned_eli5_pipeline_en_5.5.0_3.0_1725264758927.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_finetuned_eli5_pipeline_en_5.5.0_3.0_1725264758927.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilroberta_finetuned_eli5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilroberta_finetuned_eli5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilroberta_finetuned_eli5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|306.5 MB| + +## References + +https://huggingface.co/ashaduzzaman/distilroberta-finetuned-eli5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-drone_severity_embedding_en.md b/docs/_posts/ahmedlone127/2024-09-02-drone_severity_embedding_en.md new file mode 100644 index 00000000000000..833e2285c9b833 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-drone_severity_embedding_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English drone_severity_embedding MPNetEmbeddings from swardiantara +author: John Snow Labs +name: drone_severity_embedding +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`drone_severity_embedding` is a English model originally trained by swardiantara. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/drone_severity_embedding_en_5.5.0_3.0_1725313578840.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/drone_severity_embedding_en_5.5.0_3.0_1725313578840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("drone_severity_embedding","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("drone_severity_embedding","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|drone_severity_embedding| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/swardiantara/drone-severity-embedding \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-drone_severity_embedding_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-drone_severity_embedding_pipeline_en.md new file mode 100644 index 00000000000000..14678c636e6de9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-drone_severity_embedding_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English drone_severity_embedding_pipeline pipeline MPNetEmbeddings from swardiantara +author: John Snow Labs +name: drone_severity_embedding_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`drone_severity_embedding_pipeline` is a English model originally trained by swardiantara. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/drone_severity_embedding_pipeline_en_5.5.0_3.0_1725313602821.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/drone_severity_embedding_pipeline_en_5.5.0_3.0_1725313602821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("drone_severity_embedding_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("drone_severity_embedding_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|drone_severity_embedding_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/swardiantara/drone-severity-embedding + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_camembert_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_camembert_en.md new file mode 100644 index 00000000000000..6f490688903a36 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_camembert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_camembert CamemBertEmbeddings from vonewman +author: John Snow Labs +name: dummy_camembert +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_camembert` is a English model originally trained by vonewman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_camembert_en_5.5.0_3.0_1725301993949.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_camembert_en_5.5.0_3.0_1725301993949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_camembert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_camembert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_camembert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/vonewman/dummy-camembert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_2024_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_2024_en.md new file mode 100644 index 00000000000000..8c822d80e0d0c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_2024_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_2024 CamemBertEmbeddings from Justin-2024 +author: John Snow Labs +name: dummy_model_2024 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_2024` is a English model originally trained by Justin-2024. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_2024_en_5.5.0_3.0_1725303084187.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_2024_en_5.5.0_3.0_1725303084187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_2024","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_2024","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_2024| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Justin-2024/dummy-model-2024 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_2024_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_2024_pipeline_en.md new file mode 100644 index 00000000000000..f07e4155d3460f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_2024_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_2024_pipeline pipeline CamemBertEmbeddings from Justin-2024 +author: John Snow Labs +name: dummy_model_2024_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_2024_pipeline` is a English model originally trained by Justin-2024. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_2024_pipeline_en_5.5.0_3.0_1725303162968.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_2024_pipeline_en_5.5.0_3.0_1725303162968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_2024_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_2024_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_2024_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Justin-2024/dummy-model-2024 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_adam1224_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_adam1224_pipeline_en.md new file mode 100644 index 00000000000000..ee7e73a0a333c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_adam1224_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_adam1224_pipeline pipeline CamemBertEmbeddings from adam1224 +author: John Snow Labs +name: dummy_model_adam1224_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_adam1224_pipeline` is a English model originally trained by adam1224. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_adam1224_pipeline_en_5.5.0_3.0_1725320307342.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_adam1224_pipeline_en_5.5.0_3.0_1725320307342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_adam1224_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_adam1224_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_adam1224_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/adam1224/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ahgadji_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ahgadji_en.md new file mode 100644 index 00000000000000..2784ecc8a4b3b5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ahgadji_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_ahgadji CamemBertEmbeddings from ahGadji +author: John Snow Labs +name: dummy_model_ahgadji +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ahgadji` is a English model originally trained by ahGadji. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ahgadji_en_5.5.0_3.0_1725320600840.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ahgadji_en_5.5.0_3.0_1725320600840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_ahgadji","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ahgadji","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_ahgadji| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/ahGadji/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ahgadji_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ahgadji_pipeline_en.md new file mode 100644 index 00000000000000..bbea011939d78f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ahgadji_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_ahgadji_pipeline pipeline CamemBertEmbeddings from ahGadji +author: John Snow Labs +name: dummy_model_ahgadji_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ahgadji_pipeline` is a English model originally trained by ahGadji. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ahgadji_pipeline_en_5.5.0_3.0_1725320678937.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ahgadji_pipeline_en_5.5.0_3.0_1725320678937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_ahgadji_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_ahgadji_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_ahgadji_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/ahGadji/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_akshatupadhyay_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_akshatupadhyay_pipeline_en.md new file mode 100644 index 00000000000000..7a8ae557dcf36c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_akshatupadhyay_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_akshatupadhyay_pipeline pipeline CamemBertEmbeddings from akshatupadhyay +author: John Snow Labs +name: dummy_model_akshatupadhyay_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_akshatupadhyay_pipeline` is a English model originally trained by akshatupadhyay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_akshatupadhyay_pipeline_en_5.5.0_3.0_1725299710069.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_akshatupadhyay_pipeline_en_5.5.0_3.0_1725299710069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_akshatupadhyay_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_akshatupadhyay_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_akshatupadhyay_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/akshatupadhyay/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_alirezatalakoobi_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_alirezatalakoobi_en.md new file mode 100644 index 00000000000000..a1a0c353ec765a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_alirezatalakoobi_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_alirezatalakoobi CamemBertEmbeddings from alirezatalakoobi +author: John Snow Labs +name: dummy_model_alirezatalakoobi +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_alirezatalakoobi` is a English model originally trained by alirezatalakoobi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_alirezatalakoobi_en_5.5.0_3.0_1725300261308.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_alirezatalakoobi_en_5.5.0_3.0_1725300261308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_alirezatalakoobi","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_alirezatalakoobi","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_alirezatalakoobi| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/alirezatalakoobi/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_almova_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_almova_en.md new file mode 100644 index 00000000000000..3edab3603ea23e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_almova_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_almova CamemBertEmbeddings from Almova +author: John Snow Labs +name: dummy_model_almova +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_almova` is a English model originally trained by Almova. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_almova_en_5.5.0_3.0_1725302633777.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_almova_en_5.5.0_3.0_1725302633777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_almova","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_almova","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_almova| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Almova/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_almova_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_almova_pipeline_en.md new file mode 100644 index 00000000000000..0fd55d89a71c94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_almova_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_almova_pipeline pipeline CamemBertEmbeddings from Almova +author: John Snow Labs +name: dummy_model_almova_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_almova_pipeline` is a English model originally trained by Almova. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_almova_pipeline_en_5.5.0_3.0_1725302712494.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_almova_pipeline_en_5.5.0_3.0_1725302712494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_almova_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_almova_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_almova_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Almova/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ameer05_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ameer05_en.md new file mode 100644 index 00000000000000..e77be99e3206bf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ameer05_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_ameer05 CamemBertEmbeddings from Ameer05 +author: John Snow Labs +name: dummy_model_ameer05 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ameer05` is a English model originally trained by Ameer05. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ameer05_en_5.5.0_3.0_1725297877665.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ameer05_en_5.5.0_3.0_1725297877665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_ameer05","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ameer05","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_ameer05| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Ameer05/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_andreibelousov_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_andreibelousov_en.md new file mode 100644 index 00000000000000..01dca5ea905d96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_andreibelousov_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_andreibelousov CamemBertEmbeddings from AndreiBelousov +author: John Snow Labs +name: dummy_model_andreibelousov +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_andreibelousov` is a English model originally trained by AndreiBelousov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_andreibelousov_en_5.5.0_3.0_1725296459821.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_andreibelousov_en_5.5.0_3.0_1725296459821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_andreibelousov","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_andreibelousov","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_andreibelousov| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/AndreiBelousov/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_andreibelousov_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_andreibelousov_pipeline_en.md new file mode 100644 index 00000000000000..794aa78cc63a5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_andreibelousov_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_andreibelousov_pipeline pipeline CamemBertEmbeddings from AndreiBelousov +author: John Snow Labs +name: dummy_model_andreibelousov_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_andreibelousov_pipeline` is a English model originally trained by AndreiBelousov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_andreibelousov_pipeline_en_5.5.0_3.0_1725296538246.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_andreibelousov_pipeline_en_5.5.0_3.0_1725296538246.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_andreibelousov_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_andreibelousov_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_andreibelousov_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/AndreiBelousov/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ankitkupadhyay_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ankitkupadhyay_pipeline_en.md new file mode 100644 index 00000000000000..abbf2af0516514 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ankitkupadhyay_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_ankitkupadhyay_pipeline pipeline CamemBertEmbeddings from ankitkupadhyay +author: John Snow Labs +name: dummy_model_ankitkupadhyay_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ankitkupadhyay_pipeline` is a English model originally trained by ankitkupadhyay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ankitkupadhyay_pipeline_en_5.5.0_3.0_1725302519362.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ankitkupadhyay_pipeline_en_5.5.0_3.0_1725302519362.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_ankitkupadhyay_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_ankitkupadhyay_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_ankitkupadhyay_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/ankitkupadhyay/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ankush_chander_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ankush_chander_en.md new file mode 100644 index 00000000000000..c2b6001a8c213d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ankush_chander_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_ankush_chander CamemBertEmbeddings from Ankush-Chander +author: John Snow Labs +name: dummy_model_ankush_chander +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ankush_chander` is a English model originally trained by Ankush-Chander. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ankush_chander_en_5.5.0_3.0_1725320692854.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ankush_chander_en_5.5.0_3.0_1725320692854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_ankush_chander","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ankush_chander","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_ankush_chander| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Ankush-Chander/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_arushi151_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_arushi151_pipeline_en.md new file mode 100644 index 00000000000000..6f2d140c9772a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_arushi151_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_arushi151_pipeline pipeline CamemBertEmbeddings from Arushi151 +author: John Snow Labs +name: dummy_model_arushi151_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_arushi151_pipeline` is a English model originally trained by Arushi151. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_arushi151_pipeline_en_5.5.0_3.0_1725300542856.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_arushi151_pipeline_en_5.5.0_3.0_1725300542856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_arushi151_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_arushi151_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_arushi151_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Arushi151/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_banbiossa_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_banbiossa_en.md new file mode 100644 index 00000000000000..ddd9f2b2a5b7e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_banbiossa_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_banbiossa CamemBertEmbeddings from banbiossa +author: John Snow Labs +name: dummy_model_banbiossa +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_banbiossa` is a English model originally trained by banbiossa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_banbiossa_en_5.5.0_3.0_1725296638806.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_banbiossa_en_5.5.0_3.0_1725296638806.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_banbiossa","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_banbiossa","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_banbiossa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/banbiossa/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_banbiossa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_banbiossa_pipeline_en.md new file mode 100644 index 00000000000000..bf7cfe428e7f01 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_banbiossa_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_banbiossa_pipeline pipeline CamemBertEmbeddings from banbiossa +author: John Snow Labs +name: dummy_model_banbiossa_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_banbiossa_pipeline` is a English model originally trained by banbiossa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_banbiossa_pipeline_en_5.5.0_3.0_1725296717483.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_banbiossa_pipeline_en_5.5.0_3.0_1725296717483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_banbiossa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_banbiossa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_banbiossa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/banbiossa/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bishgupp_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bishgupp_en.md new file mode 100644 index 00000000000000..cddb828aa5231e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bishgupp_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_bishgupp CamemBertEmbeddings from bishgupp +author: John Snow Labs +name: dummy_model_bishgupp +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_bishgupp` is a English model originally trained by bishgupp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_bishgupp_en_5.5.0_3.0_1725299512032.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_bishgupp_en_5.5.0_3.0_1725299512032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_bishgupp","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_bishgupp","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_bishgupp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/bishgupp/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bishgupp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bishgupp_pipeline_en.md new file mode 100644 index 00000000000000..2f45eaba4cdc51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bishgupp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_bishgupp_pipeline pipeline CamemBertEmbeddings from bishgupp +author: John Snow Labs +name: dummy_model_bishgupp_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_bishgupp_pipeline` is a English model originally trained by bishgupp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_bishgupp_pipeline_en_5.5.0_3.0_1725299592518.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_bishgupp_pipeline_en_5.5.0_3.0_1725299592518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_bishgupp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_bishgupp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_bishgupp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/bishgupp/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bucktrends_fr.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bucktrends_fr.md new file mode 100644 index 00000000000000..3d67bf6cb2f600 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bucktrends_fr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: French dummy_model_bucktrends CamemBertEmbeddings from bucktrends +author: John Snow Labs +name: dummy_model_bucktrends +date: 2024-09-02 +tags: [fr, open_source, onnx, embeddings, camembert] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_bucktrends` is a French model originally trained by bucktrends. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_bucktrends_fr_5.5.0_3.0_1725297940442.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_bucktrends_fr_5.5.0_3.0_1725297940442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_bucktrends","fr") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_bucktrends","fr") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_bucktrends| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|fr| +|Size:|264.0 MB| + +## References + +https://huggingface.co/bucktrends/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bugpie_fr.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bugpie_fr.md new file mode 100644 index 00000000000000..ea91697d0bd6a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bugpie_fr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: French dummy_model_bugpie CamemBertEmbeddings from Bugpie +author: John Snow Labs +name: dummy_model_bugpie +date: 2024-09-02 +tags: [fr, open_source, onnx, embeddings, camembert] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_bugpie` is a French model originally trained by Bugpie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_bugpie_fr_5.5.0_3.0_1725300703938.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_bugpie_fr_5.5.0_3.0_1725300703938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_bugpie","fr") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_bugpie","fr") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_bugpie| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|fr| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Bugpie/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bugpie_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bugpie_pipeline_fr.md new file mode 100644 index 00000000000000..65ecf868fb5251 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bugpie_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French dummy_model_bugpie_pipeline pipeline CamemBertEmbeddings from Bugpie +author: John Snow Labs +name: dummy_model_bugpie_pipeline +date: 2024-09-02 +tags: [fr, open_source, pipeline, onnx] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_bugpie_pipeline` is a French model originally trained by Bugpie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_bugpie_pipeline_fr_5.5.0_3.0_1725300782359.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_bugpie_pipeline_fr_5.5.0_3.0_1725300782359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_bugpie_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_bugpie_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_bugpie_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Bugpie/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_chetang_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_chetang_en.md new file mode 100644 index 00000000000000..0b63af11c8d1fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_chetang_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_chetang CamemBertEmbeddings from chetang +author: John Snow Labs +name: dummy_model_chetang +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_chetang` is a English model originally trained by chetang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_chetang_en_5.5.0_3.0_1725301994093.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_chetang_en_5.5.0_3.0_1725301994093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_chetang","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_chetang","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_chetang| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/chetang/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_chetang_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_chetang_pipeline_en.md new file mode 100644 index 00000000000000..8485c781296772 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_chetang_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_chetang_pipeline pipeline CamemBertEmbeddings from chetang +author: John Snow Labs +name: dummy_model_chetang_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_chetang_pipeline` is a English model originally trained by chetang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_chetang_pipeline_en_5.5.0_3.0_1725302075728.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_chetang_pipeline_en_5.5.0_3.0_1725302075728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_chetang_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_chetang_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_chetang_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/chetang/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_data_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_data_en.md new file mode 100644 index 00000000000000..cbe6ffdec20cf4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_data_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_data CamemBertEmbeddings from Yasira +author: John Snow Labs +name: dummy_model_data +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_data` is a English model originally trained by Yasira. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_data_en_5.5.0_3.0_1725302660775.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_data_en_5.5.0_3.0_1725302660775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_data","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_data","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_data| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Yasira/dummy-model-data \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_data_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_data_pipeline_en.md new file mode 100644 index 00000000000000..469ca191adf624 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_data_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_data_pipeline pipeline CamemBertEmbeddings from Yasira +author: John Snow Labs +name: dummy_model_data_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_data_pipeline` is a English model originally trained by Yasira. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_data_pipeline_en_5.5.0_3.0_1725302739505.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_data_pipeline_en_5.5.0_3.0_1725302739505.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_data_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_data_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_data_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Yasira/dummy-model-data + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ddaannee_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ddaannee_en.md new file mode 100644 index 00000000000000..411028da1e017a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ddaannee_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_ddaannee CamemBertEmbeddings from ddaannee +author: John Snow Labs +name: dummy_model_ddaannee +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ddaannee` is a English model originally trained by ddaannee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ddaannee_en_5.5.0_3.0_1725300768289.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ddaannee_en_5.5.0_3.0_1725300768289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_ddaannee","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ddaannee","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_ddaannee| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/ddaannee/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ddaannee_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ddaannee_pipeline_en.md new file mode 100644 index 00000000000000..dd0c43cd0f12e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ddaannee_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_ddaannee_pipeline pipeline CamemBertEmbeddings from ddaannee +author: John Snow Labs +name: dummy_model_ddaannee_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ddaannee_pipeline` is a English model originally trained by ddaannee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ddaannee_pipeline_en_5.5.0_3.0_1725300844660.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ddaannee_pipeline_en_5.5.0_3.0_1725300844660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_ddaannee_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_ddaannee_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_ddaannee_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/ddaannee/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_delayedkarma_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_delayedkarma_en.md new file mode 100644 index 00000000000000..578dc699ec8e90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_delayedkarma_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_delayedkarma CamemBertEmbeddings from delayedkarma +author: John Snow Labs +name: dummy_model_delayedkarma +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_delayedkarma` is a English model originally trained by delayedkarma. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_delayedkarma_en_5.5.0_3.0_1725319855373.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_delayedkarma_en_5.5.0_3.0_1725319855373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_delayedkarma","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_delayedkarma","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_delayedkarma| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/delayedkarma/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_delayedkarma_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_delayedkarma_pipeline_en.md new file mode 100644 index 00000000000000..07d3922c7fe752 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_delayedkarma_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_delayedkarma_pipeline pipeline CamemBertEmbeddings from delayedkarma +author: John Snow Labs +name: dummy_model_delayedkarma_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_delayedkarma_pipeline` is a English model originally trained by delayedkarma. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_delayedkarma_pipeline_en_5.5.0_3.0_1725319933678.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_delayedkarma_pipeline_en_5.5.0_3.0_1725319933678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_delayedkarma_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_delayedkarma_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_delayedkarma_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/delayedkarma/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_deva2_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_deva2_en.md new file mode 100644 index 00000000000000..c48a921d58ed5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_deva2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_deva2 CamemBertEmbeddings from Deva2 +author: John Snow Labs +name: dummy_model_deva2 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_deva2` is a English model originally trained by Deva2. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_deva2_en_5.5.0_3.0_1725302895902.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_deva2_en_5.5.0_3.0_1725302895902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_deva2","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_deva2","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_deva2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Deva2/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_deva2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_deva2_pipeline_en.md new file mode 100644 index 00000000000000..439c13ca1dcea5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_deva2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_deva2_pipeline pipeline CamemBertEmbeddings from Deva2 +author: John Snow Labs +name: dummy_model_deva2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_deva2_pipeline` is a English model originally trained by Deva2. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_deva2_pipeline_en_5.5.0_3.0_1725302974802.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_deva2_pipeline_en_5.5.0_3.0_1725302974802.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_deva2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_deva2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_deva2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Deva2/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_dianeshan_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_dianeshan_en.md new file mode 100644 index 00000000000000..e42831e79e17a1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_dianeshan_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_dianeshan CamemBertEmbeddings from dianeshan +author: John Snow Labs +name: dummy_model_dianeshan +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_dianeshan` is a English model originally trained by dianeshan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_dianeshan_en_5.5.0_3.0_1725320455562.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_dianeshan_en_5.5.0_3.0_1725320455562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_dianeshan","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_dianeshan","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_dianeshan| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/dianeshan/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_dianeshan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_dianeshan_pipeline_en.md new file mode 100644 index 00000000000000..4b4b72ba05c52d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_dianeshan_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_dianeshan_pipeline pipeline CamemBertEmbeddings from dianeshan +author: John Snow Labs +name: dummy_model_dianeshan_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_dianeshan_pipeline` is a English model originally trained by dianeshan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_dianeshan_pipeline_en_5.5.0_3.0_1725320532670.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_dianeshan_pipeline_en_5.5.0_3.0_1725320532670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_dianeshan_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_dianeshan_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_dianeshan_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/dianeshan/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_e99y_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_e99y_en.md new file mode 100644 index 00000000000000..9b025a29c43013 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_e99y_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_e99y CamemBertEmbeddings from E99y +author: John Snow Labs +name: dummy_model_e99y +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_e99y` is a English model originally trained by E99y. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_e99y_en_5.5.0_3.0_1725303140863.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_e99y_en_5.5.0_3.0_1725303140863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_e99y","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_e99y","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_e99y| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/E99y/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_e99y_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_e99y_pipeline_en.md new file mode 100644 index 00000000000000..40d0ee0cfd2547 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_e99y_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_e99y_pipeline pipeline CamemBertEmbeddings from E99y +author: John Snow Labs +name: dummy_model_e99y_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_e99y_pipeline` is a English model originally trained by E99y. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_e99y_pipeline_en_5.5.0_3.0_1725303218854.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_e99y_pipeline_en_5.5.0_3.0_1725303218854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_e99y_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_e99y_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_e99y_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/E99y/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_giodeleo_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_giodeleo_en.md new file mode 100644 index 00000000000000..82ccb42e82421b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_giodeleo_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_giodeleo CamemBertEmbeddings from giodeleo +author: John Snow Labs +name: dummy_model_giodeleo +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_giodeleo` is a English model originally trained by giodeleo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_giodeleo_en_5.5.0_3.0_1725303032044.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_giodeleo_en_5.5.0_3.0_1725303032044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_giodeleo","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_giodeleo","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_giodeleo| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/giodeleo/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_giodeleo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_giodeleo_pipeline_en.md new file mode 100644 index 00000000000000..536309ba59e174 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_giodeleo_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_giodeleo_pipeline pipeline CamemBertEmbeddings from giodeleo +author: John Snow Labs +name: dummy_model_giodeleo_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_giodeleo_pipeline` is a English model originally trained by giodeleo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_giodeleo_pipeline_en_5.5.0_3.0_1725303110682.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_giodeleo_pipeline_en_5.5.0_3.0_1725303110682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_giodeleo_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_giodeleo_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_giodeleo_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/giodeleo/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_heartlocket_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_heartlocket_pipeline_en.md new file mode 100644 index 00000000000000..c25febfb2cf4a3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_heartlocket_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_heartlocket_pipeline pipeline CamemBertEmbeddings from heartlocket +author: John Snow Labs +name: dummy_model_heartlocket_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_heartlocket_pipeline` is a English model originally trained by heartlocket. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_heartlocket_pipeline_en_5.5.0_3.0_1725296949427.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_heartlocket_pipeline_en_5.5.0_3.0_1725296949427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_heartlocket_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_heartlocket_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_heartlocket_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/heartlocket/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_hironon_actiphy_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_hironon_actiphy_en.md new file mode 100644 index 00000000000000..2bb716d4f17363 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_hironon_actiphy_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_hironon_actiphy CamemBertEmbeddings from hironon-actiphy +author: John Snow Labs +name: dummy_model_hironon_actiphy +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hironon_actiphy` is a English model originally trained by hironon-actiphy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hironon_actiphy_en_5.5.0_3.0_1725297112132.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hironon_actiphy_en_5.5.0_3.0_1725297112132.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_hironon_actiphy","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_hironon_actiphy","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_hironon_actiphy| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/hironon-actiphy/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_hironon_actiphy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_hironon_actiphy_pipeline_en.md new file mode 100644 index 00000000000000..2174d75ea01486 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_hironon_actiphy_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_hironon_actiphy_pipeline pipeline CamemBertEmbeddings from hironon-actiphy +author: John Snow Labs +name: dummy_model_hironon_actiphy_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hironon_actiphy_pipeline` is a English model originally trained by hironon-actiphy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hironon_actiphy_pipeline_en_5.5.0_3.0_1725297190384.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hironon_actiphy_pipeline_en_5.5.0_3.0_1725297190384.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_hironon_actiphy_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_hironon_actiphy_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_hironon_actiphy_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/hironon-actiphy/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_iryska_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_iryska_en.md new file mode 100644 index 00000000000000..beaa3a871f914a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_iryska_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_iryska CamemBertEmbeddings from iryska +author: John Snow Labs +name: dummy_model_iryska +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_iryska` is a English model originally trained by iryska. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_iryska_en_5.5.0_3.0_1725302866284.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_iryska_en_5.5.0_3.0_1725302866284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_iryska","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_iryska","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_iryska| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/iryska/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_iryska_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_iryska_pipeline_en.md new file mode 100644 index 00000000000000..60967c3fd00637 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_iryska_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_iryska_pipeline pipeline CamemBertEmbeddings from iryska +author: John Snow Labs +name: dummy_model_iryska_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_iryska_pipeline` is a English model originally trained by iryska. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_iryska_pipeline_en_5.5.0_3.0_1725302943879.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_iryska_pipeline_en_5.5.0_3.0_1725302943879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_iryska_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_iryska_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_iryska_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/iryska/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jamaya_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jamaya_en.md new file mode 100644 index 00000000000000..9654f4aac06fbd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jamaya_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_jamaya CamemBertEmbeddings from jamaya +author: John Snow Labs +name: dummy_model_jamaya +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jamaya` is a English model originally trained by jamaya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jamaya_en_5.5.0_3.0_1725299866650.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jamaya_en_5.5.0_3.0_1725299866650.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_jamaya","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jamaya","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jamaya| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/jamaya/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jamaya_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jamaya_pipeline_en.md new file mode 100644 index 00000000000000..9807c03a80f2a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jamaya_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_jamaya_pipeline pipeline CamemBertEmbeddings from jamaya +author: John Snow Labs +name: dummy_model_jamaya_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jamaya_pipeline` is a English model originally trained by jamaya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jamaya_pipeline_en_5.5.0_3.0_1725299944973.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jamaya_pipeline_en_5.5.0_3.0_1725299944973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_jamaya_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_jamaya_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jamaya_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/jamaya/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jbern29_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jbern29_pipeline_en.md new file mode 100644 index 00000000000000..f924b661e7c88e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jbern29_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_jbern29_pipeline pipeline CamemBertEmbeddings from JBERN29 +author: John Snow Labs +name: dummy_model_jbern29_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jbern29_pipeline` is a English model originally trained by JBERN29. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jbern29_pipeline_en_5.5.0_3.0_1725299593057.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jbern29_pipeline_en_5.5.0_3.0_1725299593057.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_jbern29_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_jbern29_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jbern29_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/JBERN29/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jcai1_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jcai1_en.md new file mode 100644 index 00000000000000..3dcc2ec35bb160 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jcai1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_jcai1 CamemBertEmbeddings from jcai1 +author: John Snow Labs +name: dummy_model_jcai1 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jcai1` is a English model originally trained by jcai1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jcai1_en_5.5.0_3.0_1725297718155.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jcai1_en_5.5.0_3.0_1725297718155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_jcai1","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jcai1","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jcai1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/jcai1/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jcai1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jcai1_pipeline_en.md new file mode 100644 index 00000000000000..c8032beedf78f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jcai1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_jcai1_pipeline pipeline CamemBertEmbeddings from jcai1 +author: John Snow Labs +name: dummy_model_jcai1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jcai1_pipeline` is a English model originally trained by jcai1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jcai1_pipeline_en_5.5.0_3.0_1725297795360.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jcai1_pipeline_en_5.5.0_3.0_1725297795360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_jcai1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_jcai1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jcai1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/jcai1/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jeeday_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jeeday_en.md new file mode 100644 index 00000000000000..248e339c366541 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jeeday_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_jeeday CamemBertEmbeddings from JeeDay +author: John Snow Labs +name: dummy_model_jeeday +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jeeday` is a English model originally trained by JeeDay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jeeday_en_5.5.0_3.0_1725299746420.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jeeday_en_5.5.0_3.0_1725299746420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_jeeday","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jeeday","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jeeday| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/JeeDay/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jelly_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jelly_en.md new file mode 100644 index 00000000000000..78ecccf339f4b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jelly_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_jelly CamemBertEmbeddings from Jelly +author: John Snow Labs +name: dummy_model_jelly +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jelly` is a English model originally trained by Jelly. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jelly_en_5.5.0_3.0_1725299735836.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jelly_en_5.5.0_3.0_1725299735836.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_jelly","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jelly","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jelly| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Jelly/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jelly_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jelly_pipeline_en.md new file mode 100644 index 00000000000000..fb067794b469c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jelly_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_jelly_pipeline pipeline CamemBertEmbeddings from Jelly +author: John Snow Labs +name: dummy_model_jelly_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jelly_pipeline` is a English model originally trained by Jelly. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jelly_pipeline_en_5.5.0_3.0_1725299814796.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jelly_pipeline_en_5.5.0_3.0_1725299814796.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_jelly_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_jelly_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jelly_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Jelly/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jlasam_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jlasam_en.md new file mode 100644 index 00000000000000..e6268c591591fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jlasam_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_jlasam CamemBertEmbeddings from jlasam +author: John Snow Labs +name: dummy_model_jlasam +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jlasam` is a English model originally trained by jlasam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jlasam_en_5.5.0_3.0_1725297374039.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jlasam_en_5.5.0_3.0_1725297374039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_jlasam","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jlasam","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jlasam| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/jlasam/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jlasam_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jlasam_pipeline_en.md new file mode 100644 index 00000000000000..b9900f17185747 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jlasam_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_jlasam_pipeline pipeline CamemBertEmbeddings from jlasam +author: John Snow Labs +name: dummy_model_jlasam_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jlasam_pipeline` is a English model originally trained by jlasam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jlasam_pipeline_en_5.5.0_3.0_1725297452606.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jlasam_pipeline_en_5.5.0_3.0_1725297452606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_jlasam_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_jlasam_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jlasam_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/jlasam/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_joe8zhang_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_joe8zhang_en.md new file mode 100644 index 00000000000000..8f6a0fe2f02c10 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_joe8zhang_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_joe8zhang CamemBertEmbeddings from joe8zhang +author: John Snow Labs +name: dummy_model_joe8zhang +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_joe8zhang` is a English model originally trained by joe8zhang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_joe8zhang_en_5.5.0_3.0_1725300693245.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_joe8zhang_en_5.5.0_3.0_1725300693245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_joe8zhang","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_joe8zhang","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_joe8zhang| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/joe8zhang/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jonathanlin0707_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jonathanlin0707_en.md new file mode 100644 index 00000000000000..9d789fa40329b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jonathanlin0707_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_jonathanlin0707 CamemBertEmbeddings from JonathanLin0707 +author: John Snow Labs +name: dummy_model_jonathanlin0707 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jonathanlin0707` is a English model originally trained by JonathanLin0707. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jonathanlin0707_en_5.5.0_3.0_1725297592612.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jonathanlin0707_en_5.5.0_3.0_1725297592612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_jonathanlin0707","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jonathanlin0707","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jonathanlin0707| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/JonathanLin0707/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jongyeop_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jongyeop_pipeline_en.md new file mode 100644 index 00000000000000..b7e20cd25def6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jongyeop_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_jongyeop_pipeline pipeline CamemBertEmbeddings from JongYeop +author: John Snow Labs +name: dummy_model_jongyeop_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jongyeop_pipeline` is a English model originally trained by JongYeop. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jongyeop_pipeline_en_5.5.0_3.0_1725300524588.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jongyeop_pipeline_en_5.5.0_3.0_1725300524588.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_jongyeop_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_jongyeop_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jongyeop_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/JongYeop/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jwchung_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jwchung_en.md new file mode 100644 index 00000000000000..576281dc779dee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jwchung_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_jwchung CamemBertEmbeddings from jwchung +author: John Snow Labs +name: dummy_model_jwchung +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jwchung` is a English model originally trained by jwchung. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jwchung_en_5.5.0_3.0_1725297516798.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jwchung_en_5.5.0_3.0_1725297516798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_jwchung","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jwchung","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jwchung| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/jwchung/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jzzcutler_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jzzcutler_en.md new file mode 100644 index 00000000000000..6a329a48de8b83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jzzcutler_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_jzzcutler CamemBertEmbeddings from jzzcutler +author: John Snow Labs +name: dummy_model_jzzcutler +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jzzcutler` is a English model originally trained by jzzcutler. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jzzcutler_en_5.5.0_3.0_1725320907448.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jzzcutler_en_5.5.0_3.0_1725320907448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_jzzcutler","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jzzcutler","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jzzcutler| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/jzzcutler/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jzzcutler_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jzzcutler_pipeline_en.md new file mode 100644 index 00000000000000..eaa8a05ec6045f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jzzcutler_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_jzzcutler_pipeline pipeline CamemBertEmbeddings from jzzcutler +author: John Snow Labs +name: dummy_model_jzzcutler_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jzzcutler_pipeline` is a English model originally trained by jzzcutler. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jzzcutler_pipeline_en_5.5.0_3.0_1725320983334.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jzzcutler_pipeline_en_5.5.0_3.0_1725320983334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_jzzcutler_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_jzzcutler_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jzzcutler_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/jzzcutler/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_katrin_kc_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_katrin_kc_en.md new file mode 100644 index 00000000000000..d1190675fd3897 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_katrin_kc_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_katrin_kc CamemBertEmbeddings from katrin-kc +author: John Snow Labs +name: dummy_model_katrin_kc +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_katrin_kc` is a English model originally trained by katrin-kc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_katrin_kc_en_5.5.0_3.0_1725299902467.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_katrin_kc_en_5.5.0_3.0_1725299902467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_katrin_kc","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_katrin_kc","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_katrin_kc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/katrin-kc/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_katrin_kc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_katrin_kc_pipeline_en.md new file mode 100644 index 00000000000000..40cab98e273671 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_katrin_kc_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_katrin_kc_pipeline pipeline CamemBertEmbeddings from katrin-kc +author: John Snow Labs +name: dummy_model_katrin_kc_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_katrin_kc_pipeline` is a English model originally trained by katrin-kc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_katrin_kc_pipeline_en_5.5.0_3.0_1725299980543.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_katrin_kc_pipeline_en_5.5.0_3.0_1725299980543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_katrin_kc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_katrin_kc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_katrin_kc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/katrin-kc/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_kprashanth_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_kprashanth_pipeline_en.md new file mode 100644 index 00000000000000..1edef188d9b9e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_kprashanth_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_kprashanth_pipeline pipeline CamemBertEmbeddings from KPrashanth +author: John Snow Labs +name: dummy_model_kprashanth_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_kprashanth_pipeline` is a English model originally trained by KPrashanth. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_kprashanth_pipeline_en_5.5.0_3.0_1725300634780.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_kprashanth_pipeline_en_5.5.0_3.0_1725300634780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_kprashanth_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_kprashanth_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_kprashanth_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/KPrashanth/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_lucianodeben_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_lucianodeben_pipeline_en.md new file mode 100644 index 00000000000000..c80424e54e1c45 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_lucianodeben_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_lucianodeben_pipeline pipeline CamemBertEmbeddings from LucianoDeben +author: John Snow Labs +name: dummy_model_lucianodeben_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lucianodeben_pipeline` is a English model originally trained by LucianoDeben. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_lucianodeben_pipeline_en_5.5.0_3.0_1725319871233.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lucianodeben_pipeline_en_5.5.0_3.0_1725319871233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_lucianodeben_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_lucianodeben_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_lucianodeben_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/LucianoDeben/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_lyla_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_lyla_en.md new file mode 100644 index 00000000000000..0a92c11c17aeb2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_lyla_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_lyla CamemBertEmbeddings from Lyla +author: John Snow Labs +name: dummy_model_lyla +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lyla` is a English model originally trained by Lyla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_lyla_en_5.5.0_3.0_1725296645460.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lyla_en_5.5.0_3.0_1725296645460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_lyla","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_lyla","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_lyla| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Lyla/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_lyla_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_lyla_pipeline_en.md new file mode 100644 index 00000000000000..a8d57d45403391 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_lyla_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_lyla_pipeline pipeline CamemBertEmbeddings from Lyla +author: John Snow Labs +name: dummy_model_lyla_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lyla_pipeline` is a English model originally trained by Lyla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_lyla_pipeline_en_5.5.0_3.0_1725296723891.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lyla_pipeline_en_5.5.0_3.0_1725296723891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_lyla_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_lyla_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_lyla_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Lyla/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_marisming_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_marisming_pipeline_en.md new file mode 100644 index 00000000000000..a2c95f681a1d00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_marisming_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_marisming_pipeline pipeline CamemBertEmbeddings from marisming +author: John Snow Labs +name: dummy_model_marisming_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_marisming_pipeline` is a English model originally trained by marisming. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_marisming_pipeline_en_5.5.0_3.0_1725297285371.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_marisming_pipeline_en_5.5.0_3.0_1725297285371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_marisming_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_marisming_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_marisming_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/marisming/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_matthewvedder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_matthewvedder_pipeline_en.md new file mode 100644 index 00000000000000..cbd3a5dc0fca59 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_matthewvedder_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_matthewvedder_pipeline pipeline CamemBertEmbeddings from MatthewVedder +author: John Snow Labs +name: dummy_model_matthewvedder_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_matthewvedder_pipeline` is a English model originally trained by MatthewVedder. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_matthewvedder_pipeline_en_5.5.0_3.0_1725302964068.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_matthewvedder_pipeline_en_5.5.0_3.0_1725302964068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_matthewvedder_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_matthewvedder_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_matthewvedder_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/MatthewVedder/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_mbearss_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_mbearss_pipeline_en.md new file mode 100644 index 00000000000000..dfec112fa79792 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_mbearss_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_mbearss_pipeline pipeline CamemBertEmbeddings from mbearss +author: John Snow Labs +name: dummy_model_mbearss_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_mbearss_pipeline` is a English model originally trained by mbearss. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_mbearss_pipeline_en_5.5.0_3.0_1725296488371.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_mbearss_pipeline_en_5.5.0_3.0_1725296488371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_mbearss_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_mbearss_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_mbearss_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/mbearss/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_nestornav_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_nestornav_en.md new file mode 100644 index 00000000000000..241ae16b37f020 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_nestornav_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_nestornav CamemBertEmbeddings from nestornav +author: John Snow Labs +name: dummy_model_nestornav +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_nestornav` is a English model originally trained by nestornav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_nestornav_en_5.5.0_3.0_1725302112661.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_nestornav_en_5.5.0_3.0_1725302112661.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_nestornav","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_nestornav","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_nestornav| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/nestornav/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_nestornav_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_nestornav_pipeline_en.md new file mode 100644 index 00000000000000..c3ff4e65ac6472 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_nestornav_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_nestornav_pipeline pipeline CamemBertEmbeddings from nestornav +author: John Snow Labs +name: dummy_model_nestornav_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_nestornav_pipeline` is a English model originally trained by nestornav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_nestornav_pipeline_en_5.5.0_3.0_1725302190872.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_nestornav_pipeline_en_5.5.0_3.0_1725302190872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_nestornav_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_nestornav_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_nestornav_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/nestornav/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_neutron_tom_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_neutron_tom_en.md new file mode 100644 index 00000000000000..0683871cc5af26 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_neutron_tom_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_neutron_tom CamemBertEmbeddings from neutron-tom +author: John Snow Labs +name: dummy_model_neutron_tom +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_neutron_tom` is a English model originally trained by neutron-tom. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_neutron_tom_en_5.5.0_3.0_1725297666966.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_neutron_tom_en_5.5.0_3.0_1725297666966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_neutron_tom","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_neutron_tom","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_neutron_tom| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/neutron-tom/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_neutron_tom_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_neutron_tom_pipeline_en.md new file mode 100644 index 00000000000000..3d7e3a46d98742 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_neutron_tom_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_neutron_tom_pipeline pipeline CamemBertEmbeddings from neutron-tom +author: John Snow Labs +name: dummy_model_neutron_tom_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_neutron_tom_pipeline` is a English model originally trained by neutron-tom. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_neutron_tom_pipeline_en_5.5.0_3.0_1725297744949.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_neutron_tom_pipeline_en_5.5.0_3.0_1725297744949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_neutron_tom_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_neutron_tom_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_neutron_tom_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/neutron-tom/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_omenndt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_omenndt_pipeline_en.md new file mode 100644 index 00000000000000..90511ba1bfb1e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_omenndt_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_omenndt_pipeline pipeline CamemBertEmbeddings from OmenNDT +author: John Snow Labs +name: dummy_model_omenndt_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_omenndt_pipeline` is a English model originally trained by OmenNDT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_omenndt_pipeline_en_5.5.0_3.0_1725302728749.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_omenndt_pipeline_en_5.5.0_3.0_1725302728749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_omenndt_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_omenndt_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_omenndt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/OmenNDT/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ozguryilmazel_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ozguryilmazel_en.md new file mode 100644 index 00000000000000..f4c409a1ce3b67 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ozguryilmazel_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_ozguryilmazel CamemBertEmbeddings from ozguryilmazel +author: John Snow Labs +name: dummy_model_ozguryilmazel +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ozguryilmazel` is a English model originally trained by ozguryilmazel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ozguryilmazel_en_5.5.0_3.0_1725302061180.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ozguryilmazel_en_5.5.0_3.0_1725302061180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_ozguryilmazel","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ozguryilmazel","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_ozguryilmazel| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/ozguryilmazel/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ozguryilmazel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ozguryilmazel_pipeline_en.md new file mode 100644 index 00000000000000..99f42b7ade2b0e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ozguryilmazel_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_ozguryilmazel_pipeline pipeline CamemBertEmbeddings from ozguryilmazel +author: John Snow Labs +name: dummy_model_ozguryilmazel_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ozguryilmazel_pipeline` is a English model originally trained by ozguryilmazel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ozguryilmazel_pipeline_en_5.5.0_3.0_1725302140393.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ozguryilmazel_pipeline_en_5.5.0_3.0_1725302140393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_ozguryilmazel_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_ozguryilmazel_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_ozguryilmazel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/ozguryilmazel/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pawankumar_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pawankumar_en.md new file mode 100644 index 00000000000000..41f801e48c0d41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pawankumar_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_pawankumar CamemBertEmbeddings from pawankumar +author: John Snow Labs +name: dummy_model_pawankumar +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_pawankumar` is a English model originally trained by pawankumar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_pawankumar_en_5.5.0_3.0_1725299964891.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_pawankumar_en_5.5.0_3.0_1725299964891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_pawankumar","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_pawankumar","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_pawankumar| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/pawankumar/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pgperrone_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pgperrone_en.md new file mode 100644 index 00000000000000..1ee54d99a8d384 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pgperrone_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_pgperrone CamemBertEmbeddings from pgperrone +author: John Snow Labs +name: dummy_model_pgperrone +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_pgperrone` is a English model originally trained by pgperrone. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_pgperrone_en_5.5.0_3.0_1725297360333.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_pgperrone_en_5.5.0_3.0_1725297360333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_pgperrone","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_pgperrone","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_pgperrone| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/pgperrone/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pgperrone_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pgperrone_pipeline_en.md new file mode 100644 index 00000000000000..6175bee6982a7e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pgperrone_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_pgperrone_pipeline pipeline CamemBertEmbeddings from pgperrone +author: John Snow Labs +name: dummy_model_pgperrone_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_pgperrone_pipeline` is a English model originally trained by pgperrone. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_pgperrone_pipeline_en_5.5.0_3.0_1725297438866.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_pgperrone_pipeline_en_5.5.0_3.0_1725297438866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_pgperrone_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_pgperrone_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_pgperrone_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/pgperrone/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_phamvanlinh143_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_phamvanlinh143_en.md new file mode 100644 index 00000000000000..ae44ed6aff8df6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_phamvanlinh143_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_phamvanlinh143 CamemBertEmbeddings from phamvanlinh143 +author: John Snow Labs +name: dummy_model_phamvanlinh143 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_phamvanlinh143` is a English model originally trained by phamvanlinh143. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_phamvanlinh143_en_5.5.0_3.0_1725296402094.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_phamvanlinh143_en_5.5.0_3.0_1725296402094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_phamvanlinh143","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_phamvanlinh143","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_phamvanlinh143| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/phamvanlinh143/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_phamvanlinh143_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_phamvanlinh143_pipeline_en.md new file mode 100644 index 00000000000000..0b06190238ae6b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_phamvanlinh143_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_phamvanlinh143_pipeline pipeline CamemBertEmbeddings from phamvanlinh143 +author: John Snow Labs +name: dummy_model_phamvanlinh143_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_phamvanlinh143_pipeline` is a English model originally trained by phamvanlinh143. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_phamvanlinh143_pipeline_en_5.5.0_3.0_1725296488120.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_phamvanlinh143_pipeline_en_5.5.0_3.0_1725296488120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_phamvanlinh143_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_phamvanlinh143_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_phamvanlinh143_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/phamvanlinh143/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_plan_9_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_plan_9_en.md new file mode 100644 index 00000000000000..d9526555be1bb4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_plan_9_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_plan_9 CamemBertEmbeddings from Plan-9 +author: John Snow Labs +name: dummy_model_plan_9 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_plan_9` is a English model originally trained by Plan-9. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_plan_9_en_5.5.0_3.0_1725300096803.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_plan_9_en_5.5.0_3.0_1725300096803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_plan_9","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_plan_9","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_plan_9| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Plan-9/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_plan_9_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_plan_9_pipeline_en.md new file mode 100644 index 00000000000000..713a07e3b23434 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_plan_9_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_plan_9_pipeline pipeline CamemBertEmbeddings from Plan-9 +author: John Snow Labs +name: dummy_model_plan_9_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_plan_9_pipeline` is a English model originally trained by Plan-9. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_plan_9_pipeline_en_5.5.0_3.0_1725300174780.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_plan_9_pipeline_en_5.5.0_3.0_1725300174780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_plan_9_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_plan_9_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_plan_9_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Plan-9/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pmontesd_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pmontesd_en.md new file mode 100644 index 00000000000000..d938c9f434d318 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pmontesd_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_pmontesd CamemBertEmbeddings from pmontesd +author: John Snow Labs +name: dummy_model_pmontesd +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_pmontesd` is a English model originally trained by pmontesd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_pmontesd_en_5.5.0_3.0_1725320379732.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_pmontesd_en_5.5.0_3.0_1725320379732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_pmontesd","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_pmontesd","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_pmontesd| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/pmontesd/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pmontesd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pmontesd_pipeline_en.md new file mode 100644 index 00000000000000..fd912e30a8aeac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pmontesd_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_pmontesd_pipeline pipeline CamemBertEmbeddings from pmontesd +author: John Snow Labs +name: dummy_model_pmontesd_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_pmontesd_pipeline` is a English model originally trained by pmontesd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_pmontesd_pipeline_en_5.5.0_3.0_1725320458109.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_pmontesd_pipeline_en_5.5.0_3.0_1725320458109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_pmontesd_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_pmontesd_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_pmontesd_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/pmontesd/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_purnima1201_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_purnima1201_en.md new file mode 100644 index 00000000000000..43704f5cfb4526 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_purnima1201_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_purnima1201 CamemBertEmbeddings from purnima1201 +author: John Snow Labs +name: dummy_model_purnima1201 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_purnima1201` is a English model originally trained by purnima1201. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_purnima1201_en_5.5.0_3.0_1725302547539.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_purnima1201_en_5.5.0_3.0_1725302547539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_purnima1201","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_purnima1201","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_purnima1201| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/purnima1201/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_purnima1201_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_purnima1201_pipeline_en.md new file mode 100644 index 00000000000000..cb9d0bba30d6a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_purnima1201_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_purnima1201_pipeline pipeline CamemBertEmbeddings from purnima1201 +author: John Snow Labs +name: dummy_model_purnima1201_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_purnima1201_pipeline` is a English model originally trained by purnima1201. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_purnima1201_pipeline_en_5.5.0_3.0_1725302626763.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_purnima1201_pipeline_en_5.5.0_3.0_1725302626763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_purnima1201_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_purnima1201_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_purnima1201_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/purnima1201/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_rafvb_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_rafvb_en.md new file mode 100644 index 00000000000000..2832d514f0751d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_rafvb_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_rafvb CamemBertEmbeddings from rafvb +author: John Snow Labs +name: dummy_model_rafvb +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_rafvb` is a English model originally trained by rafvb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_rafvb_en_5.5.0_3.0_1725297694489.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_rafvb_en_5.5.0_3.0_1725297694489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_rafvb","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_rafvb","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_rafvb| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/rafvb/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_rafvb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_rafvb_pipeline_en.md new file mode 100644 index 00000000000000..7d80e80f404e9b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_rafvb_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_rafvb_pipeline pipeline CamemBertEmbeddings from rafvb +author: John Snow Labs +name: dummy_model_rafvb_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_rafvb_pipeline` is a English model originally trained by rafvb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_rafvb_pipeline_en_5.5.0_3.0_1725297772023.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_rafvb_pipeline_en_5.5.0_3.0_1725297772023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_rafvb_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_rafvb_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_rafvb_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/rafvb/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sabazo_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sabazo_en.md new file mode 100644 index 00000000000000..9edcc49ce435fa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sabazo_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_sabazo CamemBertEmbeddings from sabazo +author: John Snow Labs +name: dummy_model_sabazo +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sabazo` is a English model originally trained by sabazo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sabazo_en_5.5.0_3.0_1725320159983.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sabazo_en_5.5.0_3.0_1725320159983.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_sabazo","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_sabazo","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_sabazo| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/sabazo/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sabazo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sabazo_pipeline_en.md new file mode 100644 index 00000000000000..81620655e69e5a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sabazo_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_sabazo_pipeline pipeline CamemBertEmbeddings from sabazo +author: John Snow Labs +name: dummy_model_sabazo_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sabazo_pipeline` is a English model originally trained by sabazo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sabazo_pipeline_en_5.5.0_3.0_1725320238797.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sabazo_pipeline_en_5.5.0_3.0_1725320238797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_sabazo_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_sabazo_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_sabazo_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/sabazo/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sg2023_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sg2023_en.md new file mode 100644 index 00000000000000..624b29a83d6b67 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sg2023_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_sg2023 CamemBertEmbeddings from sg2023 +author: John Snow Labs +name: dummy_model_sg2023 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sg2023` is a English model originally trained by sg2023. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sg2023_en_5.5.0_3.0_1725302415910.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sg2023_en_5.5.0_3.0_1725302415910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_sg2023","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_sg2023","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_sg2023| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/sg2023/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sg2023_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sg2023_pipeline_en.md new file mode 100644 index 00000000000000..e7fefc4d9f62c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sg2023_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_sg2023_pipeline pipeline CamemBertEmbeddings from sg2023 +author: John Snow Labs +name: dummy_model_sg2023_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sg2023_pipeline` is a English model originally trained by sg2023. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sg2023_pipeline_en_5.5.0_3.0_1725302494461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sg2023_pipeline_en_5.5.0_3.0_1725302494461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_sg2023_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_sg2023_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_sg2023_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/sg2023/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_skonmeme_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_skonmeme_en.md new file mode 100644 index 00000000000000..ba0caa9a7d26b5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_skonmeme_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_skonmeme CamemBertEmbeddings from skonmeme +author: John Snow Labs +name: dummy_model_skonmeme +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_skonmeme` is a English model originally trained by skonmeme. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_skonmeme_en_5.5.0_3.0_1725320973604.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_skonmeme_en_5.5.0_3.0_1725320973604.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_skonmeme","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_skonmeme","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_skonmeme| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/skonmeme/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_skonmeme_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_skonmeme_pipeline_en.md new file mode 100644 index 00000000000000..732fd63eb76c73 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_skonmeme_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_skonmeme_pipeline pipeline CamemBertEmbeddings from skonmeme +author: John Snow Labs +name: dummy_model_skonmeme_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_skonmeme_pipeline` is a English model originally trained by skonmeme. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_skonmeme_pipeline_en_5.5.0_3.0_1725321048397.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_skonmeme_pipeline_en_5.5.0_3.0_1725321048397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_skonmeme_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_skonmeme_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_skonmeme_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/skonmeme/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_spaceman23_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_spaceman23_en.md new file mode 100644 index 00000000000000..3482dd2763fa91 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_spaceman23_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_spaceman23 CamemBertEmbeddings from Spaceman23 +author: John Snow Labs +name: dummy_model_spaceman23 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_spaceman23` is a English model originally trained by Spaceman23. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_spaceman23_en_5.5.0_3.0_1725300665544.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_spaceman23_en_5.5.0_3.0_1725300665544.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_spaceman23","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_spaceman23","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_spaceman23| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Spaceman23/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_spaceman23_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_spaceman23_pipeline_en.md new file mode 100644 index 00000000000000..515d4c4a19c20b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_spaceman23_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_spaceman23_pipeline pipeline CamemBertEmbeddings from Spaceman23 +author: John Snow Labs +name: dummy_model_spaceman23_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_spaceman23_pipeline` is a English model originally trained by Spaceman23. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_spaceman23_pipeline_en_5.5.0_3.0_1725300744028.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_spaceman23_pipeline_en_5.5.0_3.0_1725300744028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_spaceman23_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_spaceman23_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_spaceman23_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Spaceman23/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sul_lix_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sul_lix_en.md new file mode 100644 index 00000000000000..9a8fbdb9bd088c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sul_lix_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_sul_lix CamemBertEmbeddings from sul-lix +author: John Snow Labs +name: dummy_model_sul_lix +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sul_lix` is a English model originally trained by sul-lix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sul_lix_en_5.5.0_3.0_1725297919118.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sul_lix_en_5.5.0_3.0_1725297919118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_sul_lix","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_sul_lix","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_sul_lix| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/sul-lix/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sul_lix_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sul_lix_pipeline_en.md new file mode 100644 index 00000000000000..639bc4c5db0f2d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_sul_lix_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_sul_lix_pipeline pipeline CamemBertEmbeddings from sul-lix +author: John Snow Labs +name: dummy_model_sul_lix_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sul_lix_pipeline` is a English model originally trained by sul-lix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sul_lix_pipeline_en_5.5.0_3.0_1725297995378.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sul_lix_pipeline_en_5.5.0_3.0_1725297995378.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_sul_lix_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_sul_lix_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_sul_lix_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/sul-lix/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_tpanza_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_tpanza_pipeline_en.md new file mode 100644 index 00000000000000..f1b15aa6bbb4f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_tpanza_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_tpanza_pipeline pipeline CamemBertEmbeddings from tpanza +author: John Snow Labs +name: dummy_model_tpanza_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_tpanza_pipeline` is a English model originally trained by tpanza. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_tpanza_pipeline_en_5.5.0_3.0_1725320752836.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_tpanza_pipeline_en_5.5.0_3.0_1725320752836.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_tpanza_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_tpanza_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_tpanza_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/tpanza/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_wangst_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_wangst_pipeline_en.md new file mode 100644 index 00000000000000..63ad5394e8baba --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_wangst_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_wangst_pipeline pipeline CamemBertEmbeddings from wangst +author: John Snow Labs +name: dummy_model_wangst_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_wangst_pipeline` is a English model originally trained by wangst. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_wangst_pipeline_en_5.5.0_3.0_1725303328481.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_wangst_pipeline_en_5.5.0_3.0_1725303328481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_wangst_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_wangst_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_wangst_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/wangst/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_xjx001_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_xjx001_en.md new file mode 100644 index 00000000000000..6b4136d1deb22e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_xjx001_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_xjx001 CamemBertEmbeddings from xjx001 +author: John Snow Labs +name: dummy_model_xjx001 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_xjx001` is a English model originally trained by xjx001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_xjx001_en_5.5.0_3.0_1725300257689.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_xjx001_en_5.5.0_3.0_1725300257689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_xjx001","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_xjx001","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_xjx001| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/xjx001/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_xjx001_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_xjx001_pipeline_en.md new file mode 100644 index 00000000000000..8efb3ac7fd9232 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_xjx001_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_xjx001_pipeline pipeline CamemBertEmbeddings from xjx001 +author: John Snow Labs +name: dummy_model_xjx001_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_xjx001_pipeline` is a English model originally trained by xjx001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_xjx001_pipeline_en_5.5.0_3.0_1725300335575.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_xjx001_pipeline_en_5.5.0_3.0_1725300335575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_xjx001_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_xjx001_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_xjx001_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/xjx001/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zarasim_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zarasim_en.md new file mode 100644 index 00000000000000..62c604c5fffeca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zarasim_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_zarasim CamemBertEmbeddings from Zarasim +author: John Snow Labs +name: dummy_model_zarasim +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_zarasim` is a English model originally trained by Zarasim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_zarasim_en_5.5.0_3.0_1725302881502.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_zarasim_en_5.5.0_3.0_1725302881502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_zarasim","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_zarasim","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_zarasim| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Zarasim/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zarasim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zarasim_pipeline_en.md new file mode 100644 index 00000000000000..9ebc64c4ceba93 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zarasim_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_zarasim_pipeline pipeline CamemBertEmbeddings from Zarasim +author: John Snow Labs +name: dummy_model_zarasim_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_zarasim_pipeline` is a English model originally trained by Zarasim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_zarasim_pipeline_en_5.5.0_3.0_1725302959908.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_zarasim_pipeline_en_5.5.0_3.0_1725302959908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_zarasim_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_zarasim_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_zarasim_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Zarasim/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zhenghuabin_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zhenghuabin_en.md new file mode 100644 index 00000000000000..ba42ee5e20c910 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zhenghuabin_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_zhenghuabin CamemBertEmbeddings from zhenghuabin +author: John Snow Labs +name: dummy_model_zhenghuabin +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_zhenghuabin` is a English model originally trained by zhenghuabin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_zhenghuabin_en_5.5.0_3.0_1725302783229.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_zhenghuabin_en_5.5.0_3.0_1725302783229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_zhenghuabin","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_zhenghuabin","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_zhenghuabin| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/zhenghuabin/dummy_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zhenghuabin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zhenghuabin_pipeline_en.md new file mode 100644 index 00000000000000..4ef1cafccbc15e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zhenghuabin_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_zhenghuabin_pipeline pipeline CamemBertEmbeddings from zhenghuabin +author: John Snow Labs +name: dummy_model_zhenghuabin_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_zhenghuabin_pipeline` is a English model originally trained by zhenghuabin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_zhenghuabin_pipeline_en_5.5.0_3.0_1725302861829.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_zhenghuabin_pipeline_en_5.5.0_3.0_1725302861829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_zhenghuabin_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_zhenghuabin_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_zhenghuabin_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/zhenghuabin/dummy_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_translation_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_translation_en.md new file mode 100644 index 00000000000000..b9faa69ab00886 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_translation_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_translation MarianTransformer from lewtun +author: John Snow Labs +name: dummy_translation +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_translation` is a English model originally trained by lewtun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_translation_en_5.5.0_3.0_1725242568473.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_translation_en_5.5.0_3.0_1725242568473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("dummy_translation","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("dummy_translation","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_translation| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.6 MB| + +## References + +https://huggingface.co/lewtun/dummy-translation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_translation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_translation_pipeline_en.md new file mode 100644 index 00000000000000..e338127337cd37 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_translation_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_translation_pipeline pipeline MarianTransformer from lewtun +author: John Snow Labs +name: dummy_translation_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_translation_pipeline` is a English model originally trained by lewtun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_translation_pipeline_en_5.5.0_3.0_1725242601700.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_translation_pipeline_en_5.5.0_3.0_1725242601700.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_translation_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_translation_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_translation_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|509.2 MB| + +## References + +https://huggingface.co/lewtun/dummy-translation + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e2m_best_19_4_23_en.md b/docs/_posts/ahmedlone127/2024-09-02-e2m_best_19_4_23_en.md new file mode 100644 index 00000000000000..38f1a7a2618416 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e2m_best_19_4_23_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English e2m_best_19_4_23 MarianTransformer from Sunbird +author: John Snow Labs +name: e2m_best_19_4_23 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e2m_best_19_4_23` is a English model originally trained by Sunbird. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e2m_best_19_4_23_en_5.5.0_3.0_1725243414801.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e2m_best_19_4_23_en_5.5.0_3.0_1725243414801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("e2m_best_19_4_23","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("e2m_best_19_4_23","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e2m_best_19_4_23| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|530.2 MB| + +## References + +https://huggingface.co/Sunbird/e2m_best_19_4_23 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e2m_best_19_4_23_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-e2m_best_19_4_23_pipeline_en.md new file mode 100644 index 00000000000000..d505be2a8000f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e2m_best_19_4_23_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English e2m_best_19_4_23_pipeline pipeline MarianTransformer from Sunbird +author: John Snow Labs +name: e2m_best_19_4_23_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e2m_best_19_4_23_pipeline` is a English model originally trained by Sunbird. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e2m_best_19_4_23_pipeline_en_5.5.0_3.0_1725243444573.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e2m_best_19_4_23_pipeline_en_5.5.0_3.0_1725243444573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e2m_best_19_4_23_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e2m_best_19_4_23_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e2m_best_19_4_23_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|530.7 MB| + +## References + +https://huggingface.co/Sunbird/e2m_best_19_4_23 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e2m_dataset_tags_1000_en.md b/docs/_posts/ahmedlone127/2024-09-02-e2m_dataset_tags_1000_en.md new file mode 100644 index 00000000000000..c5ccc2a834785b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e2m_dataset_tags_1000_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English e2m_dataset_tags_1000 MarianTransformer from mekaneeky +author: John Snow Labs +name: e2m_dataset_tags_1000 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e2m_dataset_tags_1000` is a English model originally trained by mekaneeky. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e2m_dataset_tags_1000_en_5.5.0_3.0_1725303885322.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e2m_dataset_tags_1000_en_5.5.0_3.0_1725303885322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("e2m_dataset_tags_1000","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("e2m_dataset_tags_1000","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e2m_dataset_tags_1000| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|530.2 MB| + +## References + +https://huggingface.co/mekaneeky/e2m-dataset-tags-1000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e2m_dataset_tags_900_en.md b/docs/_posts/ahmedlone127/2024-09-02-e2m_dataset_tags_900_en.md new file mode 100644 index 00000000000000..fb57d56e1f8a20 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e2m_dataset_tags_900_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English e2m_dataset_tags_900 MarianTransformer from mekaneeky +author: John Snow Labs +name: e2m_dataset_tags_900 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e2m_dataset_tags_900` is a English model originally trained by mekaneeky. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e2m_dataset_tags_900_en_5.5.0_3.0_1725305020528.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e2m_dataset_tags_900_en_5.5.0_3.0_1725305020528.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("e2m_dataset_tags_900","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("e2m_dataset_tags_900","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e2m_dataset_tags_900| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|530.1 MB| + +## References + +https://huggingface.co/mekaneeky/e2m-dataset-tags-900 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e2m_dataset_tags_900_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-e2m_dataset_tags_900_pipeline_en.md new file mode 100644 index 00000000000000..0cfb955a788ebd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e2m_dataset_tags_900_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English e2m_dataset_tags_900_pipeline pipeline MarianTransformer from mekaneeky +author: John Snow Labs +name: e2m_dataset_tags_900_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e2m_dataset_tags_900_pipeline` is a English model originally trained by mekaneeky. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e2m_dataset_tags_900_pipeline_en_5.5.0_3.0_1725305048570.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e2m_dataset_tags_900_pipeline_en_5.5.0_3.0_1725305048570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e2m_dataset_tags_900_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e2m_dataset_tags_900_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e2m_dataset_tags_900_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|530.6 MB| + +## References + +https://huggingface.co/mekaneeky/e2m-dataset-tags-900 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e2m_marianmt_tags_en.md b/docs/_posts/ahmedlone127/2024-09-02-e2m_marianmt_tags_en.md new file mode 100644 index 00000000000000..0420285c64e769 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e2m_marianmt_tags_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English e2m_marianmt_tags MarianTransformer from Sunbird +author: John Snow Labs +name: e2m_marianmt_tags +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e2m_marianmt_tags` is a English model originally trained by Sunbird. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e2m_marianmt_tags_en_5.5.0_3.0_1725303680281.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e2m_marianmt_tags_en_5.5.0_3.0_1725303680281.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("e2m_marianmt_tags","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("e2m_marianmt_tags","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e2m_marianmt_tags| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|530.2 MB| + +## References + +https://huggingface.co/Sunbird/e2m_marianmt_tags \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e2m_marianmt_tags_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-e2m_marianmt_tags_pipeline_en.md new file mode 100644 index 00000000000000..59c4ea7c16efd1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e2m_marianmt_tags_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English e2m_marianmt_tags_pipeline pipeline MarianTransformer from Sunbird +author: John Snow Labs +name: e2m_marianmt_tags_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e2m_marianmt_tags_pipeline` is a English model originally trained by Sunbird. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e2m_marianmt_tags_pipeline_en_5.5.0_3.0_1725303716062.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e2m_marianmt_tags_pipeline_en_5.5.0_3.0_1725303716062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e2m_marianmt_tags_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e2m_marianmt_tags_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e2m_marianmt_tags_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|530.7 MB| + +## References + +https://huggingface.co/Sunbird/e2m_marianmt_tags + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_10k_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_10k_en.md new file mode 100644 index 00000000000000..4ae0dc1b6454e7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e5_10k_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_10k E5Embeddings from heka-ai +author: John Snow Labs +name: e5_10k +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_10k` is a English model originally trained by heka-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_10k_en_5.5.0_3.0_1725259958514.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_10k_en_5.5.0_3.0_1725259958514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_10k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_10k","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_10k| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|401.1 MB| + +## References + +https://huggingface.co/heka-ai/e5-10k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_10k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_10k_pipeline_en.md new file mode 100644 index 00000000000000..e3bd0ca17b9ec6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e5_10k_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English e5_10k_pipeline pipeline E5Embeddings from heka-ai +author: John Snow Labs +name: e5_10k_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_10k_pipeline` is a English model originally trained by heka-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_10k_pipeline_en_5.5.0_3.0_1725259987178.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_10k_pipeline_en_5.5.0_3.0_1725259987178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_10k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_10k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_10k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|401.2 MB| + +## References + +https://huggingface.co/heka-ai/e5-10k + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_base_arguana_10000_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_base_arguana_10000_en.md new file mode 100644 index 00000000000000..ce161f858ff63f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e5_base_arguana_10000_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_base_arguana_10000 E5Embeddings from rithwik-db +author: John Snow Labs +name: e5_base_arguana_10000 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_arguana_10000` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_arguana_10000_en_5.5.0_3.0_1725259086357.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_arguana_10000_en_5.5.0_3.0_1725259086357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_base_arguana_10000","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_base_arguana_10000","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_arguana_10000| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|391.1 MB| + +## References + +https://huggingface.co/rithwik-db/e5-base_arguana_10000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_base_arguana_10000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_base_arguana_10000_pipeline_en.md new file mode 100644 index 00000000000000..a29424350901de --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e5_base_arguana_10000_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English e5_base_arguana_10000_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: e5_base_arguana_10000_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_arguana_10000_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_arguana_10000_pipeline_en_5.5.0_3.0_1725259111442.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_arguana_10000_pipeline_en_5.5.0_3.0_1725259111442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_base_arguana_10000_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_base_arguana_10000_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_arguana_10000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|391.1 MB| + +## References + +https://huggingface.co/rithwik-db/e5-base_arguana_10000 + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_base_unsupervised_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_base_unsupervised_en.md new file mode 100644 index 00000000000000..a415e5bb22b46b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e5_base_unsupervised_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_base_unsupervised E5Embeddings from intfloat +author: John Snow Labs +name: e5_base_unsupervised +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised` is a English model originally trained by intfloat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_en_5.5.0_3.0_1725259562709.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_en_5.5.0_3.0_1725259562709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_base_unsupervised","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_base_unsupervised","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_unsupervised| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|258.6 MB| + +## References + +https://huggingface.co/intfloat/e5-base-unsupervised \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_base_unsupervised_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_base_unsupervised_pipeline_en.md new file mode 100644 index 00000000000000..ff90294aa49928 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e5_base_unsupervised_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English e5_base_unsupervised_pipeline pipeline E5Embeddings from intfloat +author: John Snow Labs +name: e5_base_unsupervised_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_pipeline` is a English model originally trained by intfloat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pipeline_en_5.5.0_3.0_1725259640580.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pipeline_en_5.5.0_3.0_1725259640580.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_base_unsupervised_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_base_unsupervised_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_unsupervised_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|258.7 MB| + +## References + +https://huggingface.co/intfloat/e5-base-unsupervised + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_en.md new file mode 100644 index 00000000000000..cb51a19df4d5b9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015 E5Embeddings from rithwik-db +author: John Snow Labs +name: e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_en_5.5.0_3.0_1725259868201.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_en_5.5.0_3.0_1725259868201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|402.7 MB| + +## References + +https://huggingface.co/rithwik-db/e5-base-unsupervised-pseudo-gpl-fiqa-131a12-d23573-4be015 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_pipeline_en.md new file mode 100644 index 00000000000000..045ebea3bae8f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_pipeline_en_5.5.0_3.0_1725259890196.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_pipeline_en_5.5.0_3.0_1725259890196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|402.7 MB| + +## References + +https://huggingface.co/rithwik-db/e5-base-unsupervised-pseudo-gpl-fiqa-131a12-d23573-4be015 + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_large_unsupervised_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_large_unsupervised_en.md new file mode 100644 index 00000000000000..6aac285db9acee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e5_large_unsupervised_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_large_unsupervised E5Embeddings from intfloat +author: John Snow Labs +name: e5_large_unsupervised +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_unsupervised` is a English model originally trained by intfloat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_unsupervised_en_5.5.0_3.0_1725259637855.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_unsupervised_en_5.5.0_3.0_1725259637855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_large_unsupervised","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_large_unsupervised","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_large_unsupervised| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|796.1 MB| + +## References + +https://huggingface.co/intfloat/e5-large-unsupervised \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_large_unsupervised_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_large_unsupervised_pipeline_en.md new file mode 100644 index 00000000000000..e49a0b6d7f9086 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e5_large_unsupervised_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English e5_large_unsupervised_pipeline pipeline E5Embeddings from intfloat +author: John Snow Labs +name: e5_large_unsupervised_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_unsupervised_pipeline` is a English model originally trained by intfloat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_unsupervised_pipeline_en_5.5.0_3.0_1725259879580.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_unsupervised_pipeline_en_5.5.0_3.0_1725259879580.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_large_unsupervised_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_large_unsupervised_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_large_unsupervised_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|796.1 MB| + +## References + +https://huggingface.co/intfloat/e5-large-unsupervised + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_large_v2_intfloat_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_large_v2_intfloat_en.md new file mode 100644 index 00000000000000..efeafd1ab51eed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e5_large_v2_intfloat_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_large_v2_intfloat E5Embeddings from intfloat +author: John Snow Labs +name: e5_large_v2_intfloat +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_v2_intfloat` is a English model originally trained by intfloat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_v2_intfloat_en_5.5.0_3.0_1725259720064.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_v2_intfloat_en_5.5.0_3.0_1725259720064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_large_v2_intfloat","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_large_v2_intfloat","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_large_v2_intfloat| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|796.2 MB| + +## References + +https://huggingface.co/intfloat/e5-large-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_large_v2_intfloat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_large_v2_intfloat_pipeline_en.md new file mode 100644 index 00000000000000..20d4beb0960371 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-e5_large_v2_intfloat_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English e5_large_v2_intfloat_pipeline pipeline E5Embeddings from intfloat +author: John Snow Labs +name: e5_large_v2_intfloat_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_v2_intfloat_pipeline` is a English model originally trained by intfloat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_v2_intfloat_pipeline_en_5.5.0_3.0_1725259957830.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_v2_intfloat_pipeline_en_5.5.0_3.0_1725259957830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_large_v2_intfloat_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_large_v2_intfloat_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_large_v2_intfloat_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|796.2 MB| + +## References + +https://huggingface.co/intfloat/e5-large-v2 + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-electra_qa_German_question_answer_de.md b/docs/_posts/ahmedlone127/2024-09-02-electra_qa_German_question_answer_de.md new file mode 100644 index 00000000000000..245bb85370b9c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-electra_qa_German_question_answer_de.md @@ -0,0 +1,98 @@ +--- +layout: model +title: German ElectraForQuestionAnswering model (from Sahajtomar) +author: John Snow Labs +name: electra_qa_German_question_answer +date: 2024-09-02 +tags: [de, open_source, electra, question_answering, onnx] +task: Question Answering +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `German-question-answer-Electra` is a German model originally trained by `Sahajtomar`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_German_question_answer_de_5.5.0_3.0_1725312569508.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_German_question_answer_de_5.5.0_3.0_1725312569508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_German_question_answer","de") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer")\ +.setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, spanClassifier]) + +data = spark.createDataFrame([["Was ist mein Name?", "Mein Name ist Clara und ich lebe in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_German_question_answer","de") +.setInputCols(Array("document", "token")) +.setOutputCol("answer") +.setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) + +val data = Seq("Was ist mein Name?", "Mein Name ist Clara und ich lebe in Berkeley.").toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.answer_question.electra").predict("""Was ist mein Name?|||"Mein Name ist Clara und ich lebe in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|electra_qa_German_question_answer| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|de| +|Size:|1.3 GB| + +## References + +References + +- https://huggingface.co/Sahajtomar/German-question-answer-Electra \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-electra_qa_German_question_answer_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-02-electra_qa_German_question_answer_pipeline_de.md new file mode 100644 index 00000000000000..8bf42e57a223cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-electra_qa_German_question_answer_pipeline_de.md @@ -0,0 +1,69 @@ +--- +layout: model +title: German electra_qa_German_question_answer_pipeline pipeline BertForQuestionAnswering from Sahajtomar +author: John Snow Labs +name: electra_qa_German_question_answer_pipeline +date: 2024-09-02 +tags: [de, open_source, pipeline, onnx] +task: Question Answering +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_German_question_answer_pipeline` is a German model originally trained by Sahajtomar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_German_question_answer_pipeline_de_5.5.0_3.0_1725312632360.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_German_question_answer_pipeline_de_5.5.0_3.0_1725312632360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("electra_qa_German_question_answer_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("electra_qa_German_question_answer_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|electra_qa_German_question_answer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Sahajtomar/German-question-answer-Electra + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-emotion_bot_1000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-emotion_bot_1000_pipeline_en.md new file mode 100644 index 00000000000000..e0293b5a546067 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-emotion_bot_1000_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English emotion_bot_1000_pipeline pipeline DistilBertForSequenceClassification from rrpetroff +author: John Snow Labs +name: emotion_bot_1000_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_bot_1000_pipeline` is a English model originally trained by rrpetroff. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_bot_1000_pipeline_en_5.5.0_3.0_1725306154431.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_bot_1000_pipeline_en_5.5.0_3.0_1725306154431.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("emotion_bot_1000_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("emotion_bot_1000_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|emotion_bot_1000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/rrpetroff/emotion-bot-1000 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-emotion_recognition_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-emotion_recognition_pipeline_en.md new file mode 100644 index 00000000000000..b8f3be30a01ae0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-emotion_recognition_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English emotion_recognition_pipeline pipeline DistilBertForSequenceClassification from Atharvsharma14 +author: John Snow Labs +name: emotion_recognition_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_recognition_pipeline` is a English model originally trained by Atharvsharma14. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_recognition_pipeline_en_5.5.0_3.0_1725306146894.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_recognition_pipeline_en_5.5.0_3.0_1725306146894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("emotion_recognition_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("emotion_recognition_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|emotion_recognition_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Atharvsharma14/Emotion_Recognition + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-emotion_text_classification_en.md b/docs/_posts/ahmedlone127/2024-09-02-emotion_text_classification_en.md new file mode 100644 index 00000000000000..27a7b5f1985819 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-emotion_text_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English emotion_text_classification DistilBertForSequenceClassification from yangswei +author: John Snow Labs +name: emotion_text_classification +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_text_classification` is a English model originally trained by yangswei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_text_classification_en_5.5.0_3.0_1725291764585.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_text_classification_en_5.5.0_3.0_1725291764585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("emotion_text_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("emotion_text_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|emotion_text_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/yangswei/emotion_text_classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-emotion_text_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-emotion_text_classification_pipeline_en.md new file mode 100644 index 00000000000000..e20983c6a410f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-emotion_text_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English emotion_text_classification_pipeline pipeline DistilBertForSequenceClassification from yangswei +author: John Snow Labs +name: emotion_text_classification_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_text_classification_pipeline` is a English model originally trained by yangswei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_text_classification_pipeline_en_5.5.0_3.0_1725291777454.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_text_classification_pipeline_en_5.5.0_3.0_1725291777454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("emotion_text_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("emotion_text_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|emotion_text_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/yangswei/emotion_text_classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-enccr_en.md b/docs/_posts/ahmedlone127/2024-09-02-enccr_en.md new file mode 100644 index 00000000000000..4b829da7243378 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-enccr_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English enccr RoBertaForSequenceClassification from AntoineGourru +author: John Snow Labs +name: enccr +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`enccr` is a English model originally trained by AntoineGourru. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/enccr_en_5.5.0_3.0_1725276996547.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/enccr_en_5.5.0_3.0_1725276996547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("enccr","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("enccr", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|enccr| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|417.0 MB| + +## References + +https://huggingface.co/AntoineGourru/Enccr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-eng_hin_translator_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-eng_hin_translator_pipeline_en.md new file mode 100644 index 00000000000000..293262f92c1f35 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-eng_hin_translator_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English eng_hin_translator_pipeline pipeline MarianTransformer from Vasanth +author: John Snow Labs +name: eng_hin_translator_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eng_hin_translator_pipeline` is a English model originally trained by Vasanth. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eng_hin_translator_pipeline_en_5.5.0_3.0_1725244132740.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eng_hin_translator_pipeline_en_5.5.0_3.0_1725244132740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("eng_hin_translator_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("eng_hin_translator_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|eng_hin_translator_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|523.4 MB| + +## References + +https://huggingface.co/Vasanth/eng-hin-translator + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-english_arabic_model_en.md b/docs/_posts/ahmedlone127/2024-09-02-english_arabic_model_en.md new file mode 100644 index 00000000000000..49d009fea3538c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-english_arabic_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English english_arabic_model MarianTransformer from BoghdadyJR +author: John Snow Labs +name: english_arabic_model +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_arabic_model` is a English model originally trained by BoghdadyJR. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_arabic_model_en_5.5.0_3.0_1725294642051.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_arabic_model_en_5.5.0_3.0_1725294642051.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("english_arabic_model","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("english_arabic_model","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|english_arabic_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|528.2 MB| + +## References + +https://huggingface.co/BoghdadyJR/en-ar-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-english_ganda_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-english_ganda_pipeline_en.md new file mode 100644 index 00000000000000..4fdcd9deed5891 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-english_ganda_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English english_ganda_pipeline pipeline MarianTransformer from AI-Lab-Makerere +author: John Snow Labs +name: english_ganda_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_ganda_pipeline` is a English model originally trained by AI-Lab-Makerere. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_ganda_pipeline_en_5.5.0_3.0_1725243741975.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_ganda_pipeline_en_5.5.0_3.0_1725243741975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("english_ganda_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("english_ganda_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|english_ganda_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|530.9 MB| + +## References + +https://huggingface.co/AI-Lab-Makerere/en_lg + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_dutch_marianmt_en.md b/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_dutch_marianmt_en.md new file mode 100644 index 00000000000000..d78b1f8e2375d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_dutch_marianmt_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English english_tonga_tonga_islands_dutch_marianmt MarianTransformer from vvn +author: John Snow Labs +name: english_tonga_tonga_islands_dutch_marianmt +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_dutch_marianmt` is a English model originally trained by vvn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dutch_marianmt_en_5.5.0_3.0_1725294838403.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dutch_marianmt_en_5.5.0_3.0_1725294838403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("english_tonga_tonga_islands_dutch_marianmt","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("english_tonga_tonga_islands_dutch_marianmt","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|english_tonga_tonga_islands_dutch_marianmt| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|548.8 MB| + +## References + +https://huggingface.co/vvn/en-to-dutch-marianmt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_dutch_marianmt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_dutch_marianmt_pipeline_en.md new file mode 100644 index 00000000000000..23b9f7adfd93da --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_dutch_marianmt_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English english_tonga_tonga_islands_dutch_marianmt_pipeline pipeline MarianTransformer from vvn +author: John Snow Labs +name: english_tonga_tonga_islands_dutch_marianmt_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_dutch_marianmt_pipeline` is a English model originally trained by vvn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dutch_marianmt_pipeline_en_5.5.0_3.0_1725294867984.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dutch_marianmt_pipeline_en_5.5.0_3.0_1725294867984.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("english_tonga_tonga_islands_dutch_marianmt_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("english_tonga_tonga_islands_dutch_marianmt_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|english_tonga_tonga_islands_dutch_marianmt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|549.4 MB| + +## References + +https://huggingface.co/vvn/en-to-dutch-marianmt + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_hinglish_en.md b/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_hinglish_en.md new file mode 100644 index 00000000000000..c4fdff00c88d6a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_hinglish_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English english_tonga_tonga_islands_hinglish MarianTransformer from SkAndMl +author: John Snow Labs +name: english_tonga_tonga_islands_hinglish +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_hinglish` is a English model originally trained by SkAndMl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_hinglish_en_5.5.0_3.0_1725243266776.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_hinglish_en_5.5.0_3.0_1725243266776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("english_tonga_tonga_islands_hinglish","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("english_tonga_tonga_islands_hinglish","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|english_tonga_tonga_islands_hinglish| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|522.2 MB| + +## References + +https://huggingface.co/SkAndMl/english-to-hinglish \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_hinglish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_hinglish_pipeline_en.md new file mode 100644 index 00000000000000..11fcbf521db149 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_hinglish_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English english_tonga_tonga_islands_hinglish_pipeline pipeline MarianTransformer from SkAndMl +author: John Snow Labs +name: english_tonga_tonga_islands_hinglish_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_hinglish_pipeline` is a English model originally trained by SkAndMl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_hinglish_pipeline_en_5.5.0_3.0_1725243298483.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_hinglish_pipeline_en_5.5.0_3.0_1725243298483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("english_tonga_tonga_islands_hinglish_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("english_tonga_tonga_islands_hinglish_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|english_tonga_tonga_islands_hinglish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|522.7 MB| + +## References + +https://huggingface.co/SkAndMl/english-to-hinglish + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-englishtodarija_en.md b/docs/_posts/ahmedlone127/2024-09-02-englishtodarija_en.md new file mode 100644 index 00000000000000..d63816816aab59 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-englishtodarija_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English englishtodarija MarianTransformer from Vrspi +author: John Snow Labs +name: englishtodarija +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`englishtodarija` is a English model originally trained by Vrspi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/englishtodarija_en_5.5.0_3.0_1725295860030.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/englishtodarija_en_5.5.0_3.0_1725295860030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("englishtodarija","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("englishtodarija","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|englishtodarija| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|507.8 MB| + +## References + +https://huggingface.co/Vrspi/EnglishToDarija \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-englishtodarija_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-englishtodarija_pipeline_en.md new file mode 100644 index 00000000000000..b69513cbe0d2c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-englishtodarija_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English englishtodarija_pipeline pipeline MarianTransformer from Vrspi +author: John Snow Labs +name: englishtodarija_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`englishtodarija_pipeline` is a English model originally trained by Vrspi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/englishtodarija_pipeline_en_5.5.0_3.0_1725295888293.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/englishtodarija_pipeline_en_5.5.0_3.0_1725295888293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("englishtodarija_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("englishtodarija_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|englishtodarija_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.4 MB| + +## References + +https://huggingface.co/Vrspi/EnglishToDarija + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-entitycs_39_wep_xlmr_base_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-entitycs_39_wep_xlmr_base_pipeline_xx.md new file mode 100644 index 00000000000000..957e22bd7401ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-entitycs_39_wep_xlmr_base_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual entitycs_39_wep_xlmr_base_pipeline pipeline XlmRoBertaEmbeddings from huawei-noah +author: John Snow Labs +name: entitycs_39_wep_xlmr_base_pipeline +date: 2024-09-02 +tags: [xx, open_source, pipeline, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`entitycs_39_wep_xlmr_base_pipeline` is a Multilingual model originally trained by huawei-noah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/entitycs_39_wep_xlmr_base_pipeline_xx_5.5.0_3.0_1725271402620.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/entitycs_39_wep_xlmr_base_pipeline_xx_5.5.0_3.0_1725271402620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("entitycs_39_wep_xlmr_base_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("entitycs_39_wep_xlmr_base_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|entitycs_39_wep_xlmr_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|944.9 MB| + +## References + +https://huggingface.co/huawei-noah/EntityCS-39-WEP-xlmr-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-entitycs_39_wep_xlmr_base_xx.md b/docs/_posts/ahmedlone127/2024-09-02-entitycs_39_wep_xlmr_base_xx.md new file mode 100644 index 00000000000000..a1800f413f14d3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-entitycs_39_wep_xlmr_base_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual entitycs_39_wep_xlmr_base XlmRoBertaEmbeddings from huawei-noah +author: John Snow Labs +name: entitycs_39_wep_xlmr_base +date: 2024-09-02 +tags: [xx, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`entitycs_39_wep_xlmr_base` is a Multilingual model originally trained by huawei-noah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/entitycs_39_wep_xlmr_base_xx_5.5.0_3.0_1725271310085.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/entitycs_39_wep_xlmr_base_xx_5.5.0_3.0_1725271310085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("entitycs_39_wep_xlmr_base","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("entitycs_39_wep_xlmr_base","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|entitycs_39_wep_xlmr_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|xx| +|Size:|944.9 MB| + +## References + +https://huggingface.co/huawei-noah/EntityCS-39-WEP-xlmr-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-environmentalbert_biodiversity_en.md b/docs/_posts/ahmedlone127/2024-09-02-environmentalbert_biodiversity_en.md new file mode 100644 index 00000000000000..76fd7003b718e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-environmentalbert_biodiversity_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English environmentalbert_biodiversity RoBertaForSequenceClassification from ESGBERT +author: John Snow Labs +name: environmentalbert_biodiversity +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`environmentalbert_biodiversity` is a English model originally trained by ESGBERT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/environmentalbert_biodiversity_en_5.5.0_3.0_1725277653824.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/environmentalbert_biodiversity_en_5.5.0_3.0_1725277653824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("environmentalbert_biodiversity","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("environmentalbert_biodiversity", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|environmentalbert_biodiversity| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|309.0 MB| + +## References + +https://huggingface.co/ESGBERT/EnvironmentalBERT-biodiversity \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-esg_prediction_icelandic_en.md b/docs/_posts/ahmedlone127/2024-09-02-esg_prediction_icelandic_en.md new file mode 100644 index 00000000000000..8855108aed0313 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-esg_prediction_icelandic_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English esg_prediction_icelandic CamemBertForSequenceClassification from Katkatkuu +author: John Snow Labs +name: esg_prediction_icelandic +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esg_prediction_icelandic` is a English model originally trained by Katkatkuu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esg_prediction_icelandic_en_5.5.0_3.0_1725298856039.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esg_prediction_icelandic_en_5.5.0_3.0_1725298856039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("esg_prediction_icelandic","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("esg_prediction_icelandic", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esg_prediction_icelandic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|394.3 MB| + +## References + +https://huggingface.co/Katkatkuu/ESG_Prediction_IS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-esg_prediction_icelandic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-esg_prediction_icelandic_pipeline_en.md new file mode 100644 index 00000000000000..e5e6850a9100a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-esg_prediction_icelandic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English esg_prediction_icelandic_pipeline pipeline CamemBertForSequenceClassification from Katkatkuu +author: John Snow Labs +name: esg_prediction_icelandic_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esg_prediction_icelandic_pipeline` is a English model originally trained by Katkatkuu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esg_prediction_icelandic_pipeline_en_5.5.0_3.0_1725298877768.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esg_prediction_icelandic_pipeline_en_5.5.0_3.0_1725298877768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("esg_prediction_icelandic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("esg_prediction_icelandic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esg_prediction_icelandic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|394.4 MB| + +## References + +https://huggingface.co/Katkatkuu/ESG_Prediction_IS + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-esperberto_small_eo.md b/docs/_posts/ahmedlone127/2024-09-02-esperberto_small_eo.md new file mode 100644 index 00000000000000..3b74539a526a60 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-esperberto_small_eo.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Esperanto esperberto_small RoBertaEmbeddings from julien-c +author: John Snow Labs +name: esperberto_small +date: 2024-09-02 +tags: [eo, open_source, onnx, embeddings, roberta] +task: Embeddings +language: eo +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esperberto_small` is a Esperanto model originally trained by julien-c. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esperberto_small_eo_5.5.0_3.0_1725264870926.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esperberto_small_eo_5.5.0_3.0_1725264870926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("esperberto_small","eo") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("esperberto_small","eo") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esperberto_small| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|eo| +|Size:|308.6 MB| + +## References + +https://huggingface.co/julien-c/EsperBERTo-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-esperberto_small_pipeline_eo.md b/docs/_posts/ahmedlone127/2024-09-02-esperberto_small_pipeline_eo.md new file mode 100644 index 00000000000000..6e1f6a8bf0ed5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-esperberto_small_pipeline_eo.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Esperanto esperberto_small_pipeline pipeline RoBertaEmbeddings from julien-c +author: John Snow Labs +name: esperberto_small_pipeline +date: 2024-09-02 +tags: [eo, open_source, pipeline, onnx] +task: Embeddings +language: eo +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esperberto_small_pipeline` is a Esperanto model originally trained by julien-c. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esperberto_small_pipeline_eo_5.5.0_3.0_1725264888278.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esperberto_small_pipeline_eo_5.5.0_3.0_1725264888278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("esperberto_small_pipeline", lang = "eo") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("esperberto_small_pipeline", lang = "eo") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esperberto_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|eo| +|Size:|308.6 MB| + +## References + +https://huggingface.co/julien-c/EsperBERTo-small + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fashion_clip_patrickjohncyh_en.md b/docs/_posts/ahmedlone127/2024-09-02-fashion_clip_patrickjohncyh_en.md new file mode 100644 index 00000000000000..5b52de07e0447b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fashion_clip_patrickjohncyh_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English fashion_clip_patrickjohncyh CLIPForZeroShotClassification from patrickjohncyh +author: John Snow Labs +name: fashion_clip_patrickjohncyh +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_clip_patrickjohncyh` is a English model originally trained by patrickjohncyh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_clip_patrickjohncyh_en_5.5.0_3.0_1725275422662.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_clip_patrickjohncyh_en_5.5.0_3.0_1725275422662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("fashion_clip_patrickjohncyh","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("fashion_clip_patrickjohncyh","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fashion_clip_patrickjohncyh| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.7 MB| + +## References + +https://huggingface.co/patrickjohncyh/fashion-clip \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fashion_clip_patrickjohncyh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-fashion_clip_patrickjohncyh_pipeline_en.md new file mode 100644 index 00000000000000..b8b6f0ab16eba0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fashion_clip_patrickjohncyh_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fashion_clip_patrickjohncyh_pipeline pipeline CLIPForZeroShotClassification from patrickjohncyh +author: John Snow Labs +name: fashion_clip_patrickjohncyh_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_clip_patrickjohncyh_pipeline` is a English model originally trained by patrickjohncyh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_clip_patrickjohncyh_pipeline_en_5.5.0_3.0_1725275519496.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_clip_patrickjohncyh_pipeline_en_5.5.0_3.0_1725275519496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fashion_clip_patrickjohncyh_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fashion_clip_patrickjohncyh_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fashion_clip_patrickjohncyh_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.7 MB| + +## References + +https://huggingface.co/patrickjohncyh/fashion-clip + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fashion_embedder_en.md b/docs/_posts/ahmedlone127/2024-09-02-fashion_embedder_en.md new file mode 100644 index 00000000000000..c60a048aeada6b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fashion_embedder_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English fashion_embedder CLIPForZeroShotClassification from McClain +author: John Snow Labs +name: fashion_embedder +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_embedder` is a English model originally trained by McClain. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_embedder_en_5.5.0_3.0_1725256499332.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_embedder_en_5.5.0_3.0_1725256499332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("fashion_embedder","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("fashion_embedder","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fashion_embedder| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.7 MB| + +## References + +https://huggingface.co/McClain/fashion-embedder \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fashion_embedder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-fashion_embedder_pipeline_en.md new file mode 100644 index 00000000000000..20551ddedf1e15 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fashion_embedder_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fashion_embedder_pipeline pipeline CLIPForZeroShotClassification from McClain +author: John Snow Labs +name: fashion_embedder_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_embedder_pipeline` is a English model originally trained by McClain. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_embedder_pipeline_en_5.5.0_3.0_1725256596647.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_embedder_pipeline_en_5.5.0_3.0_1725256596647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fashion_embedder_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fashion_embedder_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fashion_embedder_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.7 MB| + +## References + +https://huggingface.co/McClain/fashion-embedder + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-feel_italian_finetuned_pro_emit_big7_en.md b/docs/_posts/ahmedlone127/2024-09-02-feel_italian_finetuned_pro_emit_big7_en.md new file mode 100644 index 00000000000000..8062accb725502 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-feel_italian_finetuned_pro_emit_big7_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English feel_italian_finetuned_pro_emit_big7 CamemBertForSequenceClassification from lupobricco +author: John Snow Labs +name: feel_italian_finetuned_pro_emit_big7 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`feel_italian_finetuned_pro_emit_big7` is a English model originally trained by lupobricco. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_big7_en_5.5.0_3.0_1725298769905.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_big7_en_5.5.0_3.0_1725298769905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("feel_italian_finetuned_pro_emit_big7","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("feel_italian_finetuned_pro_emit_big7", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|feel_italian_finetuned_pro_emit_big7| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|403.1 MB| + +## References + +https://huggingface.co/lupobricco/feel_it_finetuned_pro_emit_big7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-feel_italian_finetuned_pro_emit_big8_en.md b/docs/_posts/ahmedlone127/2024-09-02-feel_italian_finetuned_pro_emit_big8_en.md new file mode 100644 index 00000000000000..be2317aa23256f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-feel_italian_finetuned_pro_emit_big8_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English feel_italian_finetuned_pro_emit_big8 CamemBertForSequenceClassification from lupobricco +author: John Snow Labs +name: feel_italian_finetuned_pro_emit_big8 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`feel_italian_finetuned_pro_emit_big8` is a English model originally trained by lupobricco. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_big8_en_5.5.0_3.0_1725298821654.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_big8_en_5.5.0_3.0_1725298821654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("feel_italian_finetuned_pro_emit_big8","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("feel_italian_finetuned_pro_emit_big8", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|feel_italian_finetuned_pro_emit_big8| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|398.1 MB| + +## References + +https://huggingface.co/lupobricco/feel_it_finetuned_pro_emit_big8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fewshot_qa_002_20230613_003_exp2_en.md b/docs/_posts/ahmedlone127/2024-09-02-fewshot_qa_002_20230613_003_exp2_en.md new file mode 100644 index 00000000000000..0ecdc67c28a70d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fewshot_qa_002_20230613_003_exp2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fewshot_qa_002_20230613_003_exp2 XlmRoBertaForQuestionAnswering from intanm +author: John Snow Labs +name: fewshot_qa_002_20230613_003_exp2 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fewshot_qa_002_20230613_003_exp2` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fewshot_qa_002_20230613_003_exp2_en_5.5.0_3.0_1725254566096.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fewshot_qa_002_20230613_003_exp2_en_5.5.0_3.0_1725254566096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("fewshot_qa_002_20230613_003_exp2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("fewshot_qa_002_20230613_003_exp2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fewshot_qa_002_20230613_003_exp2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|880.4 MB| + +## References + +https://huggingface.co/intanm/fewshot-qa-002-20230613-003-exp2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fin_camembert_base_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-fin_camembert_base_pipeline_fr.md new file mode 100644 index 00000000000000..797a8d9c8e8421 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fin_camembert_base_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French fin_camembert_base_pipeline pipeline CamemBertEmbeddings from Ngawang +author: John Snow Labs +name: fin_camembert_base_pipeline +date: 2024-09-02 +tags: [fr, open_source, pipeline, onnx] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fin_camembert_base_pipeline` is a French model originally trained by Ngawang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fin_camembert_base_pipeline_fr_5.5.0_3.0_1725320062394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fin_camembert_base_pipeline_fr_5.5.0_3.0_1725320062394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fin_camembert_base_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fin_camembert_base_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fin_camembert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|412.6 MB| + +## References + +https://huggingface.co/Ngawang/fin_camembert-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-final_roberta_with_nepal_bhasa_400k_plus_37k_best_en.md b/docs/_posts/ahmedlone127/2024-09-02-final_roberta_with_nepal_bhasa_400k_plus_37k_best_en.md new file mode 100644 index 00000000000000..ed2bc462d55cf2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-final_roberta_with_nepal_bhasa_400k_plus_37k_best_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English final_roberta_with_nepal_bhasa_400k_plus_37k_best RoBertaForSequenceClassification from ManojAlexender +author: John Snow Labs +name: final_roberta_with_nepal_bhasa_400k_plus_37k_best +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`final_roberta_with_nepal_bhasa_400k_plus_37k_best` is a English model originally trained by ManojAlexender. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/final_roberta_with_nepal_bhasa_400k_plus_37k_best_en_5.5.0_3.0_1725278040359.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_roberta_with_nepal_bhasa_400k_plus_37k_best_en_5.5.0_3.0_1725278040359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("final_roberta_with_nepal_bhasa_400k_plus_37k_best","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("final_roberta_with_nepal_bhasa_400k_plus_37k_best", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|final_roberta_with_nepal_bhasa_400k_plus_37k_best| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.4 MB| + +## References + +https://huggingface.co/ManojAlexender/final_roberta_with_new_400k_plus_37k_Best \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-final_roberta_with_nepal_bhasa_400k_plus_37k_best_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-final_roberta_with_nepal_bhasa_400k_plus_37k_best_pipeline_en.md new file mode 100644 index 00000000000000..07877093e194ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-final_roberta_with_nepal_bhasa_400k_plus_37k_best_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English final_roberta_with_nepal_bhasa_400k_plus_37k_best_pipeline pipeline RoBertaForSequenceClassification from ManojAlexender +author: John Snow Labs +name: final_roberta_with_nepal_bhasa_400k_plus_37k_best_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`final_roberta_with_nepal_bhasa_400k_plus_37k_best_pipeline` is a English model originally trained by ManojAlexender. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/final_roberta_with_nepal_bhasa_400k_plus_37k_best_pipeline_en_5.5.0_3.0_1725278064783.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_roberta_with_nepal_bhasa_400k_plus_37k_best_pipeline_en_5.5.0_3.0_1725278064783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("final_roberta_with_nepal_bhasa_400k_plus_37k_best_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("final_roberta_with_nepal_bhasa_400k_plus_37k_best_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|final_roberta_with_nepal_bhasa_400k_plus_37k_best_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.4 MB| + +## References + +https://huggingface.co/ManojAlexender/final_roberta_with_new_400k_plus_37k_Best + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finance_article_titles_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-02-finance_article_titles_classifier_en.md new file mode 100644 index 00000000000000..309978654ebb02 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finance_article_titles_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finance_article_titles_classifier DistilBertForSequenceClassification from hatmimoha +author: John Snow Labs +name: finance_article_titles_classifier +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finance_article_titles_classifier` is a English model originally trained by hatmimoha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finance_article_titles_classifier_en_5.5.0_3.0_1725291695031.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finance_article_titles_classifier_en_5.5.0_3.0_1725291695031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("finance_article_titles_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finance_article_titles_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finance_article_titles_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|246.2 MB| + +## References + +https://huggingface.co/hatmimoha/finance-article-titles-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bert_pipeline_en.md new file mode 100644 index 00000000000000..f349a335730a6e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fine_tuned_bert_pipeline pipeline DistilBertForSequenceClassification from samanthakarungi +author: John Snow Labs +name: fine_tuned_bert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bert_pipeline` is a English model originally trained by samanthakarungi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_pipeline_en_5.5.0_3.0_1725291931111.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_pipeline_en_5.5.0_3.0_1725291931111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/samanthakarungi/fine-tuned-bert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bge_small_english_v1_5_another_data_formate_en.md b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bge_small_english_v1_5_another_data_formate_en.md new file mode 100644 index 00000000000000..a5ea186fa1aac6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bge_small_english_v1_5_another_data_formate_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English fine_tuned_bge_small_english_v1_5_another_data_formate BGEEmbeddings from ravch +author: John Snow Labs +name: fine_tuned_bge_small_english_v1_5_another_data_formate +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bge_small_english_v1_5_another_data_formate` is a English model originally trained by ravch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bge_small_english_v1_5_another_data_formate_en_5.5.0_3.0_1725242191366.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bge_small_english_v1_5_another_data_formate_en_5.5.0_3.0_1725242191366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("fine_tuned_bge_small_english_v1_5_another_data_formate","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("fine_tuned_bge_small_english_v1_5_another_data_formate","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_bge_small_english_v1_5_another_data_formate| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|124.6 MB| + +## References + +https://huggingface.co/ravch/fine_tuned_bge_small_en_v1.5_another_data_formate \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bge_small_english_v1_5_another_data_formate_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bge_small_english_v1_5_another_data_formate_pipeline_en.md new file mode 100644 index 00000000000000..10babd4387a245 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bge_small_english_v1_5_another_data_formate_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tuned_bge_small_english_v1_5_another_data_formate_pipeline pipeline BGEEmbeddings from ravch +author: John Snow Labs +name: fine_tuned_bge_small_english_v1_5_another_data_formate_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bge_small_english_v1_5_another_data_formate_pipeline` is a English model originally trained by ravch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bge_small_english_v1_5_another_data_formate_pipeline_en_5.5.0_3.0_1725242197326.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bge_small_english_v1_5_another_data_formate_pipeline_en_5.5.0_3.0_1725242197326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_bge_small_english_v1_5_another_data_formate_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_bge_small_english_v1_5_another_data_formate_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_bge_small_english_v1_5_another_data_formate_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|124.6 MB| + +## References + +https://huggingface.co/ravch/fine_tuned_bge_small_en_v1.5_another_data_formate + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_deberta_question_answering_base_en.md b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_deberta_question_answering_base_en.md new file mode 100644 index 00000000000000..18fccfcaef9bbb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_deberta_question_answering_base_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fine_tuned_deberta_question_answering_base DeBertaForQuestionAnswering from seenuvasanfoss +author: John Snow Labs +name: fine_tuned_deberta_question_answering_base +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_deberta_question_answering_base` is a English model originally trained by seenuvasanfoss. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_question_answering_base_en_5.5.0_3.0_1725240616612.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_question_answering_base_en_5.5.0_3.0_1725240616612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("fine_tuned_deberta_question_answering_base","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("fine_tuned_deberta_question_answering_base", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_deberta_question_answering_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|550.7 MB| + +## References + +https://huggingface.co/seenuvasanfoss/fine_tuned_deberta_question_answering_base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_deberta_question_answering_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_deberta_question_answering_base_pipeline_en.md new file mode 100644 index 00000000000000..0f07d5042fefa8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_deberta_question_answering_base_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tuned_deberta_question_answering_base_pipeline pipeline DeBertaForQuestionAnswering from seenuvasanfoss +author: John Snow Labs +name: fine_tuned_deberta_question_answering_base_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_deberta_question_answering_base_pipeline` is a English model originally trained by seenuvasanfoss. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_question_answering_base_pipeline_en_5.5.0_3.0_1725240702021.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_question_answering_base_pipeline_en_5.5.0_3.0_1725240702021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_deberta_question_answering_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_deberta_question_answering_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_deberta_question_answering_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|550.7 MB| + +## References + +https://huggingface.co/seenuvasanfoss/fine_tuned_deberta_question_answering_base + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_indic_en.md b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_indic_en.md new file mode 100644 index 00000000000000..cf452c52020e54 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_indic_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fine_tuned_indic AlbertForQuestionAnswering from manasbarman +author: John Snow Labs +name: fine_tuned_indic +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indic` is a English model originally trained by manasbarman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indic_en_5.5.0_3.0_1725236975149.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indic_en_5.5.0_3.0_1725236975149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("fine_tuned_indic","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("fine_tuned_indic", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|125.5 MB| + +## References + +https://huggingface.co/manasbarman/fine-tuned-indic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_indic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_indic_pipeline_en.md new file mode 100644 index 00000000000000..c8a4b74e510aba --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_indic_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tuned_indic_pipeline pipeline AlbertForQuestionAnswering from manasbarman +author: John Snow Labs +name: fine_tuned_indic_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indic_pipeline` is a English model originally trained by manasbarman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indic_pipeline_en_5.5.0_3.0_1725236982034.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indic_pipeline_en_5.5.0_3.0_1725236982034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_indic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_indic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|125.5 MB| + +## References + +https://huggingface.co/manasbarman/fine-tuned-indic + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_united_airlines_twitter_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_united_airlines_twitter_sentiment_analysis_pipeline_en.md new file mode 100644 index 00000000000000..48cc1d879dab4b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_united_airlines_twitter_sentiment_analysis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fine_tuned_united_airlines_twitter_sentiment_analysis_pipeline pipeline DistilBertForSequenceClassification from Kayyyy27 +author: John Snow Labs +name: fine_tuned_united_airlines_twitter_sentiment_analysis_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_united_airlines_twitter_sentiment_analysis_pipeline` is a English model originally trained by Kayyyy27. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_united_airlines_twitter_sentiment_analysis_pipeline_en_5.5.0_3.0_1725306101027.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_united_airlines_twitter_sentiment_analysis_pipeline_en_5.5.0_3.0_1725306101027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_united_airlines_twitter_sentiment_analysis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_united_airlines_twitter_sentiment_analysis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_united_airlines_twitter_sentiment_analysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Kayyyy27/fine-tuned-United_Airlines_Twitter_Sentiment_Analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_bge_small_english_v1_5_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_bge_small_english_v1_5_en.md new file mode 100644 index 00000000000000..b1c98cc0d23221 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_bge_small_english_v1_5_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English finetuned_bge_small_english_v1_5 BGEEmbeddings from Jjzzzz +author: John Snow Labs +name: finetuned_bge_small_english_v1_5 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_small_english_v1_5` is a English model originally trained by Jjzzzz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bge_small_english_v1_5_en_5.5.0_3.0_1725241960341.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_small_english_v1_5_en_5.5.0_3.0_1725241960341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("finetuned_bge_small_english_v1_5","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("finetuned_bge_small_english_v1_5","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bge_small_english_v1_5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|78.9 MB| + +## References + +https://huggingface.co/Jjzzzz/finetuned_bge-small-en-v1.5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_bge_small_english_v1_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_bge_small_english_v1_5_pipeline_en.md new file mode 100644 index 00000000000000..1eee218c4bb9c3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_bge_small_english_v1_5_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English finetuned_bge_small_english_v1_5_pipeline pipeline BGEEmbeddings from Jjzzzz +author: John Snow Labs +name: finetuned_bge_small_english_v1_5_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_small_english_v1_5_pipeline` is a English model originally trained by Jjzzzz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bge_small_english_v1_5_pipeline_en_5.5.0_3.0_1725241986101.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_small_english_v1_5_pipeline_en_5.5.0_3.0_1725241986101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_bge_small_english_v1_5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_bge_small_english_v1_5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bge_small_english_v1_5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|78.9 MB| + +## References + +https://huggingface.co/Jjzzzz/finetuned_bge-small-en-v1.5 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_classification_model_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_classification_model_en.md new file mode 100644 index 00000000000000..500d9b92662e9d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_classification_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_classification_model DistilBertForSequenceClassification from Mr-Vicky-01 +author: John Snow Labs +name: finetuned_classification_model +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_classification_model` is a English model originally trained by Mr-Vicky-01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_classification_model_en_5.5.0_3.0_1725305634884.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_classification_model_en_5.5.0_3.0_1725305634884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuned_classification_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuned_classification_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_classification_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Mr-Vicky-01/finetuned_classification_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_ditilbert_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_ditilbert_en.md new file mode 100644 index 00000000000000..fec996ee8adc87 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_ditilbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_ditilbert DistilBertForTokenClassification from Gkumi +author: John Snow Labs +name: finetuned_ditilbert +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_ditilbert` is a English model originally trained by Gkumi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_ditilbert_en_5.5.0_3.0_1725267509633.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_ditilbert_en_5.5.0_3.0_1725267509633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("finetuned_ditilbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("finetuned_ditilbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_ditilbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|244.1 MB| + +## References + +https://huggingface.co/Gkumi/finetuned-ditilbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_ditilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_ditilbert_pipeline_en.md new file mode 100644 index 00000000000000..44b486a1312e2f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_ditilbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_ditilbert_pipeline pipeline DistilBertForTokenClassification from Gkumi +author: John Snow Labs +name: finetuned_ditilbert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_ditilbert_pipeline` is a English model originally trained by Gkumi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_ditilbert_pipeline_en_5.5.0_3.0_1725267523277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_ditilbert_pipeline_en_5.5.0_3.0_1725267523277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_ditilbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_ditilbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_ditilbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|244.1 MB| + +## References + +https://huggingface.co/Gkumi/finetuned-ditilbert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_en.md new file mode 100644 index 00000000000000..14870eefde2672 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English finetuned_four_epoch_multi_qa_mpnet_base_dot_v1 MPNetEmbeddings from mustozsarac +author: John Snow Labs +name: finetuned_four_epoch_multi_qa_mpnet_base_dot_v1 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_four_epoch_multi_qa_mpnet_base_dot_v1` is a English model originally trained by mustozsarac. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_en_5.5.0_3.0_1725258578602.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_en_5.5.0_3.0_1725258578602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("finetuned_four_epoch_multi_qa_mpnet_base_dot_v1","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("finetuned_four_epoch_multi_qa_mpnet_base_dot_v1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_four_epoch_multi_qa_mpnet_base_dot_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/mustozsarac/finetuned-four-epoch-multi-qa-mpnet-base-dot-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_pipeline_en.md new file mode 100644 index 00000000000000..410a156de95216 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_pipeline pipeline MPNetEmbeddings from mustozsarac +author: John Snow Labs +name: finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_pipeline` is a English model originally trained by mustozsarac. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_pipeline_en_5.5.0_3.0_1725258600096.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_pipeline_en_5.5.0_3.0_1725258600096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_four_epoch_multi_qa_mpnet_base_dot_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/mustozsarac/finetuned-four-epoch-multi-qa-mpnet-base-dot-v1 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_marianmtmodel_ccmatrix77k_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_marianmtmodel_ccmatrix77k_en.md new file mode 100644 index 00000000000000..c4c3c44d968941 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_marianmtmodel_ccmatrix77k_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_marianmtmodel_ccmatrix77k MarianTransformer from HugginJake +author: John Snow Labs +name: finetuned_marianmtmodel_ccmatrix77k +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_marianmtmodel_ccmatrix77k` is a English model originally trained by HugginJake. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_marianmtmodel_ccmatrix77k_en_5.5.0_3.0_1725294954147.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_marianmtmodel_ccmatrix77k_en_5.5.0_3.0_1725294954147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("finetuned_marianmtmodel_ccmatrix77k","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("finetuned_marianmtmodel_ccmatrix77k","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_marianmtmodel_ccmatrix77k| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|509.6 MB| + +## References + +https://huggingface.co/HugginJake/Finetuned_MarianMTModel_ccmatrix77k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_marianmtmodel_ccmatrix77k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_marianmtmodel_ccmatrix77k_pipeline_en.md new file mode 100644 index 00000000000000..9135a33253cd04 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_marianmtmodel_ccmatrix77k_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_marianmtmodel_ccmatrix77k_pipeline pipeline MarianTransformer from HugginJake +author: John Snow Labs +name: finetuned_marianmtmodel_ccmatrix77k_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_marianmtmodel_ccmatrix77k_pipeline` is a English model originally trained by HugginJake. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_marianmtmodel_ccmatrix77k_pipeline_en_5.5.0_3.0_1725294982353.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_marianmtmodel_ccmatrix77k_pipeline_en_5.5.0_3.0_1725294982353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_marianmtmodel_ccmatrix77k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_marianmtmodel_ccmatrix77k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_marianmtmodel_ccmatrix77k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|510.1 MB| + +## References + +https://huggingface.co/HugginJake/Finetuned_MarianMTModel_ccmatrix77k + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_opusmt_english_tonga_tonga_islands_hindi_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_opusmt_english_tonga_tonga_islands_hindi_en.md new file mode 100644 index 00000000000000..bd78eb87442010 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_opusmt_english_tonga_tonga_islands_hindi_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_opusmt_english_tonga_tonga_islands_hindi MarianTransformer from Varsha00 +author: John Snow Labs +name: finetuned_opusmt_english_tonga_tonga_islands_hindi +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_opusmt_english_tonga_tonga_islands_hindi` is a English model originally trained by Varsha00. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_opusmt_english_tonga_tonga_islands_hindi_en_5.5.0_3.0_1725295629136.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_opusmt_english_tonga_tonga_islands_hindi_en_5.5.0_3.0_1725295629136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("finetuned_opusmt_english_tonga_tonga_islands_hindi","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("finetuned_opusmt_english_tonga_tonga_islands_hindi","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_opusmt_english_tonga_tonga_islands_hindi| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|530.1 MB| + +## References + +https://huggingface.co/Varsha00/finetuned-opusmt-en-to-hi \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_random6_1epoch_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_random6_1epoch_en.md new file mode 100644 index 00000000000000..31bd1650474645 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_random6_1epoch_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English finetuned_random6_1epoch MPNetEmbeddings from jhsmith +author: John Snow Labs +name: finetuned_random6_1epoch +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_random6_1epoch` is a English model originally trained by jhsmith. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_random6_1epoch_en_5.5.0_3.0_1725281077708.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_random6_1epoch_en_5.5.0_3.0_1725281077708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("finetuned_random6_1epoch","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("finetuned_random6_1epoch","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_random6_1epoch| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.4 MB| + +## References + +https://huggingface.co/jhsmith/finetuned_random6_1epoch \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_random6_1epoch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_random6_1epoch_pipeline_en.md new file mode 100644 index 00000000000000..5626ca921b0d1f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_random6_1epoch_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English finetuned_random6_1epoch_pipeline pipeline MPNetEmbeddings from jhsmith +author: John Snow Labs +name: finetuned_random6_1epoch_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_random6_1epoch_pipeline` is a English model originally trained by jhsmith. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_random6_1epoch_pipeline_en_5.5.0_3.0_1725281098948.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_random6_1epoch_pipeline_en_5.5.0_3.0_1725281098948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_random6_1epoch_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_random6_1epoch_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_random6_1epoch_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.4 MB| + +## References + +https://huggingface.co/jhsmith/finetuned_random6_1epoch + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_en.md new file mode 100644 index 00000000000000..4d1be8aa0899a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50 DistilBertForTokenClassification from ali2066 +author: John Snow Labs +name: finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50` is a English model originally trained by ali2066. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_en_5.5.0_3.0_1725267284583.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_en_5.5.0_3.0_1725267284583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/ali2066/finetuned_token_itr0_3e-05_webDiscourse_16_02_2022-20_59_50 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_pipeline_en.md new file mode 100644 index 00000000000000..a9998a9b22721b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_pipeline pipeline DistilBertForTokenClassification from ali2066 +author: John Snow Labs +name: finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_pipeline` is a English model originally trained by ali2066. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_pipeline_en_5.5.0_3.0_1725267303385.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_pipeline_en_5.5.0_3.0_1725267303385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_token_itr0_3e_05_webdiscourse_16_02_2022_20_59_50_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/ali2066/finetuned_token_itr0_3e-05_webDiscourse_16_02_2022-20_59_50 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_anik02_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_anik02_en.md new file mode 100644 index 00000000000000..6c3c1fd37abb43 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_anik02_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuning_sentiment_model_3000_samples_anik02 DistilBertForSequenceClassification from Anik02 +author: John Snow Labs +name: finetuning_sentiment_model_3000_samples_anik02 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_anik02` is a English model originally trained by Anik02. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_anik02_en_5.5.0_3.0_1725305902889.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_anik02_en_5.5.0_3.0_1725305902889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_anik02","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_anik02", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_3000_samples_anik02| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Anik02/finetuning-sentiment-model-3000-samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_anik02_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_anik02_pipeline_en.md new file mode 100644 index 00000000000000..b45ed27177a55f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_anik02_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuning_sentiment_model_3000_samples_anik02_pipeline pipeline DistilBertForSequenceClassification from Anik02 +author: John Snow Labs +name: finetuning_sentiment_model_3000_samples_anik02_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_anik02_pipeline` is a English model originally trained by Anik02. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_anik02_pipeline_en_5.5.0_3.0_1725305915554.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_anik02_pipeline_en_5.5.0_3.0_1725305915554.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_anik02_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_anik02_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_3000_samples_anik02_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Anik02/finetuning-sentiment-model-3000-samples + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_bloodyaca_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_bloodyaca_en.md new file mode 100644 index 00000000000000..8ec16a428722f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_bloodyaca_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuning_sentiment_model_3000_samples_bloodyaca DistilBertForSequenceClassification from bloodyaca +author: John Snow Labs +name: finetuning_sentiment_model_3000_samples_bloodyaca +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_bloodyaca` is a English model originally trained by bloodyaca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_bloodyaca_en_5.5.0_3.0_1725292217479.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_bloodyaca_en_5.5.0_3.0_1725292217479.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_bloodyaca","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_bloodyaca", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_3000_samples_bloodyaca| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/bloodyaca/finetuning-sentiment-model-3000-samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_bloodyaca_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_bloodyaca_pipeline_en.md new file mode 100644 index 00000000000000..c569bf7f0533c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_bloodyaca_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuning_sentiment_model_3000_samples_bloodyaca_pipeline pipeline DistilBertForSequenceClassification from bloodyaca +author: John Snow Labs +name: finetuning_sentiment_model_3000_samples_bloodyaca_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_bloodyaca_pipeline` is a English model originally trained by bloodyaca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_bloodyaca_pipeline_en_5.5.0_3.0_1725292230921.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_bloodyaca_pipeline_en_5.5.0_3.0_1725292230921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_bloodyaca_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_bloodyaca_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_3000_samples_bloodyaca_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/bloodyaca/finetuning-sentiment-model-3000-samples + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_thp99_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_thp99_pipeline_en.md new file mode 100644 index 00000000000000..ac254c382c2809 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_thp99_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuning_sentiment_model_3000_samples_thp99_pipeline pipeline DistilBertForSequenceClassification from ThP99 +author: John Snow Labs +name: finetuning_sentiment_model_3000_samples_thp99_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_thp99_pipeline` is a English model originally trained by ThP99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_thp99_pipeline_en_5.5.0_3.0_1725306000604.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_thp99_pipeline_en_5.5.0_3.0_1725306000604.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_thp99_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_thp99_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_3000_samples_thp99_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/ThP99/finetuning-sentiment-model-3000-samples + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3004_samples_vaishu23_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3004_samples_vaishu23_en.md new file mode 100644 index 00000000000000..da9c93888e16c3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3004_samples_vaishu23_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuning_sentiment_model_3004_samples_vaishu23 DistilBertForSequenceClassification from vaishu23 +author: John Snow Labs +name: finetuning_sentiment_model_3004_samples_vaishu23 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3004_samples_vaishu23` is a English model originally trained by vaishu23. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3004_samples_vaishu23_en_5.5.0_3.0_1725305803025.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3004_samples_vaishu23_en_5.5.0_3.0_1725305803025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3004_samples_vaishu23","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3004_samples_vaishu23", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_3004_samples_vaishu23| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/vaishu23/finetuning-sentiment-model-3004-samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_hw6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_hw6_pipeline_en.md new file mode 100644 index 00000000000000..7b503d2a0ef933 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_hw6_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuning_sentiment_model_hw6_pipeline pipeline DistilBertForSequenceClassification from anosognosie +author: John Snow Labs +name: finetuning_sentiment_model_hw6_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_hw6_pipeline` is a English model originally trained by anosognosie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_hw6_pipeline_en_5.5.0_3.0_1725305975790.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_hw6_pipeline_en_5.5.0_3.0_1725305975790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuning_sentiment_model_hw6_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuning_sentiment_model_hw6_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_hw6_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/anosognosie/finetuning-sentiment-model-hw6 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetunned_legal_deberta_v3_base_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetunned_legal_deberta_v3_base_en.md new file mode 100644 index 00000000000000..da8139087e9220 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetunned_legal_deberta_v3_base_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English finetunned_legal_deberta_v3_base DeBertaForQuestionAnswering from satishsingh90 +author: John Snow Labs +name: finetunned_legal_deberta_v3_base +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetunned_legal_deberta_v3_base` is a English model originally trained by satishsingh90. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetunned_legal_deberta_v3_base_en_5.5.0_3.0_1725240218701.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetunned_legal_deberta_v3_base_en_5.5.0_3.0_1725240218701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("finetunned_legal_deberta_v3_base","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("finetunned_legal_deberta_v3_base", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetunned_legal_deberta_v3_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|569.2 MB| + +## References + +https://huggingface.co/satishsingh90/finetunned_legal_deberta_v3_base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetunned_legal_deberta_v3_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetunned_legal_deberta_v3_base_pipeline_en.md new file mode 100644 index 00000000000000..7e8f9610e0f68f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-finetunned_legal_deberta_v3_base_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English finetunned_legal_deberta_v3_base_pipeline pipeline DeBertaForQuestionAnswering from satishsingh90 +author: John Snow Labs +name: finetunned_legal_deberta_v3_base_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetunned_legal_deberta_v3_base_pipeline` is a English model originally trained by satishsingh90. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetunned_legal_deberta_v3_base_pipeline_en_5.5.0_3.0_1725240299329.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetunned_legal_deberta_v3_base_pipeline_en_5.5.0_3.0_1725240299329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetunned_legal_deberta_v3_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetunned_legal_deberta_v3_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetunned_legal_deberta_v3_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|569.2 MB| + +## References + +https://huggingface.co/satishsingh90/finetunned_legal_deberta_v3_base + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fn_jll_hackathon_fine_tuned_qa_albert_squad_en.md b/docs/_posts/ahmedlone127/2024-09-02-fn_jll_hackathon_fine_tuned_qa_albert_squad_en.md new file mode 100644 index 00000000000000..d6cc1a66826262 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fn_jll_hackathon_fine_tuned_qa_albert_squad_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fn_jll_hackathon_fine_tuned_qa_albert_squad AlbertForQuestionAnswering from FredNajjar +author: John Snow Labs +name: fn_jll_hackathon_fine_tuned_qa_albert_squad +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fn_jll_hackathon_fine_tuned_qa_albert_squad` is a English model originally trained by FredNajjar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fn_jll_hackathon_fine_tuned_qa_albert_squad_en_5.5.0_3.0_1725309936873.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fn_jll_hackathon_fine_tuned_qa_albert_squad_en_5.5.0_3.0_1725309936873.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("fn_jll_hackathon_fine_tuned_qa_albert_squad","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("fn_jll_hackathon_fine_tuned_qa_albert_squad", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fn_jll_hackathon_fine_tuned_qa_albert_squad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/FredNajjar/FN_JLL-Hackathon-Fine-Tuned_QA-ALBERT-SQuAD \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-fn_jll_hackathon_fine_tuned_qa_albert_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-fn_jll_hackathon_fine_tuned_qa_albert_squad_pipeline_en.md new file mode 100644 index 00000000000000..56d2db2ef541bc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-fn_jll_hackathon_fine_tuned_qa_albert_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fn_jll_hackathon_fine_tuned_qa_albert_squad_pipeline pipeline AlbertForQuestionAnswering from FredNajjar +author: John Snow Labs +name: fn_jll_hackathon_fine_tuned_qa_albert_squad_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fn_jll_hackathon_fine_tuned_qa_albert_squad_pipeline` is a English model originally trained by FredNajjar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fn_jll_hackathon_fine_tuned_qa_albert_squad_pipeline_en_5.5.0_3.0_1725309939308.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fn_jll_hackathon_fine_tuned_qa_albert_squad_pipeline_en_5.5.0_3.0_1725309939308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fn_jll_hackathon_fine_tuned_qa_albert_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fn_jll_hackathon_fine_tuned_qa_albert_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fn_jll_hackathon_fine_tuned_qa_albert_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/FredNajjar/FN_JLL-Hackathon-Fine-Tuned_QA-ALBERT-SQuAD + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_pipeline_en.md new file mode 100644 index 00000000000000..5cead793f1ec02 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_pipeline pipeline MPNetEmbeddings from DragosGorduza +author: John Snow Labs +name: frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_pipeline` is a English model originally trained by DragosGorduza. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_pipeline_en_5.5.0_3.0_1725314018039.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_pipeline_en_5.5.0_3.0_1725314018039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/DragosGorduza/FRPile_GPL_test_pipeline_all-mpnet-base-v2_14000 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ganda_english_ai_lab_makerere_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ganda_english_ai_lab_makerere_pipeline_en.md new file mode 100644 index 00000000000000..08673468021ca1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ganda_english_ai_lab_makerere_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ganda_english_ai_lab_makerere_pipeline pipeline MarianTransformer from AI-Lab-Makerere +author: John Snow Labs +name: ganda_english_ai_lab_makerere_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ganda_english_ai_lab_makerere_pipeline` is a English model originally trained by AI-Lab-Makerere. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ganda_english_ai_lab_makerere_pipeline_en_5.5.0_3.0_1725295510905.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ganda_english_ai_lab_makerere_pipeline_en_5.5.0_3.0_1725295510905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ganda_english_ai_lab_makerere_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ganda_english_ai_lab_makerere_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ganda_english_ai_lab_makerere_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|533.0 MB| + +## References + +https://huggingface.co/AI-Lab-Makerere/lg_en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-german_english_translation_en.md b/docs/_posts/ahmedlone127/2024-09-02-german_english_translation_en.md new file mode 100644 index 00000000000000..f35c2c313067f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-german_english_translation_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English german_english_translation MarianTransformer from alina1997 +author: John Snow Labs +name: german_english_translation +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`german_english_translation` is a English model originally trained by alina1997. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/german_english_translation_en_5.5.0_3.0_1725243228751.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/german_english_translation_en_5.5.0_3.0_1725243228751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("german_english_translation","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("german_english_translation","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|german_english_translation| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|499.4 MB| + +## References + +https://huggingface.co/alina1997/de_en_translation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-german_english_translation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-german_english_translation_pipeline_en.md new file mode 100644 index 00000000000000..902cf0d862bf82 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-german_english_translation_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English german_english_translation_pipeline pipeline MarianTransformer from alina1997 +author: John Snow Labs +name: german_english_translation_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`german_english_translation_pipeline` is a English model originally trained by alina1997. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/german_english_translation_pipeline_en_5.5.0_3.0_1725243260202.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/german_english_translation_pipeline_en_5.5.0_3.0_1725243260202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("german_english_translation_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("german_english_translation_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|german_english_translation_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|499.9 MB| + +## References + +https://huggingface.co/alina1997/de_en_translation + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-german_sentiment_en.md b/docs/_posts/ahmedlone127/2024-09-02-german_sentiment_en.md new file mode 100644 index 00000000000000..b01a45e7775e5a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-german_sentiment_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English german_sentiment DistilBertForSequenceClassification from swapnasa +author: John Snow Labs +name: german_sentiment +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`german_sentiment` is a English model originally trained by swapnasa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/german_sentiment_en_5.5.0_3.0_1725306273726.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/german_sentiment_en_5.5.0_3.0_1725306273726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("german_sentiment","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("german_sentiment", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|german_sentiment| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.6 MB| + +## References + +https://huggingface.co/swapnasa/german_sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-gilberto_uncased_from_camembert_fast_tokenizer_en.md b/docs/_posts/ahmedlone127/2024-09-02-gilberto_uncased_from_camembert_fast_tokenizer_en.md new file mode 100644 index 00000000000000..5aa4dd8fc4eaa0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-gilberto_uncased_from_camembert_fast_tokenizer_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English gilberto_uncased_from_camembert_fast_tokenizer CamemBertEmbeddings from ai-models +author: John Snow Labs +name: gilberto_uncased_from_camembert_fast_tokenizer +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gilberto_uncased_from_camembert_fast_tokenizer` is a English model originally trained by ai-models. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gilberto_uncased_from_camembert_fast_tokenizer_en_5.5.0_3.0_1725320122430.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gilberto_uncased_from_camembert_fast_tokenizer_en_5.5.0_3.0_1725320122430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("gilberto_uncased_from_camembert_fast_tokenizer","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("gilberto_uncased_from_camembert_fast_tokenizer","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gilberto_uncased_from_camembert_fast_tokenizer| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|262.9 MB| + +## References + +https://huggingface.co/ai-models/gilberto-uncased-from-camembert-fast-tokenizer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-gilberto_uncased_from_camembert_fast_tokenizer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-gilberto_uncased_from_camembert_fast_tokenizer_pipeline_en.md new file mode 100644 index 00000000000000..6fa4e279872b17 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-gilberto_uncased_from_camembert_fast_tokenizer_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English gilberto_uncased_from_camembert_fast_tokenizer_pipeline pipeline CamemBertEmbeddings from ai-models +author: John Snow Labs +name: gilberto_uncased_from_camembert_fast_tokenizer_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gilberto_uncased_from_camembert_fast_tokenizer_pipeline` is a English model originally trained by ai-models. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gilberto_uncased_from_camembert_fast_tokenizer_pipeline_en_5.5.0_3.0_1725320200943.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gilberto_uncased_from_camembert_fast_tokenizer_pipeline_en_5.5.0_3.0_1725320200943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gilberto_uncased_from_camembert_fast_tokenizer_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gilberto_uncased_from_camembert_fast_tokenizer_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gilberto_uncased_from_camembert_fast_tokenizer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|262.9 MB| + +## References + +https://huggingface.co/ai-models/gilberto-uncased-from-camembert-fast-tokenizer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-github_samples_tclassifier_en.md b/docs/_posts/ahmedlone127/2024-09-02-github_samples_tclassifier_en.md new file mode 100644 index 00000000000000..5387351ee8bca3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-github_samples_tclassifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English github_samples_tclassifier DistilBertForSequenceClassification from h1alexbel +author: John Snow Labs +name: github_samples_tclassifier +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`github_samples_tclassifier` is a English model originally trained by h1alexbel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/github_samples_tclassifier_en_5.5.0_3.0_1725292211118.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/github_samples_tclassifier_en_5.5.0_3.0_1725292211118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("github_samples_tclassifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("github_samples_tclassifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|github_samples_tclassifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/h1alexbel/github-samples-tclassifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-good_vibes_en.md b/docs/_posts/ahmedlone127/2024-09-02-good_vibes_en.md new file mode 100644 index 00000000000000..7611be78836e3c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-good_vibes_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English good_vibes AlbertForSequenceClassification from dejanseo +author: John Snow Labs +name: good_vibes +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`good_vibes` is a English model originally trained by dejanseo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/good_vibes_en_5.5.0_3.0_1725278791252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/good_vibes_en_5.5.0_3.0_1725278791252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("good_vibes","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("good_vibes", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|good_vibes| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/dejanseo/good-vibes \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-good_vibes_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-good_vibes_pipeline_en.md new file mode 100644 index 00000000000000..d17b35f9b0a009 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-good_vibes_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English good_vibes_pipeline pipeline AlbertForSequenceClassification from dejanseo +author: John Snow Labs +name: good_vibes_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`good_vibes_pipeline` is a English model originally trained by dejanseo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/good_vibes_pipeline_en_5.5.0_3.0_1725278793770.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/good_vibes_pipeline_en_5.5.0_3.0_1725278793770.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("good_vibes_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("good_vibes_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|good_vibes_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/dejanseo/good-vibes + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-gpl_e5_base_unsupervised_arguana_k10_en.md b/docs/_posts/ahmedlone127/2024-09-02-gpl_e5_base_unsupervised_arguana_k10_en.md new file mode 100644 index 00000000000000..32b9bc2b81c433 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-gpl_e5_base_unsupervised_arguana_k10_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English gpl_e5_base_unsupervised_arguana_k10 E5Embeddings from rithwik-db +author: John Snow Labs +name: gpl_e5_base_unsupervised_arguana_k10 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpl_e5_base_unsupervised_arguana_k10` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_arguana_k10_en_5.5.0_3.0_1725259982755.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_arguana_k10_en_5.5.0_3.0_1725259982755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("gpl_e5_base_unsupervised_arguana_k10","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("gpl_e5_base_unsupervised_arguana_k10","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gpl_e5_base_unsupervised_arguana_k10| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|400.3 MB| + +## References + +https://huggingface.co/rithwik-db/gpl-e5-base-unsupervised-arguana-k10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-gpl_e5_base_unsupervised_arguana_k10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-gpl_e5_base_unsupervised_arguana_k10_pipeline_en.md new file mode 100644 index 00000000000000..78a4d44433b1ee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-gpl_e5_base_unsupervised_arguana_k10_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English gpl_e5_base_unsupervised_arguana_k10_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: gpl_e5_base_unsupervised_arguana_k10_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpl_e5_base_unsupervised_arguana_k10_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_arguana_k10_pipeline_en_5.5.0_3.0_1725260005929.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_arguana_k10_pipeline_en_5.5.0_3.0_1725260005929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gpl_e5_base_unsupervised_arguana_k10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gpl_e5_base_unsupervised_arguana_k10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gpl_e5_base_unsupervised_arguana_k10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|400.3 MB| + +## References + +https://huggingface.co/rithwik-db/gpl-e5-base-unsupervised-arguana-k10 + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-gujarati_in_devanagari_xlm_r_base_gu.md b/docs/_posts/ahmedlone127/2024-09-02-gujarati_in_devanagari_xlm_r_base_gu.md new file mode 100644 index 00000000000000..459d5d8db976a4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-gujarati_in_devanagari_xlm_r_base_gu.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Gujarati gujarati_in_devanagari_xlm_r_base XlmRoBertaEmbeddings from ashwani-tanwar +author: John Snow Labs +name: gujarati_in_devanagari_xlm_r_base +date: 2024-09-02 +tags: [gu, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: gu +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gujarati_in_devanagari_xlm_r_base` is a Gujarati model originally trained by ashwani-tanwar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gujarati_in_devanagari_xlm_r_base_gu_5.5.0_3.0_1725271261471.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gujarati_in_devanagari_xlm_r_base_gu_5.5.0_3.0_1725271261471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("gujarati_in_devanagari_xlm_r_base","gu") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("gujarati_in_devanagari_xlm_r_base","gu") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gujarati_in_devanagari_xlm_r_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|gu| +|Size:|652.8 MB| + +## References + +https://huggingface.co/ashwani-tanwar/Gujarati-in-Devanagari-XLM-R-Base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-gujarati_in_devanagari_xlm_r_base_pipeline_gu.md b/docs/_posts/ahmedlone127/2024-09-02-gujarati_in_devanagari_xlm_r_base_pipeline_gu.md new file mode 100644 index 00000000000000..4aab0d1653882d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-gujarati_in_devanagari_xlm_r_base_pipeline_gu.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Gujarati gujarati_in_devanagari_xlm_r_base_pipeline pipeline XlmRoBertaEmbeddings from ashwani-tanwar +author: John Snow Labs +name: gujarati_in_devanagari_xlm_r_base_pipeline +date: 2024-09-02 +tags: [gu, open_source, pipeline, onnx] +task: Embeddings +language: gu +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gujarati_in_devanagari_xlm_r_base_pipeline` is a Gujarati model originally trained by ashwani-tanwar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gujarati_in_devanagari_xlm_r_base_pipeline_gu_5.5.0_3.0_1725271457087.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gujarati_in_devanagari_xlm_r_base_pipeline_gu_5.5.0_3.0_1725271457087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gujarati_in_devanagari_xlm_r_base_pipeline", lang = "gu") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gujarati_in_devanagari_xlm_r_base_pipeline", lang = "gu") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gujarati_in_devanagari_xlm_r_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|gu| +|Size:|652.8 MB| + +## References + +https://huggingface.co/ashwani-tanwar/Gujarati-in-Devanagari-XLM-R-Base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-hel_french_english_4_layers_en.md b/docs/_posts/ahmedlone127/2024-09-02-hel_french_english_4_layers_en.md new file mode 100644 index 00000000000000..b103d230391f96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-hel_french_english_4_layers_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hel_french_english_4_layers MarianTransformer from Momo200519 +author: John Snow Labs +name: hel_french_english_4_layers +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hel_french_english_4_layers` is a English model originally trained by Momo200519. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hel_french_english_4_layers_en_5.5.0_3.0_1725243134492.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hel_french_english_4_layers_en_5.5.0_3.0_1725243134492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("hel_french_english_4_layers","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("hel_french_english_4_layers","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hel_french_english_4_layers| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|507.4 MB| + +## References + +https://huggingface.co/Momo200519/hel_fr_en_4_layers \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-hel_french_english_4_layers_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-hel_french_english_4_layers_pipeline_en.md new file mode 100644 index 00000000000000..8e534eb1d8ccae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-hel_french_english_4_layers_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hel_french_english_4_layers_pipeline pipeline MarianTransformer from Momo200519 +author: John Snow Labs +name: hel_french_english_4_layers_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hel_french_english_4_layers_pipeline` is a English model originally trained by Momo200519. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hel_french_english_4_layers_pipeline_en_5.5.0_3.0_1725243161626.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hel_french_english_4_layers_pipeline_en_5.5.0_3.0_1725243161626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hel_french_english_4_layers_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hel_french_english_4_layers_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hel_french_english_4_layers_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.0 MB| + +## References + +https://huggingface.co/Momo200519/hel_fr_en_4_layers + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_pipeline_en.md new file mode 100644 index 00000000000000..6805630a4da47b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_pipeline pipeline MarianTransformer from MikolajDeja +author: John Snow Labs +name: helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_pipeline` is a English model originally trained by MikolajDeja. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_pipeline_en_5.5.0_3.0_1725244120521.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_pipeline_en_5.5.0_3.0_1725244120521.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|529.9 MB| + +## References + +https://huggingface.co/MikolajDeja/Helsinki-NLP-opus-mt-pl-en-yhavinga-ccmatrix-finetune + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-helsinki_translation_english_moroccan_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-helsinki_translation_english_moroccan_arabic_pipeline_en.md new file mode 100644 index 00000000000000..12fa81d69f01c3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-helsinki_translation_english_moroccan_arabic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English helsinki_translation_english_moroccan_arabic_pipeline pipeline MarianTransformer from lachkarsalim +author: John Snow Labs +name: helsinki_translation_english_moroccan_arabic_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_translation_english_moroccan_arabic_pipeline` is a English model originally trained by lachkarsalim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_translation_english_moroccan_arabic_pipeline_en_5.5.0_3.0_1725295006559.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_translation_english_moroccan_arabic_pipeline_en_5.5.0_3.0_1725295006559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("helsinki_translation_english_moroccan_arabic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("helsinki_translation_english_moroccan_arabic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|helsinki_translation_english_moroccan_arabic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.4 GB| + +## References + +https://huggingface.co/lachkarsalim/Helsinki-translation-English_Moroccan-Arabic + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_en.md b/docs/_posts/ahmedlone127/2024-09-02-hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_en.md new file mode 100644 index 00000000000000..dfa27097f067fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba MarianTransformer from beanslmao +author: John Snow Labs +name: hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba` is a English model originally trained by beanslmao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_en_5.5.0_3.0_1725304698532.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_en_5.5.0_3.0_1725304698532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|540.0 MB| + +## References + +https://huggingface.co/beanslmao/hensinki-en-es-finetuned-english-to-spanish-tateoba \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_pipeline_en.md new file mode 100644 index 00000000000000..189c37a87c9754 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_pipeline pipeline MarianTransformer from beanslmao +author: John Snow Labs +name: hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_pipeline` is a English model originally trained by beanslmao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_pipeline_en_5.5.0_3.0_1725304726407.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_pipeline_en_5.5.0_3.0_1725304726407.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hensinki_english_spanish_finetuned_english_tonga_tonga_islands_spanish_tateoba_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|540.5 MB| + +## References + +https://huggingface.co/beanslmao/hensinki-en-es-finetuned-english-to-spanish-tateoba + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-hh_labeler_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-hh_labeler_pipeline_en.md new file mode 100644 index 00000000000000..f51c937df78e9a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-hh_labeler_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hh_labeler_pipeline pipeline DistilBertForSequenceClassification from davidgaofc +author: John Snow Labs +name: hh_labeler_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hh_labeler_pipeline` is a English model originally trained by davidgaofc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hh_labeler_pipeline_en_5.5.0_3.0_1725291829296.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hh_labeler_pipeline_en_5.5.0_3.0_1725291829296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hh_labeler_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hh_labeler_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hh_labeler_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/davidgaofc/hh-labeler + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-hinglish_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-hinglish_bert_pipeline_en.md new file mode 100644 index 00000000000000..5490b93478fa43 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-hinglish_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hinglish_bert_pipeline pipeline BertEmbeddings from nirantk +author: John Snow Labs +name: hinglish_bert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hinglish_bert_pipeline` is a English model originally trained by nirantk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hinglish_bert_pipeline_en_5.5.0_3.0_1725318436751.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hinglish_bert_pipeline_en_5.5.0_3.0_1725318436751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hinglish_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hinglish_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hinglish_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|665.0 MB| + +## References + +https://huggingface.co/nirantk/hinglish-bert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-hub_repoop_1706130115_en.md b/docs/_posts/ahmedlone127/2024-09-02-hub_repoop_1706130115_en.md new file mode 100644 index 00000000000000..83deb4be4b39fa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-hub_repoop_1706130115_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hub_repoop_1706130115 MPNetForSequenceClassification from Kevinger +author: John Snow Labs +name: hub_repoop_1706130115 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, mpnet] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hub_repoop_1706130115` is a English model originally trained by Kevinger. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hub_repoop_1706130115_en_5.5.0_3.0_1725255800074.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hub_repoop_1706130115_en_5.5.0_3.0_1725255800074.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = MPNetForSequenceClassification.pretrained("hub_repoop_1706130115","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = MPNetForSequenceClassification.pretrained("hub_repoop_1706130115", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hub_repoop_1706130115| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/Kevinger/Hub-Repoop-1706130115 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-hub_repoop_1706130115_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-hub_repoop_1706130115_pipeline_en.md new file mode 100644 index 00000000000000..ed33b5dedb5744 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-hub_repoop_1706130115_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hub_repoop_1706130115_pipeline pipeline MPNetForSequenceClassification from Kevinger +author: John Snow Labs +name: hub_repoop_1706130115_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hub_repoop_1706130115_pipeline` is a English model originally trained by Kevinger. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hub_repoop_1706130115_pipeline_en_5.5.0_3.0_1725255821671.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hub_repoop_1706130115_pipeline_en_5.5.0_3.0_1725255821671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hub_repoop_1706130115_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hub_repoop_1706130115_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hub_repoop_1706130115_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/Kevinger/Hub-Repoop-1706130115 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-hub_repoop_1706132005_en.md b/docs/_posts/ahmedlone127/2024-09-02-hub_repoop_1706132005_en.md new file mode 100644 index 00000000000000..e7d88d3ae430c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-hub_repoop_1706132005_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hub_repoop_1706132005 MPNetForSequenceClassification from Kevinger +author: John Snow Labs +name: hub_repoop_1706132005 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, mpnet] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hub_repoop_1706132005` is a English model originally trained by Kevinger. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hub_repoop_1706132005_en_5.5.0_3.0_1725255930920.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hub_repoop_1706132005_en_5.5.0_3.0_1725255930920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = MPNetForSequenceClassification.pretrained("hub_repoop_1706132005","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = MPNetForSequenceClassification.pretrained("hub_repoop_1706132005", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hub_repoop_1706132005| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/Kevinger/Hub-Repoop-1706132005 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-hub_repoop_1706132005_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-hub_repoop_1706132005_pipeline_en.md new file mode 100644 index 00000000000000..e3c7c779b9aa73 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-hub_repoop_1706132005_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hub_repoop_1706132005_pipeline pipeline MPNetForSequenceClassification from Kevinger +author: John Snow Labs +name: hub_repoop_1706132005_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hub_repoop_1706132005_pipeline` is a English model originally trained by Kevinger. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hub_repoop_1706132005_pipeline_en_5.5.0_3.0_1725255951856.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hub_repoop_1706132005_pipeline_en_5.5.0_3.0_1725255951856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hub_repoop_1706132005_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hub_repoop_1706132005_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hub_repoop_1706132005_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/Kevinger/Hub-Repoop-1706132005 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-hypothesismining_english_loc_en.md b/docs/_posts/ahmedlone127/2024-09-02-hypothesismining_english_loc_en.md new file mode 100644 index 00000000000000..9a668471b8d2a3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-hypothesismining_english_loc_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hypothesismining_english_loc RoBertaForSequenceClassification from raruidol +author: John Snow Labs +name: hypothesismining_english_loc +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hypothesismining_english_loc` is a English model originally trained by raruidol. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hypothesismining_english_loc_en_5.5.0_3.0_1725277333400.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hypothesismining_english_loc_en_5.5.0_3.0_1725277333400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("hypothesismining_english_loc","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("hypothesismining_english_loc", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hypothesismining_english_loc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/raruidol/HypothesisMining-EN-Loc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-hypothesismining_english_loc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-hypothesismining_english_loc_pipeline_en.md new file mode 100644 index 00000000000000..3ea3dd016d3db6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-hypothesismining_english_loc_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hypothesismining_english_loc_pipeline pipeline RoBertaForSequenceClassification from raruidol +author: John Snow Labs +name: hypothesismining_english_loc_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hypothesismining_english_loc_pipeline` is a English model originally trained by raruidol. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hypothesismining_english_loc_pipeline_en_5.5.0_3.0_1725277422403.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hypothesismining_english_loc_pipeline_en_5.5.0_3.0_1725277422403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hypothesismining_english_loc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hypothesismining_english_loc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hypothesismining_english_loc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/raruidol/HypothesisMining-EN-Loc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ibert_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-02-ibert_roberta_base_en.md new file mode 100644 index 00000000000000..49060d5ee478c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ibert_roberta_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ibert_roberta_base RoBertaEmbeddings from kssteven +author: John Snow Labs +name: ibert_roberta_base +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ibert_roberta_base` is a English model originally trained by kssteven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ibert_roberta_base_en_5.5.0_3.0_1725264076007.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ibert_roberta_base_en_5.5.0_3.0_1725264076007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("ibert_roberta_base","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("ibert_roberta_base","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ibert_roberta_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|298.2 MB| + +## References + +https://huggingface.co/kssteven/ibert-roberta-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ibert_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ibert_roberta_base_pipeline_en.md new file mode 100644 index 00000000000000..e1d161be641dd6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ibert_roberta_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ibert_roberta_base_pipeline pipeline RoBertaEmbeddings from kssteven +author: John Snow Labs +name: ibert_roberta_base_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ibert_roberta_base_pipeline` is a English model originally trained by kssteven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ibert_roberta_base_pipeline_en_5.5.0_3.0_1725264164658.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ibert_roberta_base_pipeline_en_5.5.0_3.0_1725264164658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ibert_roberta_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ibert_roberta_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ibert_roberta_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|298.2 MB| + +## References + +https://huggingface.co/kssteven/ibert-roberta-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-imdb_distilbert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-02-imdb_distilbert_base_uncased_en.md new file mode 100644 index 00000000000000..088efd343f39b5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-imdb_distilbert_base_uncased_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English imdb_distilbert_base_uncased DistilBertForSequenceClassification from JeremiahZ +author: John Snow Labs +name: imdb_distilbert_base_uncased +date: 2024-09-02 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_distilbert_base_uncased` is a English model originally trained by JeremiahZ. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdb_distilbert_base_uncased_en_5.5.0_3.0_1725292034853.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_distilbert_base_uncased_en_5.5.0_3.0_1725292034853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("imdb_distilbert_base_uncased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("imdb_distilbert_base_uncased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|imdb_distilbert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +References + +https://huggingface.co/JeremiahZ/imdb_distilbert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-imdb_microsoft_deberta_v3_base_seed_2_en.md b/docs/_posts/ahmedlone127/2024-09-02-imdb_microsoft_deberta_v3_base_seed_2_en.md new file mode 100644 index 00000000000000..07d6d56059761b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-imdb_microsoft_deberta_v3_base_seed_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English imdb_microsoft_deberta_v3_base_seed_2 DeBertaForSequenceClassification from utahnlp +author: John Snow Labs +name: imdb_microsoft_deberta_v3_base_seed_2 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_microsoft_deberta_v3_base_seed_2` is a English model originally trained by utahnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdb_microsoft_deberta_v3_base_seed_2_en_5.5.0_3.0_1725281842051.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_microsoft_deberta_v3_base_seed_2_en_5.5.0_3.0_1725281842051.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("imdb_microsoft_deberta_v3_base_seed_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("imdb_microsoft_deberta_v3_base_seed_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|imdb_microsoft_deberta_v3_base_seed_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|642.7 MB| + +## References + +https://huggingface.co/utahnlp/imdb_microsoft_deberta-v3-base_seed-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-imdb_microsoft_deberta_v3_base_seed_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-imdb_microsoft_deberta_v3_base_seed_2_pipeline_en.md new file mode 100644 index 00000000000000..c6aacdbd249b24 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-imdb_microsoft_deberta_v3_base_seed_2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English imdb_microsoft_deberta_v3_base_seed_2_pipeline pipeline DeBertaForSequenceClassification from utahnlp +author: John Snow Labs +name: imdb_microsoft_deberta_v3_base_seed_2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_microsoft_deberta_v3_base_seed_2_pipeline` is a English model originally trained by utahnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdb_microsoft_deberta_v3_base_seed_2_pipeline_en_5.5.0_3.0_1725281894636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_microsoft_deberta_v3_base_seed_2_pipeline_en_5.5.0_3.0_1725281894636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("imdb_microsoft_deberta_v3_base_seed_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("imdb_microsoft_deberta_v3_base_seed_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|imdb_microsoft_deberta_v3_base_seed_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|642.8 MB| + +## References + +https://huggingface.co/utahnlp/imdb_microsoft_deberta-v3-base_seed-2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-immensa_embeddings_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-immensa_embeddings_pipeline_en.md new file mode 100644 index 00000000000000..7b08d9735374eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-immensa_embeddings_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English immensa_embeddings_pipeline pipeline MPNetEmbeddings from engineai +author: John Snow Labs +name: immensa_embeddings_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`immensa_embeddings_pipeline` is a English model originally trained by engineai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/immensa_embeddings_pipeline_en_5.5.0_3.0_1725313563209.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/immensa_embeddings_pipeline_en_5.5.0_3.0_1725313563209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("immensa_embeddings_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("immensa_embeddings_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|immensa_embeddings_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/engineai/immensa_embeddings + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-incel_umberto_en.md b/docs/_posts/ahmedlone127/2024-09-02-incel_umberto_en.md new file mode 100644 index 00000000000000..a455db19c6c9dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-incel_umberto_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English incel_umberto CamemBertEmbeddings from pgajo +author: John Snow Labs +name: incel_umberto +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`incel_umberto` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/incel_umberto_en_5.5.0_3.0_1725301934510.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/incel_umberto_en_5.5.0_3.0_1725301934510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("incel_umberto","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("incel_umberto","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|incel_umberto| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|412.0 MB| + +## References + +https://huggingface.co/pgajo/incel-umberto \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-incel_umberto_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-incel_umberto_pipeline_en.md new file mode 100644 index 00000000000000..20991a53c8b4b0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-incel_umberto_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English incel_umberto_pipeline pipeline CamemBertEmbeddings from pgajo +author: John Snow Labs +name: incel_umberto_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`incel_umberto_pipeline` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/incel_umberto_pipeline_en_5.5.0_3.0_1725301955552.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/incel_umberto_pipeline_en_5.5.0_3.0_1725301955552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("incel_umberto_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("incel_umberto_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|incel_umberto_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.0 MB| + +## References + +https://huggingface.co/pgajo/incel-umberto + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-indic_hindi_bengali_mlm_squad_tydi_mlqa_hi.md b/docs/_posts/ahmedlone127/2024-09-02-indic_hindi_bengali_mlm_squad_tydi_mlqa_hi.md new file mode 100644 index 00000000000000..e81de7001ed2bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-indic_hindi_bengali_mlm_squad_tydi_mlqa_hi.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Hindi indic_hindi_bengali_mlm_squad_tydi_mlqa AlbertForQuestionAnswering from hapandya +author: John Snow Labs +name: indic_hindi_bengali_mlm_squad_tydi_mlqa +date: 2024-09-02 +tags: [hi, open_source, onnx, question_answering, albert] +task: Question Answering +language: hi +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_hindi_bengali_mlm_squad_tydi_mlqa` is a Hindi model originally trained by hapandya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_hindi_bengali_mlm_squad_tydi_mlqa_hi_5.5.0_3.0_1725309959151.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_hindi_bengali_mlm_squad_tydi_mlqa_hi_5.5.0_3.0_1725309959151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("indic_hindi_bengali_mlm_squad_tydi_mlqa","hi") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("indic_hindi_bengali_mlm_squad_tydi_mlqa", "hi") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indic_hindi_bengali_mlm_squad_tydi_mlqa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|hi| +|Size:|125.4 MB| + +## References + +https://huggingface.co/hapandya/indic-hi-bn-MLM-SQuAD-TyDi-MLQA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-indic_hindi_bengali_mlm_squad_tydi_mlqa_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-02-indic_hindi_bengali_mlm_squad_tydi_mlqa_pipeline_hi.md new file mode 100644 index 00000000000000..f173293d4d4076 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-indic_hindi_bengali_mlm_squad_tydi_mlqa_pipeline_hi.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Hindi indic_hindi_bengali_mlm_squad_tydi_mlqa_pipeline pipeline AlbertForQuestionAnswering from hapandya +author: John Snow Labs +name: indic_hindi_bengali_mlm_squad_tydi_mlqa_pipeline +date: 2024-09-02 +tags: [hi, open_source, pipeline, onnx] +task: Question Answering +language: hi +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_hindi_bengali_mlm_squad_tydi_mlqa_pipeline` is a Hindi model originally trained by hapandya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_hindi_bengali_mlm_squad_tydi_mlqa_pipeline_hi_5.5.0_3.0_1725309965724.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_hindi_bengali_mlm_squad_tydi_mlqa_pipeline_hi_5.5.0_3.0_1725309965724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indic_hindi_bengali_mlm_squad_tydi_mlqa_pipeline", lang = "hi") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indic_hindi_bengali_mlm_squad_tydi_mlqa_pipeline", lang = "hi") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indic_hindi_bengali_mlm_squad_tydi_mlqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|hi| +|Size:|125.4 MB| + +## References + +https://huggingface.co/hapandya/indic-hi-bn-MLM-SQuAD-TyDi-MLQA + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-indic_malbert_squad_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-indic_malbert_squad_v2_en.md new file mode 100644 index 00000000000000..53d34c532436cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-indic_malbert_squad_v2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English indic_malbert_squad_v2 AlbertForQuestionAnswering from rohitsroch +author: John Snow Labs +name: indic_malbert_squad_v2 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_malbert_squad_v2` is a English model originally trained by rohitsroch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_malbert_squad_v2_en_5.5.0_3.0_1725236767485.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_malbert_squad_v2_en_5.5.0_3.0_1725236767485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("indic_malbert_squad_v2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("indic_malbert_squad_v2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indic_malbert_squad_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|125.5 MB| + +## References + +https://huggingface.co/rohitsroch/indic-mALBERT-squad-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-indic_malbert_squad_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-indic_malbert_squad_v2_pipeline_en.md new file mode 100644 index 00000000000000..878166751a6cfc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-indic_malbert_squad_v2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English indic_malbert_squad_v2_pipeline pipeline AlbertForQuestionAnswering from rohitsroch +author: John Snow Labs +name: indic_malbert_squad_v2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_malbert_squad_v2_pipeline` is a English model originally trained by rohitsroch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_malbert_squad_v2_pipeline_en_5.5.0_3.0_1725236773720.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_malbert_squad_v2_pipeline_en_5.5.0_3.0_1725236773720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indic_malbert_squad_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indic_malbert_squad_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indic_malbert_squad_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|125.5 MB| + +## References + +https://huggingface.co/rohitsroch/indic-mALBERT-squad-v2 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-indo_roberta_small_pipeline_id.md b/docs/_posts/ahmedlone127/2024-09-02-indo_roberta_small_pipeline_id.md new file mode 100644 index 00000000000000..aa1259e5b3bb6a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-indo_roberta_small_pipeline_id.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Indonesian indo_roberta_small_pipeline pipeline RoBertaEmbeddings from w11wo +author: John Snow Labs +name: indo_roberta_small_pipeline +date: 2024-09-02 +tags: [id, open_source, pipeline, onnx] +task: Embeddings +language: id +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indo_roberta_small_pipeline` is a Indonesian model originally trained by w11wo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indo_roberta_small_pipeline_id_5.5.0_3.0_1725264274053.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indo_roberta_small_pipeline_id_5.5.0_3.0_1725264274053.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indo_roberta_small_pipeline", lang = "id") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indo_roberta_small_pipeline", lang = "id") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indo_roberta_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|id| +|Size:|311.5 MB| + +## References + +https://huggingface.co/w11wo/indo-roberta-small + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-indodistilbertweet_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-indodistilbertweet_pipeline_en.md new file mode 100644 index 00000000000000..c2b7cd973ef582 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-indodistilbertweet_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English indodistilbertweet_pipeline pipeline RoBertaForSequenceClassification from dafqi +author: John Snow Labs +name: indodistilbertweet_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indodistilbertweet_pipeline` is a English model originally trained by dafqi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indodistilbertweet_pipeline_en_5.5.0_3.0_1725277756266.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indodistilbertweet_pipeline_en_5.5.0_3.0_1725277756266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indodistilbertweet_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indodistilbertweet_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indodistilbertweet_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|467.7 MB| + +## References + +https://huggingface.co/dafqi/indoDistilBertweet + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-indonesian_bge_small_en.md b/docs/_posts/ahmedlone127/2024-09-02-indonesian_bge_small_en.md new file mode 100644 index 00000000000000..15997ee66fd5fa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-indonesian_bge_small_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English indonesian_bge_small BGEEmbeddings from ingtech +author: John Snow Labs +name: indonesian_bge_small +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_bge_small` is a English model originally trained by ingtech. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_bge_small_en_5.5.0_3.0_1725262551451.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_bge_small_en_5.5.0_3.0_1725262551451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("indonesian_bge_small","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("indonesian_bge_small","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indonesian_bge_small| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|117.1 MB| + +## References + +https://huggingface.co/ingtech/indonesian-bge-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-indonesian_bge_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-indonesian_bge_small_pipeline_en.md new file mode 100644 index 00000000000000..fbc9c624083521 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-indonesian_bge_small_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English indonesian_bge_small_pipeline pipeline BGEEmbeddings from ingtech +author: John Snow Labs +name: indonesian_bge_small_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_bge_small_pipeline` is a English model originally trained by ingtech. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_bge_small_pipeline_en_5.5.0_3.0_1725262560398.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_bge_small_pipeline_en_5.5.0_3.0_1725262560398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indonesian_bge_small_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indonesian_bge_small_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indonesian_bge_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|117.1 MB| + +## References + +https://huggingface.co/ingtech/indonesian-bge-small + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-indonesian_emotion_distilbert_base_cased_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-indonesian_emotion_distilbert_base_cased_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..d3646810be1910 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-indonesian_emotion_distilbert_base_cased_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English indonesian_emotion_distilbert_base_cased_finetuned_pipeline pipeline DistilBertForSequenceClassification from AptaArkana +author: John Snow Labs +name: indonesian_emotion_distilbert_base_cased_finetuned_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_emotion_distilbert_base_cased_finetuned_pipeline` is a English model originally trained by AptaArkana. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_emotion_distilbert_base_cased_finetuned_pipeline_en_5.5.0_3.0_1725306162353.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_emotion_distilbert_base_cased_finetuned_pipeline_en_5.5.0_3.0_1725306162353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indonesian_emotion_distilbert_base_cased_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indonesian_emotion_distilbert_base_cased_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indonesian_emotion_distilbert_base_cased_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|507.7 MB| + +## References + +https://huggingface.co/AptaArkana/indonesian-emotion-distilbert-base-cased-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-indrajith_camembert_en.md b/docs/_posts/ahmedlone127/2024-09-02-indrajith_camembert_en.md new file mode 100644 index 00000000000000..e556e3e4aef74c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-indrajith_camembert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English indrajith_camembert CamemBertEmbeddings from INDRA9388 +author: John Snow Labs +name: indrajith_camembert +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indrajith_camembert` is a English model originally trained by INDRA9388. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indrajith_camembert_en_5.5.0_3.0_1725300915317.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indrajith_camembert_en_5.5.0_3.0_1725300915317.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("indrajith_camembert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("indrajith_camembert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indrajith_camembert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/INDRA9388/Indrajith_camembert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-indrajith_camembert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-indrajith_camembert_pipeline_en.md new file mode 100644 index 00000000000000..81f3190c0f8335 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-indrajith_camembert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English indrajith_camembert_pipeline pipeline CamemBertEmbeddings from INDRA9388 +author: John Snow Labs +name: indrajith_camembert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indrajith_camembert_pipeline` is a English model originally trained by INDRA9388. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indrajith_camembert_pipeline_en_5.5.0_3.0_1725300991058.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indrajith_camembert_pipeline_en_5.5.0_3.0_1725300991058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indrajith_camembert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indrajith_camembert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indrajith_camembert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/INDRA9388/Indrajith_camembert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-intent_classification_en.md b/docs/_posts/ahmedlone127/2024-09-02-intent_classification_en.md new file mode 100644 index 00000000000000..dd9fa893b4bb47 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-intent_classification_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English intent_classification MPNetEmbeddings from Vishwas +author: John Snow Labs +name: intent_classification +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`intent_classification` is a English model originally trained by Vishwas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/intent_classification_en_5.5.0_3.0_1725280549740.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/intent_classification_en_5.5.0_3.0_1725280549740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("intent_classification","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("intent_classification","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|intent_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/Vishwas/intent_classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-intent_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-intent_classification_pipeline_en.md new file mode 100644 index 00000000000000..3a3bdba23441db --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-intent_classification_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English intent_classification_pipeline pipeline MPNetEmbeddings from Vishwas +author: John Snow Labs +name: intent_classification_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`intent_classification_pipeline` is a English model originally trained by Vishwas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/intent_classification_pipeline_en_5.5.0_3.0_1725280571305.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/intent_classification_pipeline_en_5.5.0_3.0_1725280571305.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("intent_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("intent_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|intent_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/Vishwas/intent_classification + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-intent_xs_en.md b/docs/_posts/ahmedlone127/2024-09-02-intent_xs_en.md new file mode 100644 index 00000000000000..cd315762139402 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-intent_xs_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English intent_xs AlbertForSequenceClassification from dejanseo +author: John Snow Labs +name: intent_xs +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`intent_xs` is a English model originally trained by dejanseo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/intent_xs_en_5.5.0_3.0_1725278924956.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/intent_xs_en_5.5.0_3.0_1725278924956.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("intent_xs","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("intent_xs", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|intent_xs| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/dejanseo/Intent-XS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-intent_xs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-intent_xs_pipeline_en.md new file mode 100644 index 00000000000000..ceb48111d50b87 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-intent_xs_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English intent_xs_pipeline pipeline AlbertForSequenceClassification from dejanseo +author: John Snow Labs +name: intent_xs_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`intent_xs_pipeline` is a English model originally trained by dejanseo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/intent_xs_pipeline_en_5.5.0_3.0_1725278927499.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/intent_xs_pipeline_en_5.5.0_3.0_1725278927499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("intent_xs_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("intent_xs_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|intent_xs_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.3 MB| + +## References + +https://huggingface.co/dejanseo/Intent-XS + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-iwslt17_marian_big_target_ctx4_cwd0_english_french_en.md b/docs/_posts/ahmedlone127/2024-09-02-iwslt17_marian_big_target_ctx4_cwd0_english_french_en.md new file mode 100644 index 00000000000000..67d05b1f119c6f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-iwslt17_marian_big_target_ctx4_cwd0_english_french_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English iwslt17_marian_big_target_ctx4_cwd0_english_french MarianTransformer from context-mt +author: John Snow Labs +name: iwslt17_marian_big_target_ctx4_cwd0_english_french +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iwslt17_marian_big_target_ctx4_cwd0_english_french` is a English model originally trained by context-mt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iwslt17_marian_big_target_ctx4_cwd0_english_french_en_5.5.0_3.0_1725295731200.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iwslt17_marian_big_target_ctx4_cwd0_english_french_en_5.5.0_3.0_1725295731200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("iwslt17_marian_big_target_ctx4_cwd0_english_french","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("iwslt17_marian_big_target_ctx4_cwd0_english_french","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|iwslt17_marian_big_target_ctx4_cwd0_english_french| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/context-mt/iwslt17-marian-big-target-ctx4-cwd0-en-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-iwslt17_marian_small_ctx4_cwd0_english_french_en.md b/docs/_posts/ahmedlone127/2024-09-02-iwslt17_marian_small_ctx4_cwd0_english_french_en.md new file mode 100644 index 00000000000000..baec12ed15a812 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-iwslt17_marian_small_ctx4_cwd0_english_french_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English iwslt17_marian_small_ctx4_cwd0_english_french MarianTransformer from context-mt +author: John Snow Labs +name: iwslt17_marian_small_ctx4_cwd0_english_french +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iwslt17_marian_small_ctx4_cwd0_english_french` is a English model originally trained by context-mt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iwslt17_marian_small_ctx4_cwd0_english_french_en_5.5.0_3.0_1725305137625.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iwslt17_marian_small_ctx4_cwd0_english_french_en_5.5.0_3.0_1725305137625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("iwslt17_marian_small_ctx4_cwd0_english_french","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("iwslt17_marian_small_ctx4_cwd0_english_french","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|iwslt17_marian_small_ctx4_cwd0_english_french| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.3 MB| + +## References + +https://huggingface.co/context-mt/iwslt17-marian-small-ctx4-cwd0-en-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-iwslt17_marian_small_ctx4_cwd0_english_french_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-iwslt17_marian_small_ctx4_cwd0_english_french_pipeline_en.md new file mode 100644 index 00000000000000..3b6d3f9dba2af5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-iwslt17_marian_small_ctx4_cwd0_english_french_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English iwslt17_marian_small_ctx4_cwd0_english_french_pipeline pipeline MarianTransformer from context-mt +author: John Snow Labs +name: iwslt17_marian_small_ctx4_cwd0_english_french_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iwslt17_marian_small_ctx4_cwd0_english_french_pipeline` is a English model originally trained by context-mt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iwslt17_marian_small_ctx4_cwd0_english_french_pipeline_en_5.5.0_3.0_1725305165113.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iwslt17_marian_small_ctx4_cwd0_english_french_pipeline_en_5.5.0_3.0_1725305165113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("iwslt17_marian_small_ctx4_cwd0_english_french_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("iwslt17_marian_small_ctx4_cwd0_english_french_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|iwslt17_marian_small_ctx4_cwd0_english_french_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.8 MB| + +## References + +https://huggingface.co/context-mt/iwslt17-marian-small-ctx4-cwd0-en-fr + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-kie_semantics_en.md b/docs/_posts/ahmedlone127/2024-09-02-kie_semantics_en.md new file mode 100644 index 00000000000000..1fc22fd44c0578 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-kie_semantics_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English kie_semantics DistilBertForSequenceClassification from oulmokhtar +author: John Snow Labs +name: kie_semantics +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kie_semantics` is a English model originally trained by oulmokhtar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kie_semantics_en_5.5.0_3.0_1725291602236.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kie_semantics_en_5.5.0_3.0_1725291602236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("kie_semantics","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("kie_semantics", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kie_semantics| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/oulmokhtar/kie-semantics \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-koobert_xx.md b/docs/_posts/ahmedlone127/2024-09-02-koobert_xx.md new file mode 100644 index 00000000000000..d72d171f3e3fa1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-koobert_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual koobert BertEmbeddings from KooAI +author: John Snow Labs +name: koobert +date: 2024-09-02 +tags: [xx, open_source, onnx, embeddings, bert] +task: Embeddings +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`koobert` is a Multilingual model originally trained by KooAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/koobert_xx_5.5.0_3.0_1725318861137.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/koobert_xx_5.5.0_3.0_1725318861137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = BertEmbeddings.pretrained("koobert","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("koobert","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|koobert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|xx| +|Size:|689.1 MB| + +## References + +https://huggingface.co/KooAI/KooBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lab1_finetuning_stellayin_en.md b/docs/_posts/ahmedlone127/2024-09-02-lab1_finetuning_stellayin_en.md new file mode 100644 index 00000000000000..7b7879f2ff4100 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lab1_finetuning_stellayin_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English lab1_finetuning_stellayin MarianTransformer from Stellayin +author: John Snow Labs +name: lab1_finetuning_stellayin +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_finetuning_stellayin` is a English model originally trained by Stellayin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lab1_finetuning_stellayin_en_5.5.0_3.0_1725242892752.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_finetuning_stellayin_en_5.5.0_3.0_1725242892752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("lab1_finetuning_stellayin","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("lab1_finetuning_stellayin","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lab1_finetuning_stellayin| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.1 MB| + +## References + +https://huggingface.co/Stellayin/lab1_finetuning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lab1_finetuning_stellayin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-lab1_finetuning_stellayin_pipeline_en.md new file mode 100644 index 00000000000000..bdc74fe90c6b23 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lab1_finetuning_stellayin_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lab1_finetuning_stellayin_pipeline pipeline MarianTransformer from Stellayin +author: John Snow Labs +name: lab1_finetuning_stellayin_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_finetuning_stellayin_pipeline` is a English model originally trained by Stellayin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lab1_finetuning_stellayin_pipeline_en_5.5.0_3.0_1725242920184.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_finetuning_stellayin_pipeline_en_5.5.0_3.0_1725242920184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lab1_finetuning_stellayin_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lab1_finetuning_stellayin_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lab1_finetuning_stellayin_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.6 MB| + +## References + +https://huggingface.co/Stellayin/lab1_finetuning + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lab1_finetuning_tchoudh8_en.md b/docs/_posts/ahmedlone127/2024-09-02-lab1_finetuning_tchoudh8_en.md new file mode 100644 index 00000000000000..3458112515a3ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lab1_finetuning_tchoudh8_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English lab1_finetuning_tchoudh8 MarianTransformer from tchoudh8 +author: John Snow Labs +name: lab1_finetuning_tchoudh8 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_finetuning_tchoudh8` is a English model originally trained by tchoudh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lab1_finetuning_tchoudh8_en_5.5.0_3.0_1725304088658.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_finetuning_tchoudh8_en_5.5.0_3.0_1725304088658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("lab1_finetuning_tchoudh8","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("lab1_finetuning_tchoudh8","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lab1_finetuning_tchoudh8| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.3 MB| + +## References + +https://huggingface.co/tchoudh8/lab1_finetuning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lab2_fine_tune_english_russian_en.md b/docs/_posts/ahmedlone127/2024-09-02-lab2_fine_tune_english_russian_en.md new file mode 100644 index 00000000000000..d54c0b664659dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lab2_fine_tune_english_russian_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English lab2_fine_tune_english_russian MarianTransformer from SAFUANlip +author: John Snow Labs +name: lab2_fine_tune_english_russian +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab2_fine_tune_english_russian` is a English model originally trained by SAFUANlip. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lab2_fine_tune_english_russian_en_5.5.0_3.0_1725304302784.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab2_fine_tune_english_russian_en_5.5.0_3.0_1725304302784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("lab2_fine_tune_english_russian","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("lab2_fine_tune_english_russian","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lab2_fine_tune_english_russian| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|525.5 MB| + +## References + +https://huggingface.co/SAFUANlip/lab2_fine_tune_en_ru \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lab2_fine_tune_english_russian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-lab2_fine_tune_english_russian_pipeline_en.md new file mode 100644 index 00000000000000..1aec8c35510fb7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lab2_fine_tune_english_russian_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lab2_fine_tune_english_russian_pipeline pipeline MarianTransformer from SAFUANlip +author: John Snow Labs +name: lab2_fine_tune_english_russian_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab2_fine_tune_english_russian_pipeline` is a English model originally trained by SAFUANlip. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lab2_fine_tune_english_russian_pipeline_en_5.5.0_3.0_1725304330046.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab2_fine_tune_english_russian_pipeline_en_5.5.0_3.0_1725304330046.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lab2_fine_tune_english_russian_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lab2_fine_tune_english_russian_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lab2_fine_tune_english_russian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|526.1 MB| + +## References + +https://huggingface.co/SAFUANlip/lab2_fine_tune_en_ru + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-latin_english_base_en.md b/docs/_posts/ahmedlone127/2024-09-02-latin_english_base_en.md new file mode 100644 index 00000000000000..84d57ecc0ff4c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-latin_english_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English latin_english_base MarianTransformer from grosenthal +author: John Snow Labs +name: latin_english_base +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`latin_english_base` is a English model originally trained by grosenthal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/latin_english_base_en_5.5.0_3.0_1725243063391.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/latin_english_base_en_5.5.0_3.0_1725243063391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("latin_english_base","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("latin_english_base","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|latin_english_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|539.2 MB| + +## References + +https://huggingface.co/grosenthal/la_en_base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-latin_english_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-latin_english_base_pipeline_en.md new file mode 100644 index 00000000000000..bbc590a253125a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-latin_english_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English latin_english_base_pipeline pipeline MarianTransformer from grosenthal +author: John Snow Labs +name: latin_english_base_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`latin_english_base_pipeline` is a English model originally trained by grosenthal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/latin_english_base_pipeline_en_5.5.0_3.0_1725243102965.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/latin_english_base_pipeline_en_5.5.0_3.0_1725243102965.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("latin_english_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("latin_english_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|latin_english_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|539.7 MB| + +## References + +https://huggingface.co/grosenthal/la_en_base + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..f45f32eb6e7414 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English learn_hf_food_not_food_text_classifier_distilbert_base_uncased_pipeline pipeline DistilBertForSequenceClassification from mrdbourke +author: John Snow Labs +name: learn_hf_food_not_food_text_classifier_distilbert_base_uncased_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`learn_hf_food_not_food_text_classifier_distilbert_base_uncased_pipeline` is a English model originally trained by mrdbourke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/learn_hf_food_not_food_text_classifier_distilbert_base_uncased_pipeline_en_5.5.0_3.0_1725292362961.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/learn_hf_food_not_food_text_classifier_distilbert_base_uncased_pipeline_en_5.5.0_3.0_1725292362961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("learn_hf_food_not_food_text_classifier_distilbert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("learn_hf_food_not_food_text_classifier_distilbert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|learn_hf_food_not_food_text_classifier_distilbert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/mrdbourke/learn_hf_food_not_food_text_classifier-distilbert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-legal_camembert_base_fr.md b/docs/_posts/ahmedlone127/2024-09-02-legal_camembert_base_fr.md new file mode 100644 index 00000000000000..ebd09c9a75d700 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-legal_camembert_base_fr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: French legal_camembert_base CamemBertEmbeddings from maastrichtlawtech +author: John Snow Labs +name: legal_camembert_base +date: 2024-09-02 +tags: [fr, open_source, onnx, embeddings, camembert] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_camembert_base` is a French model originally trained by maastrichtlawtech. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_camembert_base_fr_5.5.0_3.0_1725296920563.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_camembert_base_fr_5.5.0_3.0_1725296920563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("legal_camembert_base","fr") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("legal_camembert_base","fr") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_camembert_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|fr| +|Size:|412.8 MB| + +## References + +https://huggingface.co/maastrichtlawtech/legal-camembert-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-legal_camembert_base_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-legal_camembert_base_pipeline_fr.md new file mode 100644 index 00000000000000..7028ad53943fbd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-legal_camembert_base_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French legal_camembert_base_pipeline pipeline CamemBertEmbeddings from maastrichtlawtech +author: John Snow Labs +name: legal_camembert_base_pipeline +date: 2024-09-02 +tags: [fr, open_source, pipeline, onnx] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_camembert_base_pipeline` is a French model originally trained by maastrichtlawtech. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_camembert_base_pipeline_fr_5.5.0_3.0_1725296942103.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_camembert_base_pipeline_fr_5.5.0_3.0_1725296942103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("legal_camembert_base_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("legal_camembert_base_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_camembert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|412.9 MB| + +## References + +https://huggingface.co/maastrichtlawtech/legal-camembert-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-legal_roberta_base_lexlms_en.md b/docs/_posts/ahmedlone127/2024-09-02-legal_roberta_base_lexlms_en.md new file mode 100644 index 00000000000000..9aaf93157d49aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-legal_roberta_base_lexlms_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English legal_roberta_base_lexlms RoBertaEmbeddings from lexlms +author: John Snow Labs +name: legal_roberta_base_lexlms +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_roberta_base_lexlms` is a English model originally trained by lexlms. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_roberta_base_lexlms_en_5.5.0_3.0_1725265039429.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_roberta_base_lexlms_en_5.5.0_3.0_1725265039429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("legal_roberta_base_lexlms","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("legal_roberta_base_lexlms","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_roberta_base_lexlms| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|465.3 MB| + +## References + +https://huggingface.co/lexlms/legal-roberta-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-legal_roberta_base_lexlms_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-legal_roberta_base_lexlms_pipeline_en.md new file mode 100644 index 00000000000000..73707bdf1c2fdf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-legal_roberta_base_lexlms_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English legal_roberta_base_lexlms_pipeline pipeline RoBertaEmbeddings from lexlms +author: John Snow Labs +name: legal_roberta_base_lexlms_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_roberta_base_lexlms_pipeline` is a English model originally trained by lexlms. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_roberta_base_lexlms_pipeline_en_5.5.0_3.0_1725265064303.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_roberta_base_lexlms_pipeline_en_5.5.0_3.0_1725265064303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("legal_roberta_base_lexlms_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("legal_roberta_base_lexlms_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_roberta_base_lexlms_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.3 MB| + +## References + +https://huggingface.co/lexlms/legal-roberta-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-legalbert_en.md b/docs/_posts/ahmedlone127/2024-09-02-legalbert_en.md new file mode 100644 index 00000000000000..cfe3f3e222e705 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-legalbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English legalbert BertEmbeddings from casehold +author: John Snow Labs +name: legalbert +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legalbert` is a English model originally trained by casehold. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legalbert_en_5.5.0_3.0_1725318399545.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legalbert_en_5.5.0_3.0_1725318399545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = BertEmbeddings.pretrained("legalbert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("legalbert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legalbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/casehold/legalbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-legalbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-legalbert_pipeline_en.md new file mode 100644 index 00000000000000..7c76b102d85a64 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-legalbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English legalbert_pipeline pipeline BertEmbeddings from casehold +author: John Snow Labs +name: legalbert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legalbert_pipeline` is a English model originally trained by casehold. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legalbert_pipeline_en_5.5.0_3.0_1725318420157.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legalbert_pipeline_en_5.5.0_3.0_1725318420157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("legalbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("legalbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legalbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/casehold/legalbert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-legistorm_categorizer_seqclass_deberta_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-legistorm_categorizer_seqclass_deberta_v2_en.md new file mode 100644 index 00000000000000..96f99527844399 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-legistorm_categorizer_seqclass_deberta_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English legistorm_categorizer_seqclass_deberta_v2 DeBertaForSequenceClassification from leobg +author: John Snow Labs +name: legistorm_categorizer_seqclass_deberta_v2 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legistorm_categorizer_seqclass_deberta_v2` is a English model originally trained by leobg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legistorm_categorizer_seqclass_deberta_v2_en_5.5.0_3.0_1725283392216.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legistorm_categorizer_seqclass_deberta_v2_en_5.5.0_3.0_1725283392216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("legistorm_categorizer_seqclass_deberta_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("legistorm_categorizer_seqclass_deberta_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legistorm_categorizer_seqclass_deberta_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/leobg/legistorm-categorizer-seqclass-deberta-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-legistorm_categorizer_seqclass_deberta_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-legistorm_categorizer_seqclass_deberta_v2_pipeline_en.md new file mode 100644 index 00000000000000..6db808563d8b46 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-legistorm_categorizer_seqclass_deberta_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English legistorm_categorizer_seqclass_deberta_v2_pipeline pipeline DeBertaForSequenceClassification from leobg +author: John Snow Labs +name: legistorm_categorizer_seqclass_deberta_v2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legistorm_categorizer_seqclass_deberta_v2_pipeline` is a English model originally trained by leobg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legistorm_categorizer_seqclass_deberta_v2_pipeline_en_5.5.0_3.0_1725283514564.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legistorm_categorizer_seqclass_deberta_v2_pipeline_en_5.5.0_3.0_1725283514564.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("legistorm_categorizer_seqclass_deberta_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("legistorm_categorizer_seqclass_deberta_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legistorm_categorizer_seqclass_deberta_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/leobg/legistorm-categorizer-seqclass-deberta-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lenu_finnish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-lenu_finnish_pipeline_en.md new file mode 100644 index 00000000000000..24de02188919db --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lenu_finnish_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lenu_finnish_pipeline pipeline BertForSequenceClassification from Sociovestix +author: John Snow Labs +name: lenu_finnish_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_finnish_pipeline` is a English model originally trained by Sociovestix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lenu_finnish_pipeline_en_5.5.0_3.0_1725293322747.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_finnish_pipeline_en_5.5.0_3.0_1725293322747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lenu_finnish_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lenu_finnish_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lenu_finnish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|467.1 MB| + +## References + +https://huggingface.co/Sociovestix/lenu_FI + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lenu_us_german_en.md b/docs/_posts/ahmedlone127/2024-09-02-lenu_us_german_en.md new file mode 100644 index 00000000000000..4bbb61774f8cae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lenu_us_german_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English lenu_us_german BertForSequenceClassification from Sociovestix +author: John Snow Labs +name: lenu_us_german +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_us_german` is a English model originally trained by Sociovestix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lenu_us_german_en_5.5.0_3.0_1725293834000.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_us_german_en_5.5.0_3.0_1725293834000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("lenu_us_german","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("lenu_us_german", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lenu_us_german| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/Sociovestix/lenu_US-DE \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lenu_us_german_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-lenu_us_german_pipeline_en.md new file mode 100644 index 00000000000000..ab0021b494d37d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lenu_us_german_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lenu_us_german_pipeline pipeline BertForSequenceClassification from Sociovestix +author: John Snow Labs +name: lenu_us_german_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_us_german_pipeline` is a English model originally trained by Sociovestix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lenu_us_german_pipeline_en_5.5.0_3.0_1725293855583.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_us_german_pipeline_en_5.5.0_3.0_1725293855583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lenu_us_german_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lenu_us_german_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lenu_us_german_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/Sociovestix/lenu_US-DE + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-less_100000_xlm_roberta_mmar_recipe_10_base_en.md b/docs/_posts/ahmedlone127/2024-09-02-less_100000_xlm_roberta_mmar_recipe_10_base_en.md new file mode 100644 index 00000000000000..ecb187b4c82f0f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-less_100000_xlm_roberta_mmar_recipe_10_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English less_100000_xlm_roberta_mmar_recipe_10_base XlmRoBertaEmbeddings from CennetOguz +author: John Snow Labs +name: less_100000_xlm_roberta_mmar_recipe_10_base +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`less_100000_xlm_roberta_mmar_recipe_10_base` is a English model originally trained by CennetOguz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/less_100000_xlm_roberta_mmar_recipe_10_base_en_5.5.0_3.0_1725271156356.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/less_100000_xlm_roberta_mmar_recipe_10_base_en_5.5.0_3.0_1725271156356.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("less_100000_xlm_roberta_mmar_recipe_10_base","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("less_100000_xlm_roberta_mmar_recipe_10_base","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|less_100000_xlm_roberta_mmar_recipe_10_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/CennetOguz/less_100000_xlm_roberta_mmar_recipe_10_base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lettuce_sayula_popoluca_french_mono_en.md b/docs/_posts/ahmedlone127/2024-09-02-lettuce_sayula_popoluca_french_mono_en.md new file mode 100644 index 00000000000000..2cccee77c41dae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lettuce_sayula_popoluca_french_mono_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English lettuce_sayula_popoluca_french_mono CamemBertForTokenClassification from pranaydeeps +author: John Snow Labs +name: lettuce_sayula_popoluca_french_mono +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, camembert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lettuce_sayula_popoluca_french_mono` is a English model originally trained by pranaydeeps. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_french_mono_en_5.5.0_3.0_1725266186085.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_french_mono_en_5.5.0_3.0_1725266186085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = CamemBertForTokenClassification.pretrained("lettuce_sayula_popoluca_french_mono","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = CamemBertForTokenClassification.pretrained("lettuce_sayula_popoluca_french_mono", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lettuce_sayula_popoluca_french_mono| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/pranaydeeps/lettuce_pos_fr_mono \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lettuce_sayula_popoluca_french_mono_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-lettuce_sayula_popoluca_french_mono_pipeline_en.md new file mode 100644 index 00000000000000..e8ce227a546b49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lettuce_sayula_popoluca_french_mono_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lettuce_sayula_popoluca_french_mono_pipeline pipeline CamemBertForTokenClassification from pranaydeeps +author: John Snow Labs +name: lettuce_sayula_popoluca_french_mono_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lettuce_sayula_popoluca_french_mono_pipeline` is a English model originally trained by pranaydeeps. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_french_mono_pipeline_en_5.5.0_3.0_1725266208923.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_french_mono_pipeline_en_5.5.0_3.0_1725266208923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lettuce_sayula_popoluca_french_mono_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lettuce_sayula_popoluca_french_mono_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lettuce_sayula_popoluca_french_mono_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/pranaydeeps/lettuce_pos_fr_mono + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lithuanian_un_data_fine_fine_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-lithuanian_un_data_fine_fine_english_en.md new file mode 100644 index 00000000000000..3d6123b053cf97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lithuanian_un_data_fine_fine_english_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English lithuanian_un_data_fine_fine_english MPNetEmbeddings from dell-research-harvard +author: John Snow Labs +name: lithuanian_un_data_fine_fine_english +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lithuanian_un_data_fine_fine_english` is a English model originally trained by dell-research-harvard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lithuanian_un_data_fine_fine_english_en_5.5.0_3.0_1725280854536.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lithuanian_un_data_fine_fine_english_en_5.5.0_3.0_1725280854536.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("lithuanian_un_data_fine_fine_english","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("lithuanian_un_data_fine_fine_english","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lithuanian_un_data_fine_fine_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/dell-research-harvard/lt-un-data-fine-fine-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lithuanian_un_data_fine_fine_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-lithuanian_un_data_fine_fine_english_pipeline_en.md new file mode 100644 index 00000000000000..db950f5a9b786a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lithuanian_un_data_fine_fine_english_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English lithuanian_un_data_fine_fine_english_pipeline pipeline MPNetEmbeddings from dell-research-harvard +author: John Snow Labs +name: lithuanian_un_data_fine_fine_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lithuanian_un_data_fine_fine_english_pipeline` is a English model originally trained by dell-research-harvard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lithuanian_un_data_fine_fine_english_pipeline_en_5.5.0_3.0_1725280877079.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lithuanian_un_data_fine_fine_english_pipeline_en_5.5.0_3.0_1725280877079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lithuanian_un_data_fine_fine_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lithuanian_un_data_fine_fine_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lithuanian_un_data_fine_fine_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/dell-research-harvard/lt-un-data-fine-fine-en + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lithuanian_un_data_fine_industry_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-lithuanian_un_data_fine_industry_english_en.md new file mode 100644 index 00000000000000..cbbdc3fe652b26 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lithuanian_un_data_fine_industry_english_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English lithuanian_un_data_fine_industry_english MPNetEmbeddings from dell-research-harvard +author: John Snow Labs +name: lithuanian_un_data_fine_industry_english +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lithuanian_un_data_fine_industry_english` is a English model originally trained by dell-research-harvard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lithuanian_un_data_fine_industry_english_en_5.5.0_3.0_1725280510247.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lithuanian_un_data_fine_industry_english_en_5.5.0_3.0_1725280510247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("lithuanian_un_data_fine_industry_english","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("lithuanian_un_data_fine_industry_english","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lithuanian_un_data_fine_industry_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/dell-research-harvard/lt-un-data-fine-industry-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lithuanian_un_data_fine_industry_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-lithuanian_un_data_fine_industry_english_pipeline_en.md new file mode 100644 index 00000000000000..7e7e2d3b52d32d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lithuanian_un_data_fine_industry_english_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English lithuanian_un_data_fine_industry_english_pipeline pipeline MPNetEmbeddings from dell-research-harvard +author: John Snow Labs +name: lithuanian_un_data_fine_industry_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lithuanian_un_data_fine_industry_english_pipeline` is a English model originally trained by dell-research-harvard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lithuanian_un_data_fine_industry_english_pipeline_en_5.5.0_3.0_1725280535109.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lithuanian_un_data_fine_industry_english_pipeline_en_5.5.0_3.0_1725280535109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lithuanian_un_data_fine_industry_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lithuanian_un_data_fine_industry_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lithuanian_un_data_fine_industry_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/dell-research-harvard/lt-un-data-fine-industry-en + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-llama_goodlens_mpnet_en.md b/docs/_posts/ahmedlone127/2024-09-02-llama_goodlens_mpnet_en.md new file mode 100644 index 00000000000000..d19acea6ddd605 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-llama_goodlens_mpnet_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English llama_goodlens_mpnet MPNetEmbeddings from beeformer +author: John Snow Labs +name: llama_goodlens_mpnet +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_goodlens_mpnet` is a English model originally trained by beeformer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_goodlens_mpnet_en_5.5.0_3.0_1725258791038.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_goodlens_mpnet_en_5.5.0_3.0_1725258791038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("llama_goodlens_mpnet","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("llama_goodlens_mpnet","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_goodlens_mpnet| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/beeformer/Llama-goodlens-mpnet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-llama_goodlens_mpnet_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-llama_goodlens_mpnet_pipeline_en.md new file mode 100644 index 00000000000000..9401d7b16a8ab5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-llama_goodlens_mpnet_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English llama_goodlens_mpnet_pipeline pipeline MPNetEmbeddings from beeformer +author: John Snow Labs +name: llama_goodlens_mpnet_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_goodlens_mpnet_pipeline` is a English model originally trained by beeformer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_goodlens_mpnet_pipeline_en_5.5.0_3.0_1725258812549.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_goodlens_mpnet_pipeline_en_5.5.0_3.0_1725258812549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("llama_goodlens_mpnet_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("llama_goodlens_mpnet_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_goodlens_mpnet_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/beeformer/Llama-goodlens-mpnet + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-longclip_l_diffusers_en.md b/docs/_posts/ahmedlone127/2024-09-02-longclip_l_diffusers_en.md new file mode 100644 index 00000000000000..0b6dcac15db63d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-longclip_l_diffusers_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English longclip_l_diffusers CLIPForZeroShotClassification from Azazelle +author: John Snow Labs +name: longclip_l_diffusers +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`longclip_l_diffusers` is a English model originally trained by Azazelle. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/longclip_l_diffusers_en_5.5.0_3.0_1725257271476.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/longclip_l_diffusers_en_5.5.0_3.0_1725257271476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("longclip_l_diffusers","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("longclip_l_diffusers","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|longclip_l_diffusers| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/Azazelle/LongClip-L-diffusers \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-longclip_l_diffusers_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-longclip_l_diffusers_pipeline_en.md new file mode 100644 index 00000000000000..63ff8be0f7c658 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-longclip_l_diffusers_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English longclip_l_diffusers_pipeline pipeline CLIPForZeroShotClassification from Azazelle +author: John Snow Labs +name: longclip_l_diffusers_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`longclip_l_diffusers_pipeline` is a English model originally trained by Azazelle. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/longclip_l_diffusers_pipeline_en_5.5.0_3.0_1725257353000.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/longclip_l_diffusers_pipeline_en_5.5.0_3.0_1725257353000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("longclip_l_diffusers_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("longclip_l_diffusers_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|longclip_l_diffusers_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/Azazelle/LongClip-L-diffusers + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lostintranslation_en.md b/docs/_posts/ahmedlone127/2024-09-02-lostintranslation_en.md new file mode 100644 index 00000000000000..53356c10efe654 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lostintranslation_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English lostintranslation MarianTransformer from guymorlan +author: John Snow Labs +name: lostintranslation +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lostintranslation` is a English model originally trained by guymorlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lostintranslation_en_5.5.0_3.0_1725243464778.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lostintranslation_en_5.5.0_3.0_1725243464778.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("lostintranslation","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("lostintranslation","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lostintranslation| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|544.3 MB| + +## References + +https://huggingface.co/guymorlan/LostInTranslation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lostintranslation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-lostintranslation_pipeline_en.md new file mode 100644 index 00000000000000..6c417edbb40260 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lostintranslation_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lostintranslation_pipeline pipeline MarianTransformer from guymorlan +author: John Snow Labs +name: lostintranslation_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lostintranslation_pipeline` is a English model originally trained by guymorlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lostintranslation_pipeline_en_5.5.0_3.0_1725243493847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lostintranslation_pipeline_en_5.5.0_3.0_1725243493847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lostintranslation_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lostintranslation_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lostintranslation_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|544.8 MB| + +## References + +https://huggingface.co/guymorlan/LostInTranslation + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-lugatitdistilbert_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-02-lugatitdistilbert_pipeline_tr.md new file mode 100644 index 00000000000000..b1775d7dd46baf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-lugatitdistilbert_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish lugatitdistilbert_pipeline pipeline DistilBertForSequenceClassification from LugatitTurk +author: John Snow Labs +name: lugatitdistilbert_pipeline +date: 2024-09-02 +tags: [tr, open_source, pipeline, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lugatitdistilbert_pipeline` is a Turkish model originally trained by LugatitTurk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lugatitdistilbert_pipeline_tr_5.5.0_3.0_1725292029362.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lugatitdistilbert_pipeline_tr_5.5.0_3.0_1725292029362.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lugatitdistilbert_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lugatitdistilbert_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lugatitdistilbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|254.1 MB| + +## References + +https://huggingface.co/LugatitTurk/LugatitDistilBert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-m0_flat_ner_ref_ptrn_cmbert_io_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-m0_flat_ner_ref_ptrn_cmbert_io_pipeline_fr.md new file mode 100644 index 00000000000000..7bc07797fe10e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-m0_flat_ner_ref_ptrn_cmbert_io_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French m0_flat_ner_ref_ptrn_cmbert_io_pipeline pipeline CamemBertForTokenClassification from nlpso +author: John Snow Labs +name: m0_flat_ner_ref_ptrn_cmbert_io_pipeline +date: 2024-09-02 +tags: [fr, open_source, pipeline, onnx] +task: Named Entity Recognition +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m0_flat_ner_ref_ptrn_cmbert_io_pipeline` is a French model originally trained by nlpso. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m0_flat_ner_ref_ptrn_cmbert_io_pipeline_fr_5.5.0_3.0_1725266012634.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m0_flat_ner_ref_ptrn_cmbert_io_pipeline_fr_5.5.0_3.0_1725266012634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("m0_flat_ner_ref_ptrn_cmbert_io_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("m0_flat_ner_ref_ptrn_cmbert_io_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|m0_flat_ner_ref_ptrn_cmbert_io_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|412.9 MB| + +## References + +https://huggingface.co/nlpso/m0_flat_ner_ref_ptrn_cmbert_io + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-maltese_coref_english_french_gender_exp_en.md b/docs/_posts/ahmedlone127/2024-09-02-maltese_coref_english_french_gender_exp_en.md new file mode 100644 index 00000000000000..6ac96a7f279905 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-maltese_coref_english_french_gender_exp_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English maltese_coref_english_french_gender_exp MarianTransformer from nlphuji +author: John Snow Labs +name: maltese_coref_english_french_gender_exp +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_french_gender_exp` is a English model originally trained by nlphuji. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_french_gender_exp_en_5.5.0_3.0_1725294649479.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_french_gender_exp_en_5.5.0_3.0_1725294649479.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("maltese_coref_english_french_gender_exp","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("maltese_coref_english_french_gender_exp","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|maltese_coref_english_french_gender_exp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.7 MB| + +## References + +https://huggingface.co/nlphuji/mt_coref_en_fr_gender_exp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-maltese_coref_english_french_gender_exp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-maltese_coref_english_french_gender_exp_pipeline_en.md new file mode 100644 index 00000000000000..fe56556618424d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-maltese_coref_english_french_gender_exp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English maltese_coref_english_french_gender_exp_pipeline pipeline MarianTransformer from nlphuji +author: John Snow Labs +name: maltese_coref_english_french_gender_exp_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_french_gender_exp_pipeline` is a English model originally trained by nlphuji. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_french_gender_exp_pipeline_en_5.5.0_3.0_1725294681905.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_french_gender_exp_pipeline_en_5.5.0_3.0_1725294681905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("maltese_coref_english_french_gender_exp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("maltese_coref_english_french_gender_exp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|maltese_coref_english_french_gender_exp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|509.2 MB| + +## References + +https://huggingface.co/nlphuji/mt_coref_en_fr_gender_exp + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marathisampark_en.md b/docs/_posts/ahmedlone127/2024-09-02-marathisampark_en.md new file mode 100644 index 00000000000000..eaabfb2d1801ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marathisampark_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marathisampark MarianTransformer from SRDdev +author: John Snow Labs +name: marathisampark +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marathisampark` is a English model originally trained by SRDdev. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marathisampark_en_5.5.0_3.0_1725242783806.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marathisampark_en_5.5.0_3.0_1725242783806.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marathisampark","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marathisampark","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marathisampark| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|519.1 MB| + +## References + +https://huggingface.co/SRDdev/MarathiSampark \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marathisampark_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marathisampark_pipeline_en.md new file mode 100644 index 00000000000000..63137de15e9e9c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marathisampark_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marathisampark_pipeline pipeline MarianTransformer from SRDdev +author: John Snow Labs +name: marathisampark_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marathisampark_pipeline` is a English model originally trained by SRDdev. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marathisampark_pipeline_en_5.5.0_3.0_1725242812045.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marathisampark_pipeline_en_5.5.0_3.0_1725242812045.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marathisampark_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marathisampark_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marathisampark_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|519.6 MB| + +## References + +https://huggingface.co/SRDdev/MarathiSampark + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marcel_customer_service_medium_masked_en.md b/docs/_posts/ahmedlone127/2024-09-02-marcel_customer_service_medium_masked_en.md new file mode 100644 index 00000000000000..132153c04ba6dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marcel_customer_service_medium_masked_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marcel_customer_service_medium_masked CamemBertEmbeddings from maelfabien +author: John Snow Labs +name: marcel_customer_service_medium_masked +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marcel_customer_service_medium_masked` is a English model originally trained by maelfabien. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marcel_customer_service_medium_masked_en_5.5.0_3.0_1725297135041.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marcel_customer_service_medium_masked_en_5.5.0_3.0_1725297135041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("marcel_customer_service_medium_masked","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("marcel_customer_service_medium_masked","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marcel_customer_service_medium_masked| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|412.5 MB| + +## References + +https://huggingface.co/maelfabien/marcel_customer_service_medium_masked \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marcel_customer_service_medium_masked_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marcel_customer_service_medium_masked_pipeline_en.md new file mode 100644 index 00000000000000..78226d963bcc31 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marcel_customer_service_medium_masked_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marcel_customer_service_medium_masked_pipeline pipeline CamemBertEmbeddings from maelfabien +author: John Snow Labs +name: marcel_customer_service_medium_masked_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marcel_customer_service_medium_masked_pipeline` is a English model originally trained by maelfabien. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marcel_customer_service_medium_masked_pipeline_en_5.5.0_3.0_1725297156157.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marcel_customer_service_medium_masked_pipeline_en_5.5.0_3.0_1725297156157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marcel_customer_service_medium_masked_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marcel_customer_service_medium_masked_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marcel_customer_service_medium_masked_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.6 MB| + +## References + +https://huggingface.co/maelfabien/marcel_customer_service_medium_masked + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marcel_customer_service_xlarge_masked_en.md b/docs/_posts/ahmedlone127/2024-09-02-marcel_customer_service_xlarge_masked_en.md new file mode 100644 index 00000000000000..e3b3bfdd8f2bd6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marcel_customer_service_xlarge_masked_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marcel_customer_service_xlarge_masked CamemBertEmbeddings from maelfabien +author: John Snow Labs +name: marcel_customer_service_xlarge_masked +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marcel_customer_service_xlarge_masked` is a English model originally trained by maelfabien. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marcel_customer_service_xlarge_masked_en_5.5.0_3.0_1725300502994.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marcel_customer_service_xlarge_masked_en_5.5.0_3.0_1725300502994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("marcel_customer_service_xlarge_masked","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("marcel_customer_service_xlarge_masked","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marcel_customer_service_xlarge_masked| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|412.6 MB| + +## References + +https://huggingface.co/maelfabien/marcel_customer_service_xlarge_masked \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marcel_customer_service_xlarge_masked_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marcel_customer_service_xlarge_masked_pipeline_en.md new file mode 100644 index 00000000000000..8fd1b7a9923195 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marcel_customer_service_xlarge_masked_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marcel_customer_service_xlarge_masked_pipeline pipeline CamemBertEmbeddings from maelfabien +author: John Snow Labs +name: marcel_customer_service_xlarge_masked_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marcel_customer_service_xlarge_masked_pipeline` is a English model originally trained by maelfabien. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marcel_customer_service_xlarge_masked_pipeline_en_5.5.0_3.0_1725300524362.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marcel_customer_service_xlarge_masked_pipeline_en_5.5.0_3.0_1725300524362.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marcel_customer_service_xlarge_masked_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marcel_customer_service_xlarge_masked_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marcel_customer_service_xlarge_masked_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.6 MB| + +## References + +https://huggingface.co/maelfabien/marcel_customer_service_xlarge_masked + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_en.md new file mode 100644 index 00000000000000..2393cbc5290d87 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate MarianTransformer from zhenchuan +author: John Snow Labs +name: marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate` is a English model originally trained by zhenchuan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_en_5.5.0_3.0_1725294444476.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_en_5.5.0_3.0_1725294444476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|540.6 MB| + +## References + +https://huggingface.co/zhenchuan/marian-finetuned-kde4-en-to-cn-accelerate \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_pipeline_en.md new file mode 100644 index 00000000000000..6d2da761872d5a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_pipeline pipeline MarianTransformer from zhenchuan +author: John Snow Labs +name: marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_pipeline` is a English model originally trained by zhenchuan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_pipeline_en_5.5.0_3.0_1725294483779.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_pipeline_en_5.5.0_3.0_1725294483779.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_cn_accelerate_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|541.2 MB| + +## References + +https://huggingface.co/zhenchuan/marian-finetuned-kde4-en-to-cn-accelerate + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_en.md new file mode 100644 index 00000000000000..85cf2bca9cd38f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88 MarianTransformer from qianyu88 +author: John Snow Labs +name: marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88` is a English model originally trained by qianyu88. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_en_5.5.0_3.0_1725243365831.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_en_5.5.0_3.0_1725243365831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.2 MB| + +## References + +https://huggingface.co/qianyu88/marian-finetuned-kde4-en-to-fr-accelerate \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_pipeline_en.md new file mode 100644 index 00000000000000..bb5d9321ecd138 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_pipeline pipeline MarianTransformer from qianyu88 +author: John Snow Labs +name: marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_pipeline` is a English model originally trained by qianyu88. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_pipeline_en_5.5.0_3.0_1725243391977.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_pipeline_en_5.5.0_3.0_1725243391977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_qianyu88_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.7 MB| + +## References + +https://huggingface.co/qianyu88/marian-finetuned-kde4-en-to-fr-accelerate + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_en.md new file mode 100644 index 00000000000000..785af597dd8921 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis MarianTransformer from akousis +author: John Snow Labs +name: marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis` is a English model originally trained by akousis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_en_5.5.0_3.0_1725304399946.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_en_5.5.0_3.0_1725304399946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.2 MB| + +## References + +https://huggingface.co/akousis/marian-finetuned-kde4-en-to-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_pipeline_en.md new file mode 100644 index 00000000000000..230385ebf60b11 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_pipeline pipeline MarianTransformer from akousis +author: John Snow Labs +name: marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_pipeline` is a English model originally trained by akousis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_pipeline_en_5.5.0_3.0_1725304431671.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_pipeline_en_5.5.0_3.0_1725304431671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_akousis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.7 MB| + +## References + +https://huggingface.co/akousis/marian-finetuned-kde4-en-to-fr + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_en.md new file mode 100644 index 00000000000000..f9e827f42cd9b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix MarianTransformer from sul-lix +author: John Snow Labs +name: marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix` is a English model originally trained by sul-lix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_en_5.5.0_3.0_1725304314266.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_en_5.5.0_3.0_1725304314266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.1 MB| + +## References + +https://huggingface.co/sul-lix/marian-finetuned-kde4-en-to-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_pipeline_en.md new file mode 100644 index 00000000000000..fa164f6e707135 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_pipeline pipeline MarianTransformer from sul-lix +author: John Snow Labs +name: marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_pipeline` is a English model originally trained by sul-lix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_pipeline_en_5.5.0_3.0_1725304340623.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_pipeline_en_5.5.0_3.0_1725304340623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_sul_lix_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.6 MB| + +## References + +https://huggingface.co/sul-lix/marian-finetuned-kde4-en-to-fr + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_pipeline_en.md new file mode 100644 index 00000000000000..584a860a6ee33d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_pipeline pipeline MarianTransformer from zihoh +author: John Snow Labs +name: marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_pipeline` is a English model originally trained by zihoh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_pipeline_en_5.5.0_3.0_1725304087473.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_pipeline_en_5.5.0_3.0_1725304087473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.8 MB| + +## References + +https://huggingface.co/zihoh/marian-finetuned-kde4-en-to-fr + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_german_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_german_en.md new file mode 100644 index 00000000000000..e617751f7a651e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_german_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marian_finetuned_kde4_english_tonga_tonga_islands_german MarianTransformer from kktommy +author: John Snow Labs +name: marian_finetuned_kde4_english_tonga_tonga_islands_german +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_german` is a English model originally trained by kktommy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_german_en_5.5.0_3.0_1725294831100.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_german_en_5.5.0_3.0_1725294831100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_german","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_german","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_german| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|499.5 MB| + +## References + +https://huggingface.co/kktommy/marian-finetuned-kde4-en-to-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_german_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_german_pipeline_en.md new file mode 100644 index 00000000000000..80af5ceefdda79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_german_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marian_finetuned_kde4_english_tonga_tonga_islands_german_pipeline pipeline MarianTransformer from kktommy +author: John Snow Labs +name: marian_finetuned_kde4_english_tonga_tonga_islands_german_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_german_pipeline` is a English model originally trained by kktommy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_german_pipeline_en_5.5.0_3.0_1725294857911.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_german_pipeline_en_5.5.0_3.0_1725294857911.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_german_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_german_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_german_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|500.0 MB| + +## References + +https://huggingface.co/kktommy/marian-finetuned-kde4-en-to-de + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_pipeline_en.md new file mode 100644 index 00000000000000..5bcf78232ecada --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_pipeline pipeline MarianTransformer from sephinroth +author: John Snow Labs +name: marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_pipeline` is a English model originally trained by sephinroth. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_pipeline_en_5.5.0_3.0_1725305143457.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_pipeline_en_5.5.0_3.0_1725305143457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|515.8 MB| + +## References + +https://huggingface.co/sephinroth/marian-finetuned-kftt-ja-to-en-wandb + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_maltese_bbc_english_nigerian_pidgin_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_maltese_bbc_english_nigerian_pidgin_en.md new file mode 100644 index 00000000000000..cd9bed53815790 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_maltese_bbc_english_nigerian_pidgin_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marian_maltese_bbc_english_nigerian_pidgin MarianTransformer from NITHUB-AI +author: John Snow Labs +name: marian_maltese_bbc_english_nigerian_pidgin +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_maltese_bbc_english_nigerian_pidgin` is a English model originally trained by NITHUB-AI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_maltese_bbc_english_nigerian_pidgin_en_5.5.0_3.0_1725243648861.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_maltese_bbc_english_nigerian_pidgin_en_5.5.0_3.0_1725243648861.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marian_maltese_bbc_english_nigerian_pidgin","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marian_maltese_bbc_english_nigerian_pidgin","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_maltese_bbc_english_nigerian_pidgin| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|499.1 MB| + +## References + +https://huggingface.co/NITHUB-AI/marian-mt-bbc-en-pcm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_maltese_bbc_english_nigerian_pidgin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_maltese_bbc_english_nigerian_pidgin_pipeline_en.md new file mode 100644 index 00000000000000..b6c5333fb160bf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_maltese_bbc_english_nigerian_pidgin_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marian_maltese_bbc_english_nigerian_pidgin_pipeline pipeline MarianTransformer from NITHUB-AI +author: John Snow Labs +name: marian_maltese_bbc_english_nigerian_pidgin_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_maltese_bbc_english_nigerian_pidgin_pipeline` is a English model originally trained by NITHUB-AI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_maltese_bbc_english_nigerian_pidgin_pipeline_en_5.5.0_3.0_1725243676608.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_maltese_bbc_english_nigerian_pidgin_pipeline_en_5.5.0_3.0_1725243676608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marian_maltese_bbc_english_nigerian_pidgin_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marian_maltese_bbc_english_nigerian_pidgin_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_maltese_bbc_english_nigerian_pidgin_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|499.6 MB| + +## References + +https://huggingface.co/NITHUB-AI/marian-mt-bbc-en-pcm + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_maltese_english_nigerian_pidgin_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_maltese_english_nigerian_pidgin_en.md new file mode 100644 index 00000000000000..e416f83d676129 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_maltese_english_nigerian_pidgin_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marian_maltese_english_nigerian_pidgin MarianTransformer from Enutrof +author: John Snow Labs +name: marian_maltese_english_nigerian_pidgin +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_maltese_english_nigerian_pidgin` is a English model originally trained by Enutrof. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_maltese_english_nigerian_pidgin_en_5.5.0_3.0_1725243579153.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_maltese_english_nigerian_pidgin_en_5.5.0_3.0_1725243579153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marian_maltese_english_nigerian_pidgin","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marian_maltese_english_nigerian_pidgin","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_maltese_english_nigerian_pidgin| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|499.1 MB| + +## References + +https://huggingface.co/Enutrof/marian-mt-en-pcm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_maltese_english_nigerian_pidgin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_maltese_english_nigerian_pidgin_pipeline_en.md new file mode 100644 index 00000000000000..fe8a09cd078b20 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_maltese_english_nigerian_pidgin_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marian_maltese_english_nigerian_pidgin_pipeline pipeline MarianTransformer from Enutrof +author: John Snow Labs +name: marian_maltese_english_nigerian_pidgin_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_maltese_english_nigerian_pidgin_pipeline` is a English model originally trained by Enutrof. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_maltese_english_nigerian_pidgin_pipeline_en_5.5.0_3.0_1725243606277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_maltese_english_nigerian_pidgin_pipeline_en_5.5.0_3.0_1725243606277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marian_maltese_english_nigerian_pidgin_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marian_maltese_english_nigerian_pidgin_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_maltese_english_nigerian_pidgin_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|499.7 MB| + +## References + +https://huggingface.co/Enutrof/marian-mt-en-pcm + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_rinconada_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_rinconada_tonga_tonga_islands_english_en.md new file mode 100644 index 00000000000000..19d83bcad496ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_rinconada_tonga_tonga_islands_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marian_rinconada_tonga_tonga_islands_english MarianTransformer from tiffp +author: John Snow Labs +name: marian_rinconada_tonga_tonga_islands_english +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_rinconada_tonga_tonga_islands_english` is a English model originally trained by tiffp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_rinconada_tonga_tonga_islands_english_en_5.5.0_3.0_1725295970083.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_rinconada_tonga_tonga_islands_english_en_5.5.0_3.0_1725295970083.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marian_rinconada_tonga_tonga_islands_english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marian_rinconada_tonga_tonga_islands_english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_rinconada_tonga_tonga_islands_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|496.4 MB| + +## References + +https://huggingface.co/tiffp/marian-rinconada-to-english \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_rinconada_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_rinconada_tonga_tonga_islands_english_pipeline_en.md new file mode 100644 index 00000000000000..aaece012c2fd21 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marian_rinconada_tonga_tonga_islands_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marian_rinconada_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from tiffp +author: John Snow Labs +name: marian_rinconada_tonga_tonga_islands_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_rinconada_tonga_tonga_islands_english_pipeline` is a English model originally trained by tiffp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_rinconada_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725295994751.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_rinconada_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725295994751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marian_rinconada_tonga_tonga_islands_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marian_rinconada_tonga_tonga_islands_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_rinconada_tonga_tonga_islands_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|496.9 MB| + +## References + +https://huggingface.co/tiffp/marian-rinconada-to-english + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marianmt_en.md b/docs/_posts/ahmedlone127/2024-09-02-marianmt_en.md new file mode 100644 index 00000000000000..cb1192759e9814 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marianmt_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marianmt MarianTransformer from alina1997 +author: John Snow Labs +name: marianmt +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt` is a English model originally trained by alina1997. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_en_5.5.0_3.0_1725294793416.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_en_5.5.0_3.0_1725294793416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marianmt","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marianmt","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marianmt| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|499.4 MB| + +## References + +https://huggingface.co/alina1997/MarianMT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marianmt_hin_eng_czech_hi.md b/docs/_posts/ahmedlone127/2024-09-02-marianmt_hin_eng_czech_hi.md new file mode 100644 index 00000000000000..947c07fa1bd3e8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marianmt_hin_eng_czech_hi.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Hindi marianmt_hin_eng_czech MarianTransformer from ar5entum +author: John Snow Labs +name: marianmt_hin_eng_czech +date: 2024-09-02 +tags: [hi, open_source, onnx, translation, marian] +task: Translation +language: hi +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt_hin_eng_czech` is a Hindi model originally trained by ar5entum. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_hin_eng_czech_hi_5.5.0_3.0_1725295178931.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_hin_eng_czech_hi_5.5.0_3.0_1725295178931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marianmt_hin_eng_czech","hi") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marianmt_hin_eng_czech","hi") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marianmt_hin_eng_czech| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|hi| +|Size:|532.6 MB| + +## References + +https://huggingface.co/ar5entum/marianMT_hin_eng_cs \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marianmt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marianmt_pipeline_en.md new file mode 100644 index 00000000000000..b8263f60dae9d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marianmt_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marianmt_pipeline pipeline MarianTransformer from alina1997 +author: John Snow Labs +name: marianmt_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt_pipeline` is a English model originally trained by alina1997. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_pipeline_en_5.5.0_3.0_1725294819767.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_pipeline_en_5.5.0_3.0_1725294819767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marianmt_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marianmt_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marianmt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|500.0 MB| + +## References + +https://huggingface.co/alina1997/MarianMT + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marianmt_tatoeba_ruen_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marianmt_tatoeba_ruen_pipeline_en.md new file mode 100644 index 00000000000000..2503bbd836ce24 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marianmt_tatoeba_ruen_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marianmt_tatoeba_ruen_pipeline pipeline MarianTransformer from DeepPavlov +author: John Snow Labs +name: marianmt_tatoeba_ruen_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt_tatoeba_ruen_pipeline` is a English model originally trained by DeepPavlov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_tatoeba_ruen_pipeline_en_5.5.0_3.0_1725295283178.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_tatoeba_ruen_pipeline_en_5.5.0_3.0_1725295283178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marianmt_tatoeba_ruen_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marianmt_tatoeba_ruen_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marianmt_tatoeba_ruen_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|528.2 MB| + +## References + +https://huggingface.co/DeepPavlov/marianmt-tatoeba-ruen + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marianmt_ufal_english_romanian_en.md b/docs/_posts/ahmedlone127/2024-09-02-marianmt_ufal_english_romanian_en.md new file mode 100644 index 00000000000000..158e7a2ed77b5e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marianmt_ufal_english_romanian_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marianmt_ufal_english_romanian MarianTransformer from irenelizihui +author: John Snow Labs +name: marianmt_ufal_english_romanian +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt_ufal_english_romanian` is a English model originally trained by irenelizihui. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_ufal_english_romanian_en_5.5.0_3.0_1725242789636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_ufal_english_romanian_en_5.5.0_3.0_1725242789636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marianmt_ufal_english_romanian","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marianmt_ufal_english_romanian","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marianmt_ufal_english_romanian| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|507.8 MB| + +## References + +https://huggingface.co/irenelizihui/MarianMT_UFAL_en_ro \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marianmt_ufal_english_romanian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marianmt_ufal_english_romanian_pipeline_en.md new file mode 100644 index 00000000000000..cb82216e01104a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marianmt_ufal_english_romanian_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marianmt_ufal_english_romanian_pipeline pipeline MarianTransformer from irenelizihui +author: John Snow Labs +name: marianmt_ufal_english_romanian_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt_ufal_english_romanian_pipeline` is a English model originally trained by irenelizihui. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_ufal_english_romanian_pipeline_en_5.5.0_3.0_1725242819250.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_ufal_english_romanian_pipeline_en_5.5.0_3.0_1725242819250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marianmt_ufal_english_romanian_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marianmt_ufal_english_romanian_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marianmt_ufal_english_romanian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.3 MB| + +## References + +https://huggingface.co/irenelizihui/MarianMT_UFAL_en_ro + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marianmtfinetuningarabic2english_en.md b/docs/_posts/ahmedlone127/2024-09-02-marianmtfinetuningarabic2english_en.md new file mode 100644 index 00000000000000..bf23dd295e08c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marianmtfinetuningarabic2english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marianmtfinetuningarabic2english MarianTransformer from Ahmedhisham +author: John Snow Labs +name: marianmtfinetuningarabic2english +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmtfinetuningarabic2english` is a English model originally trained by Ahmedhisham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmtfinetuningarabic2english_en_5.5.0_3.0_1725304988913.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmtfinetuningarabic2english_en_5.5.0_3.0_1725304988913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marianmtfinetuningarabic2english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marianmtfinetuningarabic2english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marianmtfinetuningarabic2english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|527.8 MB| + +## References + +https://huggingface.co/Ahmedhisham/MarianMTfinetuningArabic2English \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-marianmtfinetuningarabic2english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marianmtfinetuningarabic2english_pipeline_en.md new file mode 100644 index 00000000000000..c57d9bfeeb95fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-marianmtfinetuningarabic2english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marianmtfinetuningarabic2english_pipeline pipeline MarianTransformer from Ahmedhisham +author: John Snow Labs +name: marianmtfinetuningarabic2english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmtfinetuningarabic2english_pipeline` is a English model originally trained by Ahmedhisham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmtfinetuningarabic2english_pipeline_en_5.5.0_3.0_1725305016244.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmtfinetuningarabic2english_pipeline_en_5.5.0_3.0_1725305016244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marianmtfinetuningarabic2english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marianmtfinetuningarabic2english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marianmtfinetuningarabic2english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|528.4 MB| + +## References + +https://huggingface.co/Ahmedhisham/MarianMTfinetuningArabic2English + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mcd_speech_en.md b/docs/_posts/ahmedlone127/2024-09-02-mcd_speech_en.md new file mode 100644 index 00000000000000..91d43d14666043 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mcd_speech_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English mcd_speech WhisperForCTC from Vishwaksen +author: John Snow Labs +name: mcd_speech +date: 2024-09-02 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mcd_speech` is a English model originally trained by Vishwaksen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mcd_speech_en_5.5.0_3.0_1725245080111.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mcd_speech_en_5.5.0_3.0_1725245080111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("mcd_speech","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("mcd_speech", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mcd_speech| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Vishwaksen/MCD_Speech \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mcd_speech_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mcd_speech_pipeline_en.md new file mode 100644 index 00000000000000..4bfa1763cccdc3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mcd_speech_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mcd_speech_pipeline pipeline WhisperForCTC from Vishwaksen +author: John Snow Labs +name: mcd_speech_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mcd_speech_pipeline` is a English model originally trained by Vishwaksen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mcd_speech_pipeline_en_5.5.0_3.0_1725245167991.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mcd_speech_pipeline_en_5.5.0_3.0_1725245167991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mcd_speech_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mcd_speech_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mcd_speech_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Vishwaksen/MCD_Speech + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_en.md new file mode 100644 index 00000000000000..06c96bd83d2cdd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0 DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_en_5.5.0_3.0_1725268564180.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_en_5.5.0_3.0_1725268564180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|811.6 MB| + +## References + +https://huggingface.co/pgajo/mdeberta_EW-TT-PE_U0_S1_Tingredient_DROP1_mdeberta_E4_DEV96.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_pipeline_en.md new file mode 100644 index 00000000000000..0b66b8d58c6316 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_pipeline pipeline DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_pipeline` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_pipeline_en_5.5.0_3.0_1725268679036.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_pipeline_en_5.5.0_3.0_1725268679036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_ew_tatar_pe_u0_s1_tingredient_drop1_mdeberta_e4_dev96_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|811.6 MB| + +## References + +https://huggingface.co/pgajo/mdeberta_EW-TT-PE_U0_S1_Tingredient_DROP1_mdeberta_E4_DEV96.0 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_en.md new file mode 100644 index 00000000000000..03687b8c2be019 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0 DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_en_5.5.0_3.0_1725269388851.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_en_5.5.0_3.0_1725269388851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|811.0 MB| + +## References + +https://huggingface.co/pgajo/mdeberta_EW-TT-PE_U0_S1_Tingredient_P0.25_DROP1_mdeberta_E9_DEV97.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_pipeline_en.md new file mode 100644 index 00000000000000..661ef36e9eeff5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_pipeline pipeline DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_pipeline` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_pipeline_en_5.5.0_3.0_1725269520796.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_pipeline_en_5.5.0_3.0_1725269520796.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_25_drop1_mdeberta_e9_dev97_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|811.0 MB| + +## References + +https://huggingface.co/pgajo/mdeberta_EW-TT-PE_U0_S1_Tingredient_P0.25_DROP1_mdeberta_E9_DEV97.0 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_en.md new file mode 100644 index 00000000000000..8e5c9e1359ca5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0 DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_en_5.5.0_3.0_1725269760457.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_en_5.5.0_3.0_1725269760457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|811.5 MB| + +## References + +https://huggingface.co/pgajo/mdeberta_EW-TT-PE_U0_S1_Tingredient_P0.5_DROP1_mdeberta_E4_DEV97.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_pipeline_en.md new file mode 100644 index 00000000000000..ff1d08f11492c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_pipeline pipeline DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_pipeline` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_pipeline_en_5.5.0_3.0_1725269874580.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_pipeline_en_5.5.0_3.0_1725269874580.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e4_dev97_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|811.5 MB| + +## References + +https://huggingface.co/pgajo/mdeberta_EW-TT-PE_U0_S1_Tingredient_P0.5_DROP1_mdeberta_E4_DEV97.0 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_pipeline_xx.md new file mode 100644 index 00000000000000..c2e1552f9e1b76 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual mdeberta_v3_base_pipeline pipeline DeBertaEmbeddings from microsoft +author: John Snow Labs +name: mdeberta_v3_base_pipeline +date: 2024-09-02 +tags: [xx, open_source, pipeline, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_pipeline` is a Multilingual model originally trained by microsoft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_pipeline_xx_5.5.0_3.0_1725261599166.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_pipeline_xx_5.5.0_3.0_1725261599166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|660.8 MB| + +## References + +https://huggingface.co/microsoft/mdeberta-v3-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_en.md new file mode 100644 index 00000000000000..406d266595602a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp DeBertaForQuestionAnswering from eanderson +author: John Snow Labs +name: mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp` is a English model originally trained by eanderson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_en_5.5.0_3.0_1725268879818.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_en_5.5.0_3.0_1725268879818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|874.2 MB| + +## References + +https://huggingface.co/eanderson/mdeberta-v3-base-qa-squad-nb_v2_temp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_pipeline_en.md new file mode 100644 index 00000000000000..3904c0b74fc31a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_pipeline pipeline DeBertaForQuestionAnswering from eanderson +author: John Snow Labs +name: mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_pipeline` is a English model originally trained by eanderson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_pipeline_en_5.5.0_3.0_1725268990053.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_pipeline_en_5.5.0_3.0_1725268990053.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_qa_squad_norwegian_bokml_v2_temp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|874.2 MB| + +## References + +https://huggingface.co/eanderson/mdeberta-v3-base-qa-squad-nb_v2_temp + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_squad2_sjrhuschlee_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_squad2_sjrhuschlee_pipeline_en.md new file mode 100644 index 00000000000000..2dcabf79c05a94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_squad2_sjrhuschlee_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_v3_base_squad2_sjrhuschlee_pipeline pipeline DeBertaForQuestionAnswering from sjrhuschlee +author: John Snow Labs +name: mdeberta_v3_base_squad2_sjrhuschlee_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_squad2_sjrhuschlee_pipeline` is a English model originally trained by sjrhuschlee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_squad2_sjrhuschlee_pipeline_en_5.5.0_3.0_1725268879801.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_squad2_sjrhuschlee_pipeline_en_5.5.0_3.0_1725268879801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_squad2_sjrhuschlee_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_squad2_sjrhuschlee_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_squad2_sjrhuschlee_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|854.1 MB| + +## References + +https://huggingface.co/sjrhuschlee/mdeberta-v3-base-squad2 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_vnrte_1_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_vnrte_1_en.md new file mode 100644 index 00000000000000..d34ded6c73576b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_vnrte_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mdeberta_v3_base_vnrte_1 DeBertaForSequenceClassification from tmnam20 +author: John Snow Labs +name: mdeberta_v3_base_vnrte_1 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_vnrte_1` is a English model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_vnrte_1_en_5.5.0_3.0_1725281541989.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_vnrte_1_en_5.5.0_3.0_1725281541989.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_vnrte_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_vnrte_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_vnrte_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|794.8 MB| + +## References + +https://huggingface.co/tmnam20/mdeberta-v3-base-vnrte-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_vnrte_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_vnrte_1_pipeline_en.md new file mode 100644 index 00000000000000..83ac9dfe5be3d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_vnrte_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mdeberta_v3_base_vnrte_1_pipeline pipeline DeBertaForSequenceClassification from tmnam20 +author: John Snow Labs +name: mdeberta_v3_base_vnrte_1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_vnrte_1_pipeline` is a English model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_vnrte_1_pipeline_en_5.5.0_3.0_1725281691746.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_vnrte_1_pipeline_en_5.5.0_3.0_1725281691746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_v3_base_vnrte_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_v3_base_vnrte_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base_vnrte_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|794.8 MB| + +## References + +https://huggingface.co/tmnam20/mdeberta-v3-base-vnrte-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_xx.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_xx.md new file mode 100644 index 00000000000000..049275f6d4f4b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual mdeberta_v3_base DeBertaEmbeddings from microsoft +author: John Snow Labs +name: mdeberta_v3_base +date: 2024-09-02 +tags: [xx, open_source, onnx, embeddings, deberta] +task: Embeddings +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base` is a Multilingual model originally trained by microsoft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_xx_5.5.0_3.0_1725261401860.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_xx_5.5.0_3.0_1725261401860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("mdeberta_v3_base","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("mdeberta_v3_base","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_v3_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|xx| +|Size:|660.7 MB| + +## References + +https://huggingface.co/microsoft/mdeberta-v3-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_webis_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_webis_en.md new file mode 100644 index 00000000000000..d24973aa369d5e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_webis_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_webis DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: mdeberta_webis +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_webis` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_webis_en_5.5.0_3.0_1725269278450.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_webis_en_5.5.0_3.0_1725269278450.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_webis","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_webis", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_webis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|849.6 MB| + +## References + +https://huggingface.co/intanm/mdeberta-webis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_webis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_webis_pipeline_en.md new file mode 100644 index 00000000000000..5a1758b014a7d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_webis_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_webis_pipeline pipeline DeBertaForQuestionAnswering from intanm +author: John Snow Labs +name: mdeberta_webis_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_webis_pipeline` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_webis_pipeline_en_5.5.0_3.0_1725269387141.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_webis_pipeline_en_5.5.0_3.0_1725269387141.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_webis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_webis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_webis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|849.6 MB| + +## References + +https://huggingface.co/intanm/mdeberta-webis + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_en.md new file mode 100644 index 00000000000000..1250e0aec2b7f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0 DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_en_5.5.0_3.0_1725268660842.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_en_5.5.0_3.0_1725268660842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|817.8 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-xlwa-en-it_EW-TT-PE_U0_S1_Tingredient_P0.5_DROP1_mdeberta_E5_DEV96.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_pipeline_en.md new file mode 100644 index 00000000000000..43eefdaebc7ec2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_pipeline pipeline DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_pipeline` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_pipeline_en_5.5.0_3.0_1725268774956.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_pipeline_en_5.5.0_3.0_1725268774956.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_5_drop1_mdeberta_e5_dev96_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|817.8 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-xlwa-en-it_EW-TT-PE_U0_S1_Tingredient_P0.5_DROP1_mdeberta_E5_DEV96.0 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_pipeline_en.md new file mode 100644 index 00000000000000..e8ca123c2c06bf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_pipeline pipeline DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_pipeline` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_pipeline_en_5.5.0_3.0_1725269516020.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_pipeline_en_5.5.0_3.0_1725269516020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|817.4 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-xlwa-en-it_EW-TT-PE_U0_S1_Tingredient_P0.75_DROP1_mdeberta_E4_DEV98.0 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline_en.md new file mode 100644 index 00000000000000..ed50a1826ed5b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline pipeline DeBertaForQuestionAnswering from pgajo +author: John Snow Labs +name: mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline` is a English model originally trained by pgajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline_en_5.5.0_3.0_1725240570073.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline_en_5.5.0_3.0_1725240570073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|818.7 MB| + +## References + +https://huggingface.co/pgajo/mdeberta-xlwa-en-it_EW-TT-PE_U1_S0_DROP1_mdeberta_E2_DEV100.0 + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-medical_english_french_9_4_en.md b/docs/_posts/ahmedlone127/2024-09-02-medical_english_french_9_4_en.md new file mode 100644 index 00000000000000..a1757e7abf79f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-medical_english_french_9_4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English medical_english_french_9_4 MarianTransformer from DogGoesBark +author: John Snow Labs +name: medical_english_french_9_4 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medical_english_french_9_4` is a English model originally trained by DogGoesBark. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medical_english_french_9_4_en_5.5.0_3.0_1725304325292.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medical_english_french_9_4_en_5.5.0_3.0_1725304325292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("medical_english_french_9_4","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("medical_english_french_9_4","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|medical_english_french_9_4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.3 MB| + +## References + +https://huggingface.co/DogGoesBark/medical_en_fr_9_4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-medical_english_french_9_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-medical_english_french_9_4_pipeline_en.md new file mode 100644 index 00000000000000..60f82a02c5bb72 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-medical_english_french_9_4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English medical_english_french_9_4_pipeline pipeline MarianTransformer from DogGoesBark +author: John Snow Labs +name: medical_english_french_9_4_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medical_english_french_9_4_pipeline` is a English model originally trained by DogGoesBark. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medical_english_french_9_4_pipeline_en_5.5.0_3.0_1725304359509.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medical_english_french_9_4_pipeline_en_5.5.0_3.0_1725304359509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("medical_english_french_9_4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("medical_english_french_9_4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|medical_english_french_9_4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.8 MB| + +## References + +https://huggingface.co/DogGoesBark/medical_en_fr_9_4 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-medical_pubmed_8_6_en.md b/docs/_posts/ahmedlone127/2024-09-02-medical_pubmed_8_6_en.md new file mode 100644 index 00000000000000..677f712988dcfd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-medical_pubmed_8_6_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English medical_pubmed_8_6 MarianTransformer from DogGoesBark +author: John Snow Labs +name: medical_pubmed_8_6 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medical_pubmed_8_6` is a English model originally trained by DogGoesBark. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medical_pubmed_8_6_en_5.5.0_3.0_1725304560238.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medical_pubmed_8_6_en_5.5.0_3.0_1725304560238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("medical_pubmed_8_6","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("medical_pubmed_8_6","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|medical_pubmed_8_6| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|540.1 MB| + +## References + +https://huggingface.co/DogGoesBark/medical_pubmed_8_6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-medical_pubmed_8_6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-medical_pubmed_8_6_pipeline_en.md new file mode 100644 index 00000000000000..7586023d7ebb2a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-medical_pubmed_8_6_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English medical_pubmed_8_6_pipeline pipeline MarianTransformer from DogGoesBark +author: John Snow Labs +name: medical_pubmed_8_6_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medical_pubmed_8_6_pipeline` is a English model originally trained by DogGoesBark. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medical_pubmed_8_6_pipeline_en_5.5.0_3.0_1725304592566.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medical_pubmed_8_6_pipeline_en_5.5.0_3.0_1725304592566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("medical_pubmed_8_6_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("medical_pubmed_8_6_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|medical_pubmed_8_6_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|540.6 MB| + +## References + +https://huggingface.co/DogGoesBark/medical_pubmed_8_6 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-memo_final_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-memo_final_pipeline_en.md new file mode 100644 index 00000000000000..dae4a09ba6e081 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-memo_final_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English memo_final_pipeline pipeline XlmRoBertaEmbeddings from yemen2016 +author: John Snow Labs +name: memo_final_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_final_pipeline` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_final_pipeline_en_5.5.0_3.0_1725270404068.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_final_pipeline_en_5.5.0_3.0_1725270404068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("memo_final_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("memo_final_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|memo_final_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/memo_final + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-memo_model_3500_en.md b/docs/_posts/ahmedlone127/2024-09-02-memo_model_3500_en.md new file mode 100644 index 00000000000000..0948878ac4b695 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-memo_model_3500_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English memo_model_3500 XlmRoBertaEmbeddings from yemen2016 +author: John Snow Labs +name: memo_model_3500 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_model_3500` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_model_3500_en_5.5.0_3.0_1725270759003.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_model_3500_en_5.5.0_3.0_1725270759003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("memo_model_3500","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("memo_model_3500","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|memo_model_3500| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/memo_model_3500 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-metaphor_detection_xlmr_en.md b/docs/_posts/ahmedlone127/2024-09-02-metaphor_detection_xlmr_en.md new file mode 100644 index 00000000000000..7d40cb88136975 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-metaphor_detection_xlmr_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English metaphor_detection_xlmr XlmRoBertaForTokenClassification from lwachowiak +author: John Snow Labs +name: metaphor_detection_xlmr +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`metaphor_detection_xlmr` is a English model originally trained by lwachowiak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/metaphor_detection_xlmr_en_5.5.0_3.0_1725307620847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/metaphor_detection_xlmr_en_5.5.0_3.0_1725307620847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("metaphor_detection_xlmr","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("metaphor_detection_xlmr", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|metaphor_detection_xlmr| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|786.0 MB| + +## References + +https://huggingface.co/lwachowiak/Metaphor-Detection-XLMR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-metaphor_detection_xlmr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-metaphor_detection_xlmr_pipeline_en.md new file mode 100644 index 00000000000000..b46638e495d956 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-metaphor_detection_xlmr_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English metaphor_detection_xlmr_pipeline pipeline XlmRoBertaForTokenClassification from lwachowiak +author: John Snow Labs +name: metaphor_detection_xlmr_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`metaphor_detection_xlmr_pipeline` is a English model originally trained by lwachowiak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/metaphor_detection_xlmr_pipeline_en_5.5.0_3.0_1725307769857.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/metaphor_detection_xlmr_pipeline_en_5.5.0_3.0_1725307769857.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("metaphor_detection_xlmr_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("metaphor_detection_xlmr_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|metaphor_detection_xlmr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|786.0 MB| + +## References + +https://huggingface.co/lwachowiak/Metaphor-Detection-XLMR + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mformer_fairness_en.md b/docs/_posts/ahmedlone127/2024-09-02-mformer_fairness_en.md new file mode 100644 index 00000000000000..db9da4b86d5c79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mformer_fairness_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mformer_fairness RoBertaForSequenceClassification from joshnguyen +author: John Snow Labs +name: mformer_fairness +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mformer_fairness` is a English model originally trained by joshnguyen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mformer_fairness_en_5.5.0_3.0_1725238087234.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mformer_fairness_en_5.5.0_3.0_1725238087234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("mformer_fairness","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("mformer_fairness", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mformer_fairness| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|464.8 MB| + +## References + +https://huggingface.co/joshnguyen/mformer-fairness \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mika_custom_ir_en.md b/docs/_posts/ahmedlone127/2024-09-02-mika_custom_ir_en.md new file mode 100644 index 00000000000000..383a469e6bb09d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mika_custom_ir_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mika_custom_ir MPNetEmbeddings from NASA-AIML +author: John Snow Labs +name: mika_custom_ir +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mika_custom_ir` is a English model originally trained by NASA-AIML. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mika_custom_ir_en_5.5.0_3.0_1725258330819.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mika_custom_ir_en_5.5.0_3.0_1725258330819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("mika_custom_ir","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("mika_custom_ir","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mika_custom_ir| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.4 MB| + +## References + +https://huggingface.co/NASA-AIML/MIKA_Custom_IR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mika_custom_ir_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mika_custom_ir_pipeline_en.md new file mode 100644 index 00000000000000..afad4005535e24 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mika_custom_ir_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mika_custom_ir_pipeline pipeline MPNetEmbeddings from NASA-AIML +author: John Snow Labs +name: mika_custom_ir_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mika_custom_ir_pipeline` is a English model originally trained by NASA-AIML. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mika_custom_ir_pipeline_en_5.5.0_3.0_1725258352519.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mika_custom_ir_pipeline_en_5.5.0_3.0_1725258352519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mika_custom_ir_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mika_custom_ir_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mika_custom_ir_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.4 MB| + +## References + +https://huggingface.co/NASA-AIML/MIKA_Custom_IR + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-minicheck_roberta_large_en.md b/docs/_posts/ahmedlone127/2024-09-02-minicheck_roberta_large_en.md new file mode 100644 index 00000000000000..53993a06aa5927 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-minicheck_roberta_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English minicheck_roberta_large RoBertaForSequenceClassification from lytang +author: John Snow Labs +name: minicheck_roberta_large +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`minicheck_roberta_large` is a English model originally trained by lytang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/minicheck_roberta_large_en_5.5.0_3.0_1725277491493.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/minicheck_roberta_large_en_5.5.0_3.0_1725277491493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("minicheck_roberta_large","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("minicheck_roberta_large", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|minicheck_roberta_large| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/lytang/MiniCheck-RoBERTa-Large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-minicheck_roberta_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-minicheck_roberta_large_pipeline_en.md new file mode 100644 index 00000000000000..b4f2a60313670e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-minicheck_roberta_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English minicheck_roberta_large_pipeline pipeline RoBertaForSequenceClassification from lytang +author: John Snow Labs +name: minicheck_roberta_large_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`minicheck_roberta_large_pipeline` is a English model originally trained by lytang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/minicheck_roberta_large_pipeline_en_5.5.0_3.0_1725277560238.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/minicheck_roberta_large_pipeline_en_5.5.0_3.0_1725277560238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("minicheck_roberta_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("minicheck_roberta_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|minicheck_roberta_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/lytang/MiniCheck-RoBERTa-Large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-misinformation_trainer_en.md b/docs/_posts/ahmedlone127/2024-09-02-misinformation_trainer_en.md new file mode 100644 index 00000000000000..e994ef53d2037c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-misinformation_trainer_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English misinformation_trainer DistilBertForSequenceClassification from AIUs3r0 +author: John Snow Labs +name: misinformation_trainer +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`misinformation_trainer` is a English model originally trained by AIUs3r0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/misinformation_trainer_en_5.5.0_3.0_1725292056811.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/misinformation_trainer_en_5.5.0_3.0_1725292056811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("misinformation_trainer","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("misinformation_trainer", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|misinformation_trainer| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/AIUs3r0/Misinformation_Trainer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mix1_japanese_english_helsinki_en.md b/docs/_posts/ahmedlone127/2024-09-02-mix1_japanese_english_helsinki_en.md new file mode 100644 index 00000000000000..a88f0b889328bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mix1_japanese_english_helsinki_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mix1_japanese_english_helsinki MarianTransformer from twieland +author: John Snow Labs +name: mix1_japanese_english_helsinki +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mix1_japanese_english_helsinki` is a English model originally trained by twieland. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mix1_japanese_english_helsinki_en_5.5.0_3.0_1725242938971.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mix1_japanese_english_helsinki_en_5.5.0_3.0_1725242938971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("mix1_japanese_english_helsinki","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("mix1_japanese_english_helsinki","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mix1_japanese_english_helsinki| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|517.3 MB| + +## References + +https://huggingface.co/twieland/MIX1_ja-en_helsinki \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mix1_japanese_english_helsinki_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mix1_japanese_english_helsinki_pipeline_en.md new file mode 100644 index 00000000000000..bf8d6981df125b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mix1_japanese_english_helsinki_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mix1_japanese_english_helsinki_pipeline pipeline MarianTransformer from twieland +author: John Snow Labs +name: mix1_japanese_english_helsinki_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mix1_japanese_english_helsinki_pipeline` is a English model originally trained by twieland. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mix1_japanese_english_helsinki_pipeline_en_5.5.0_3.0_1725242966138.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mix1_japanese_english_helsinki_pipeline_en_5.5.0_3.0_1725242966138.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mix1_japanese_english_helsinki_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mix1_japanese_english_helsinki_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mix1_japanese_english_helsinki_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|517.8 MB| + +## References + +https://huggingface.co/twieland/MIX1_ja-en_helsinki + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mix2_english_japanese_helsinki_en.md b/docs/_posts/ahmedlone127/2024-09-02-mix2_english_japanese_helsinki_en.md new file mode 100644 index 00000000000000..ccd47296aa3a41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mix2_english_japanese_helsinki_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mix2_english_japanese_helsinki MarianTransformer from twieland +author: John Snow Labs +name: mix2_english_japanese_helsinki +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mix2_english_japanese_helsinki` is a English model originally trained by twieland. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mix2_english_japanese_helsinki_en_5.5.0_3.0_1725304538345.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mix2_english_japanese_helsinki_en_5.5.0_3.0_1725304538345.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("mix2_english_japanese_helsinki","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("mix2_english_japanese_helsinki","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mix2_english_japanese_helsinki| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|434.3 MB| + +## References + +https://huggingface.co/twieland/MIX2_en-ja_helsinki \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mminilmv2_l12_h384_distilled_from_xlmr_large_en.md b/docs/_posts/ahmedlone127/2024-09-02-mminilmv2_l12_h384_distilled_from_xlmr_large_en.md new file mode 100644 index 00000000000000..340c4368855546 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mminilmv2_l12_h384_distilled_from_xlmr_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mminilmv2_l12_h384_distilled_from_xlmr_large XlmRoBertaEmbeddings from nreimers +author: John Snow Labs +name: mminilmv2_l12_h384_distilled_from_xlmr_large +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilmv2_l12_h384_distilled_from_xlmr_large` is a English model originally trained by nreimers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mminilmv2_l12_h384_distilled_from_xlmr_large_en_5.5.0_3.0_1725270394743.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilmv2_l12_h384_distilled_from_xlmr_large_en_5.5.0_3.0_1725270394743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("mminilmv2_l12_h384_distilled_from_xlmr_large","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("mminilmv2_l12_h384_distilled_from_xlmr_large","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mminilmv2_l12_h384_distilled_from_xlmr_large| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|282.9 MB| + +## References + +https://huggingface.co/nreimers/mMiniLMv2-L12-H384-distilled-from-XLMR-Large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline_en.md new file mode 100644 index 00000000000000..d60a53d43d330b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline pipeline XlmRoBertaEmbeddings from nreimers +author: John Snow Labs +name: mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline` is a English model originally trained by nreimers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline_en_5.5.0_3.0_1725270480022.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline_en_5.5.0_3.0_1725270480022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|282.9 MB| + +## References + +https://huggingface.co/nreimers/mMiniLMv2-L12-H384-distilled-from-XLMR-Large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-model_3_edges_beloiual_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-model_3_edges_beloiual_pipeline_en.md new file mode 100644 index 00000000000000..a14e7fa3b0e89e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-model_3_edges_beloiual_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English model_3_edges_beloiual_pipeline pipeline DistilBertForTokenClassification from beloiual +author: John Snow Labs +name: model_3_edges_beloiual_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_3_edges_beloiual_pipeline` is a English model originally trained by beloiual. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_3_edges_beloiual_pipeline_en_5.5.0_3.0_1725267414064.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_3_edges_beloiual_pipeline_en_5.5.0_3.0_1725267414064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("model_3_edges_beloiual_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("model_3_edges_beloiual_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_3_edges_beloiual_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/beloiual/model_3_edges + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-model_opus_maltese_tc_big_english_portuguese_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-02-model_opus_maltese_tc_big_english_portuguese_finetuned_en.md new file mode 100644 index 00000000000000..e0a2eddbde484f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-model_opus_maltese_tc_big_english_portuguese_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English model_opus_maltese_tc_big_english_portuguese_finetuned MarianTransformer from Miguelcj1 +author: John Snow Labs +name: model_opus_maltese_tc_big_english_portuguese_finetuned +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_opus_maltese_tc_big_english_portuguese_finetuned` is a English model originally trained by Miguelcj1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_opus_maltese_tc_big_english_portuguese_finetuned_en_5.5.0_3.0_1725244148348.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_opus_maltese_tc_big_english_portuguese_finetuned_en_5.5.0_3.0_1725244148348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("model_opus_maltese_tc_big_english_portuguese_finetuned","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("model_opus_maltese_tc_big_english_portuguese_finetuned","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_opus_maltese_tc_big_english_portuguese_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Miguelcj1/model_opus-mt-tc-big-en-pt-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-model_opus_maltese_tc_big_english_portuguese_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-model_opus_maltese_tc_big_english_portuguese_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..58d7f816957b32 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-model_opus_maltese_tc_big_english_portuguese_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English model_opus_maltese_tc_big_english_portuguese_finetuned_pipeline pipeline MarianTransformer from Miguelcj1 +author: John Snow Labs +name: model_opus_maltese_tc_big_english_portuguese_finetuned_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_opus_maltese_tc_big_english_portuguese_finetuned_pipeline` is a English model originally trained by Miguelcj1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_opus_maltese_tc_big_english_portuguese_finetuned_pipeline_en_5.5.0_3.0_1725244213858.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_opus_maltese_tc_big_english_portuguese_finetuned_pipeline_en_5.5.0_3.0_1725244213858.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("model_opus_maltese_tc_big_english_portuguese_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("model_opus_maltese_tc_big_english_portuguese_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_opus_maltese_tc_big_english_portuguese_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Miguelcj1/model_opus-mt-tc-big-en-pt-finetuned + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-model_pipeline_en.md new file mode 100644 index 00000000000000..0dc0e2381b2784 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-model_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English model_pipeline pipeline MPNetEmbeddings from Watwat100 +author: John Snow Labs +name: model_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_pipeline` is a English model originally trained by Watwat100. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_pipeline_en_5.5.0_3.0_1725280838166.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_pipeline_en_5.5.0_3.0_1725280838166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/Watwat100/model + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-model_rikvc_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-02-model_rikvc_pipeline_es.md new file mode 100644 index 00000000000000..44d0faf24a87bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-model_rikvc_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish model_rikvc_pipeline pipeline CamemBertEmbeddings from ovieyra21 +author: John Snow Labs +name: model_rikvc_pipeline +date: 2024-09-02 +tags: [es, open_source, pipeline, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_rikvc_pipeline` is a Castilian, Spanish model originally trained by ovieyra21. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_rikvc_pipeline_es_5.5.0_3.0_1725320786086.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_rikvc_pipeline_es_5.5.0_3.0_1725320786086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("model_rikvc_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("model_rikvc_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_rikvc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|264.0 MB| + +## References + +https://huggingface.co/ovieyra21/model-rikvc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-modele_trad_food_english_french_en.md b/docs/_posts/ahmedlone127/2024-09-02-modele_trad_food_english_french_en.md new file mode 100644 index 00000000000000..3c182d6f3bb4d0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-modele_trad_food_english_french_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English modele_trad_food_english_french MarianTransformer from PaulineSanchez +author: John Snow Labs +name: modele_trad_food_english_french +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modele_trad_food_english_french` is a English model originally trained by PaulineSanchez. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modele_trad_food_english_french_en_5.5.0_3.0_1725304575027.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modele_trad_food_english_french_en_5.5.0_3.0_1725304575027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("modele_trad_food_english_french","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("modele_trad_food_english_french","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|modele_trad_food_english_french| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.4 MB| + +## References + +https://huggingface.co/PaulineSanchez/Modele_Trad_Food_en_fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-modele_trad_food_english_french_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-modele_trad_food_english_french_pipeline_en.md new file mode 100644 index 00000000000000..c608af145e5779 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-modele_trad_food_english_french_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English modele_trad_food_english_french_pipeline pipeline MarianTransformer from PaulineSanchez +author: John Snow Labs +name: modele_trad_food_english_french_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modele_trad_food_english_french_pipeline` is a English model originally trained by PaulineSanchez. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modele_trad_food_english_french_pipeline_en_5.5.0_3.0_1725304605819.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modele_trad_food_english_french_pipeline_en_5.5.0_3.0_1725304605819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("modele_trad_food_english_french_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("modele_trad_food_english_french_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|modele_trad_food_english_french_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|509.0 MB| + +## References + +https://huggingface.co/PaulineSanchez/Modele_Trad_Food_en_fr + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-modelo_qa_beto_squad_spanish_pdqa_en.md b/docs/_posts/ahmedlone127/2024-09-02-modelo_qa_beto_squad_spanish_pdqa_en.md new file mode 100644 index 00000000000000..ced77e3f8cd463 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-modelo_qa_beto_squad_spanish_pdqa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English modelo_qa_beto_squad_spanish_pdqa BertForQuestionAnswering from Lisibonny +author: John Snow Labs +name: modelo_qa_beto_squad_spanish_pdqa +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modelo_qa_beto_squad_spanish_pdqa` is a English model originally trained by Lisibonny. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modelo_qa_beto_squad_spanish_pdqa_en_5.5.0_3.0_1725313095729.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modelo_qa_beto_squad_spanish_pdqa_en_5.5.0_3.0_1725313095729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("modelo_qa_beto_squad_spanish_pdqa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("modelo_qa_beto_squad_spanish_pdqa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|modelo_qa_beto_squad_spanish_pdqa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/Lisibonny/modelo_qa_beto_squad_es_pdqa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-modelo_qa_beto_squad_spanish_pdqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-modelo_qa_beto_squad_spanish_pdqa_pipeline_en.md new file mode 100644 index 00000000000000..b4b9a6150fbfc4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-modelo_qa_beto_squad_spanish_pdqa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English modelo_qa_beto_squad_spanish_pdqa_pipeline pipeline BertForQuestionAnswering from Lisibonny +author: John Snow Labs +name: modelo_qa_beto_squad_spanish_pdqa_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modelo_qa_beto_squad_spanish_pdqa_pipeline` is a English model originally trained by Lisibonny. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modelo_qa_beto_squad_spanish_pdqa_pipeline_en_5.5.0_3.0_1725313118239.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modelo_qa_beto_squad_spanish_pdqa_pipeline_en_5.5.0_3.0_1725313118239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("modelo_qa_beto_squad_spanish_pdqa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("modelo_qa_beto_squad_spanish_pdqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|modelo_qa_beto_squad_spanish_pdqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/Lisibonny/modelo_qa_beto_squad_es_pdqa + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mongolian_xlm_roberta_base_named_entity_mn.md b/docs/_posts/ahmedlone127/2024-09-02-mongolian_xlm_roberta_base_named_entity_mn.md new file mode 100644 index 00000000000000..10d0dc3c6974b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mongolian_xlm_roberta_base_named_entity_mn.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Mongolian mongolian_xlm_roberta_base_named_entity XlmRoBertaForTokenClassification from 2rtl3 +author: John Snow Labs +name: mongolian_xlm_roberta_base_named_entity +date: 2024-09-02 +tags: [mn, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: mn +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mongolian_xlm_roberta_base_named_entity` is a Mongolian model originally trained by 2rtl3. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mongolian_xlm_roberta_base_named_entity_mn_5.5.0_3.0_1725308747908.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mongolian_xlm_roberta_base_named_entity_mn_5.5.0_3.0_1725308747908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("mongolian_xlm_roberta_base_named_entity","mn") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("mongolian_xlm_roberta_base_named_entity", "mn") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mongolian_xlm_roberta_base_named_entity| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|mn| +|Size:|842.2 MB| + +## References + +https://huggingface.co/2rtl3/mn-xlm-roberta-base-named-entity \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mongolian_xlm_roberta_base_named_entity_pipeline_mn.md b/docs/_posts/ahmedlone127/2024-09-02-mongolian_xlm_roberta_base_named_entity_pipeline_mn.md new file mode 100644 index 00000000000000..3a56e09cc5714a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mongolian_xlm_roberta_base_named_entity_pipeline_mn.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Mongolian mongolian_xlm_roberta_base_named_entity_pipeline pipeline XlmRoBertaForTokenClassification from 2rtl3 +author: John Snow Labs +name: mongolian_xlm_roberta_base_named_entity_pipeline +date: 2024-09-02 +tags: [mn, open_source, pipeline, onnx] +task: Named Entity Recognition +language: mn +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mongolian_xlm_roberta_base_named_entity_pipeline` is a Mongolian model originally trained by 2rtl3. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mongolian_xlm_roberta_base_named_entity_pipeline_mn_5.5.0_3.0_1725308817705.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mongolian_xlm_roberta_base_named_entity_pipeline_mn_5.5.0_3.0_1725308817705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mongolian_xlm_roberta_base_named_entity_pipeline", lang = "mn") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mongolian_xlm_roberta_base_named_entity_pipeline", lang = "mn") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mongolian_xlm_roberta_base_named_entity_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|mn| +|Size:|842.2 MB| + +## References + +https://huggingface.co/2rtl3/mn-xlm-roberta-base-named-entity + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_gooaq_en.md b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_gooaq_en.md new file mode 100644 index 00000000000000..1f30ff8ef6ddc3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_gooaq_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mpnet_base_gooaq MPNetEmbeddings from tomaarsen +author: John Snow Labs +name: mpnet_base_gooaq +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_gooaq` is a English model originally trained by tomaarsen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_gooaq_en_5.5.0_3.0_1725258366923.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_gooaq_en_5.5.0_3.0_1725258366923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("mpnet_base_gooaq","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("mpnet_base_gooaq","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_gooaq| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/tomaarsen/mpnet-base-gooaq \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_gooaq_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_gooaq_pipeline_en.md new file mode 100644 index 00000000000000..9bf1c9b5ab8b42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_gooaq_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mpnet_base_gooaq_pipeline pipeline MPNetEmbeddings from tomaarsen +author: John Snow Labs +name: mpnet_base_gooaq_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_gooaq_pipeline` is a English model originally trained by tomaarsen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_gooaq_pipeline_en_5.5.0_3.0_1725258388258.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_gooaq_pipeline_en_5.5.0_3.0_1725258388258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mpnet_base_gooaq_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mpnet_base_gooaq_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_gooaq_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/tomaarsen/mpnet-base-gooaq + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_adaptive_layer_en.md b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_adaptive_layer_en.md new file mode 100644 index 00000000000000..2bd73c65480722 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_adaptive_layer_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mpnet_base_nli_adaptive_layer MPNetEmbeddings from tomaarsen +author: John Snow Labs +name: mpnet_base_nli_adaptive_layer +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_nli_adaptive_layer` is a English model originally trained by tomaarsen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_adaptive_layer_en_5.5.0_3.0_1725313969061.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_adaptive_layer_en_5.5.0_3.0_1725313969061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("mpnet_base_nli_adaptive_layer","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("mpnet_base_nli_adaptive_layer","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_nli_adaptive_layer| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|404.6 MB| + +## References + +https://huggingface.co/tomaarsen/mpnet-base-nli-adaptive-layer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_en.md b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_en.md new file mode 100644 index 00000000000000..1aa6ca1486b9ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mpnet_base_nli MPNetEmbeddings from tomaarsen +author: John Snow Labs +name: mpnet_base_nli +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_nli` is a English model originally trained by tomaarsen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_en_5.5.0_3.0_1725258444954.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_en_5.5.0_3.0_1725258444954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("mpnet_base_nli","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("mpnet_base_nli","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_nli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|404.4 MB| + +## References + +https://huggingface.co/tomaarsen/mpnet-base-nli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_matryoshka_tomaarsen_en.md b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_matryoshka_tomaarsen_en.md new file mode 100644 index 00000000000000..3d0b6520b8e0ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_matryoshka_tomaarsen_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mpnet_base_nli_matryoshka_tomaarsen MPNetEmbeddings from tomaarsen +author: John Snow Labs +name: mpnet_base_nli_matryoshka_tomaarsen +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_nli_matryoshka_tomaarsen` is a English model originally trained by tomaarsen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_matryoshka_tomaarsen_en_5.5.0_3.0_1725258603180.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_matryoshka_tomaarsen_en_5.5.0_3.0_1725258603180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("mpnet_base_nli_matryoshka_tomaarsen","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("mpnet_base_nli_matryoshka_tomaarsen","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_nli_matryoshka_tomaarsen| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|404.4 MB| + +## References + +https://huggingface.co/tomaarsen/mpnet-base-nli-matryoshka \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_matryoshka_tomaarsen_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_matryoshka_tomaarsen_pipeline_en.md new file mode 100644 index 00000000000000..3d874ac395b3ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_matryoshka_tomaarsen_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mpnet_base_nli_matryoshka_tomaarsen_pipeline pipeline MPNetEmbeddings from tomaarsen +author: John Snow Labs +name: mpnet_base_nli_matryoshka_tomaarsen_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_nli_matryoshka_tomaarsen_pipeline` is a English model originally trained by tomaarsen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_matryoshka_tomaarsen_pipeline_en_5.5.0_3.0_1725258628758.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_matryoshka_tomaarsen_pipeline_en_5.5.0_3.0_1725258628758.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mpnet_base_nli_matryoshka_tomaarsen_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mpnet_base_nli_matryoshka_tomaarsen_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_nli_matryoshka_tomaarsen_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|404.4 MB| + +## References + +https://huggingface.co/tomaarsen/mpnet-base-nli-matryoshka + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_sst2_distilled_en.md b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_sst2_distilled_en.md new file mode 100644 index 00000000000000..3a0d061007fe38 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_sst2_distilled_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mpnet_base_sst2_distilled MPNetForSequenceClassification from moshew +author: John Snow Labs +name: mpnet_base_sst2_distilled +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, mpnet] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_sst2_distilled` is a English model originally trained by moshew. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_sst2_distilled_en_5.5.0_3.0_1725255536060.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_sst2_distilled_en_5.5.0_3.0_1725255536060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = MPNetForSequenceClassification.pretrained("mpnet_base_sst2_distilled","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = MPNetForSequenceClassification.pretrained("mpnet_base_sst2_distilled", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_sst2_distilled| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|393.8 MB| + +## References + +https://huggingface.co/moshew/mpnet-base-sst2-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_sst2_distilled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_sst2_distilled_pipeline_en.md new file mode 100644 index 00000000000000..d51e0d3e940385 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_sst2_distilled_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mpnet_base_sst2_distilled_pipeline pipeline MPNetForSequenceClassification from moshew +author: John Snow Labs +name: mpnet_base_sst2_distilled_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_sst2_distilled_pipeline` is a English model originally trained by moshew. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_sst2_distilled_pipeline_en_5.5.0_3.0_1725255564074.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_sst2_distilled_pipeline_en_5.5.0_3.0_1725255564074.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mpnet_base_sst2_distilled_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mpnet_base_sst2_distilled_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_sst2_distilled_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|393.8 MB| + +## References + +https://huggingface.co/moshew/mpnet-base-sst2-distilled + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_v2_ukgov_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_v2_ukgov_finetuned_en.md new file mode 100644 index 00000000000000..ad9f0bf23e3aab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_v2_ukgov_finetuned_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mpnet_base_v2_ukgov_finetuned MPNetEmbeddings from AndreasThinks +author: John Snow Labs +name: mpnet_base_v2_ukgov_finetuned +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_v2_ukgov_finetuned` is a English model originally trained by AndreasThinks. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_v2_ukgov_finetuned_en_5.5.0_3.0_1725313977953.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_v2_ukgov_finetuned_en_5.5.0_3.0_1725313977953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("mpnet_base_v2_ukgov_finetuned","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("mpnet_base_v2_ukgov_finetuned","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_v2_ukgov_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/AndreasThinks/mpnet-base-v2-ukgov-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mrc_xlmr_base_dsc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mrc_xlmr_base_dsc_pipeline_en.md new file mode 100644 index 00000000000000..990167b2a42d88 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mrc_xlmr_base_dsc_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mrc_xlmr_base_dsc_pipeline pipeline XlmRoBertaForQuestionAnswering from MiuN2k3 +author: John Snow Labs +name: mrc_xlmr_base_dsc_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mrc_xlmr_base_dsc_pipeline` is a English model originally trained by MiuN2k3. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mrc_xlmr_base_dsc_pipeline_en_5.5.0_3.0_1725254114807.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mrc_xlmr_base_dsc_pipeline_en_5.5.0_3.0_1725254114807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mrc_xlmr_base_dsc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mrc_xlmr_base_dsc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mrc_xlmr_base_dsc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|815.8 MB| + +## References + +https://huggingface.co/MiuN2k3/mrc-xlmr-base-dsc + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mrpc_microsoft_deberta_v3_base_seed_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mrpc_microsoft_deberta_v3_base_seed_1_pipeline_en.md new file mode 100644 index 00000000000000..bcebd34381bf29 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mrpc_microsoft_deberta_v3_base_seed_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mrpc_microsoft_deberta_v3_base_seed_1_pipeline pipeline DeBertaForSequenceClassification from utahnlp +author: John Snow Labs +name: mrpc_microsoft_deberta_v3_base_seed_1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mrpc_microsoft_deberta_v3_base_seed_1_pipeline` is a English model originally trained by utahnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mrpc_microsoft_deberta_v3_base_seed_1_pipeline_en_5.5.0_3.0_1725282290223.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mrpc_microsoft_deberta_v3_base_seed_1_pipeline_en_5.5.0_3.0_1725282290223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mrpc_microsoft_deberta_v3_base_seed_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mrpc_microsoft_deberta_v3_base_seed_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mrpc_microsoft_deberta_v3_base_seed_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|573.9 MB| + +## References + +https://huggingface.co/utahnlp/mrpc_microsoft_deberta-v3-base_seed-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_en.md b/docs/_posts/ahmedlone127/2024-09-02-multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_en.md new file mode 100644 index 00000000000000..80956c70b82304 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150 MPNetEmbeddings from checkiejan +author: John Snow Labs +name: multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150` is a English model originally trained by checkiejan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_en_5.5.0_3.0_1725280719589.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_en_5.5.0_3.0_1725280719589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/checkiejan/multi-qa-mpnet-base-dot-v1-covidqa-search-75-25-1epoch-1150 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_pipeline_en.md new file mode 100644 index 00000000000000..d43b060ebe0cc9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_pipeline pipeline MPNetEmbeddings from checkiejan +author: John Snow Labs +name: multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_pipeline` is a English model originally trained by checkiejan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_pipeline_en_5.5.0_3.0_1725280743422.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_pipeline_en_5.5.0_3.0_1725280743422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_mpnet_base_dot_v1_covidqa_search_75_25_1epoch_1150_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/checkiejan/multi-qa-mpnet-base-dot-v1-covidqa-search-75-25-1epoch-1150 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_en.md b/docs/_posts/ahmedlone127/2024-09-02-multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_en.md new file mode 100644 index 00000000000000..f5a7904496ab07 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed MPNetEmbeddings from legacy107 +author: John Snow Labs +name: multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed` is a English model originally trained by legacy107. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_en_5.5.0_3.0_1725314123004.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_en_5.5.0_3.0_1725314123004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/legacy107/multi-qa-mpnet-base-dot-v1-wikipedia-search-farmed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_pipeline_en.md new file mode 100644 index 00000000000000..ade7de532d2f3f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_pipeline pipeline MPNetEmbeddings from legacy107 +author: John Snow Labs +name: multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_pipeline` is a English model originally trained by legacy107. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_pipeline_en_5.5.0_3.0_1725314143837.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_pipeline_en_5.5.0_3.0_1725314143837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_mpnet_base_dot_v1_wikipedia_search_farmed_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/legacy107/multi-qa-mpnet-base-dot-v1-wikipedia-search-farmed + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_pipeline_xx.md new file mode 100644 index 00000000000000..3e29e79acceb65 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_pipeline pipeline MarianTransformer from Klarly +author: John Snow Labs +name: multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_pipeline +date: 2024-09-02 +tags: [xx, open_source, pipeline, onnx] +task: Translation +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_pipeline` is a Multilingual model originally trained by Klarly. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_pipeline_xx_5.5.0_3.0_1725243730972.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_pipeline_xx_5.5.0_3.0_1725243730972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|495.3 MB| + +## References + +https://huggingface.co/Klarly/multilingual-MT_FR-ES-IT-PT-RO_CAS-NLP + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_xx.md b/docs/_posts/ahmedlone127/2024-09-02-multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_xx.md new file mode 100644 index 00000000000000..566918ed527754 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp MarianTransformer from Klarly +author: John Snow Labs +name: multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp +date: 2024-09-02 +tags: [xx, open_source, onnx, translation, marian] +task: Translation +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp` is a Multilingual model originally trained by Klarly. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_xx_5.5.0_3.0_1725243704665.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp_xx_5.5.0_3.0_1725243704665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp","xx") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp","xx") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multilingual_maltese_french_spanish_italian_portuguese_romanian_cas_nlp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|xx| +|Size:|494.7 MB| + +## References + +https://huggingface.co/Klarly/multilingual-MT_FR-ES-IT-PT-RO_CAS-NLP \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-multiplenegativesrankingloss_10_en.md b/docs/_posts/ahmedlone127/2024-09-02-multiplenegativesrankingloss_10_en.md new file mode 100644 index 00000000000000..e5f04e6cca5a2b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-multiplenegativesrankingloss_10_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English multiplenegativesrankingloss_10 MPNetEmbeddings from marianodo +author: John Snow Labs +name: multiplenegativesrankingloss_10 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multiplenegativesrankingloss_10` is a English model originally trained by marianodo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multiplenegativesrankingloss_10_en_5.5.0_3.0_1725280695575.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multiplenegativesrankingloss_10_en_5.5.0_3.0_1725280695575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("multiplenegativesrankingloss_10","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("multiplenegativesrankingloss_10","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multiplenegativesrankingloss_10| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/marianodo/MultipleNegativesRankingLoss-10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-multiplenegativesrankingloss_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-multiplenegativesrankingloss_10_pipeline_en.md new file mode 100644 index 00000000000000..87cc1f2dc528b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-multiplenegativesrankingloss_10_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English multiplenegativesrankingloss_10_pipeline pipeline MPNetEmbeddings from marianodo +author: John Snow Labs +name: multiplenegativesrankingloss_10_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multiplenegativesrankingloss_10_pipeline` is a English model originally trained by marianodo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multiplenegativesrankingloss_10_pipeline_en_5.5.0_3.0_1725280716955.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multiplenegativesrankingloss_10_pipeline_en_5.5.0_3.0_1725280716955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("multiplenegativesrankingloss_10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("multiplenegativesrankingloss_10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multiplenegativesrankingloss_10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/marianodo/MultipleNegativesRankingLoss-10 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-mytextcheck_en.md b/docs/_posts/ahmedlone127/2024-09-02-mytextcheck_en.md new file mode 100644 index 00000000000000..1732ad05476b67 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-mytextcheck_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mytextcheck DistilBertForSequenceClassification from Jnanesh12 +author: John Snow Labs +name: mytextcheck +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mytextcheck` is a English model originally trained by Jnanesh12. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mytextcheck_en_5.5.0_3.0_1725305944627.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mytextcheck_en_5.5.0_3.0_1725305944627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("mytextcheck","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("mytextcheck", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mytextcheck| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Jnanesh12/MyTextCheck \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-n_distilbert_imdb_padding10model_realgon_en.md b/docs/_posts/ahmedlone127/2024-09-02-n_distilbert_imdb_padding10model_realgon_en.md new file mode 100644 index 00000000000000..fcae7b47af2fb2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-n_distilbert_imdb_padding10model_realgon_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English n_distilbert_imdb_padding10model_realgon DistilBertForSequenceClassification from Realgon +author: John Snow Labs +name: n_distilbert_imdb_padding10model_realgon +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_distilbert_imdb_padding10model_realgon` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_distilbert_imdb_padding10model_realgon_en_5.5.0_3.0_1725305973517.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_distilbert_imdb_padding10model_realgon_en_5.5.0_3.0_1725305973517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("n_distilbert_imdb_padding10model_realgon","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("n_distilbert_imdb_padding10model_realgon", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_distilbert_imdb_padding10model_realgon| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Realgon/N_distilbert_imdb_padding10model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-n_distilbert_imdb_padding10model_realgon_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-n_distilbert_imdb_padding10model_realgon_pipeline_en.md new file mode 100644 index 00000000000000..8abd624b9b574c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-n_distilbert_imdb_padding10model_realgon_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English n_distilbert_imdb_padding10model_realgon_pipeline pipeline DistilBertForSequenceClassification from Realgon +author: John Snow Labs +name: n_distilbert_imdb_padding10model_realgon_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_distilbert_imdb_padding10model_realgon_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_distilbert_imdb_padding10model_realgon_pipeline_en_5.5.0_3.0_1725305986003.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_distilbert_imdb_padding10model_realgon_pipeline_en_5.5.0_3.0_1725305986003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("n_distilbert_imdb_padding10model_realgon_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("n_distilbert_imdb_padding10model_realgon_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_distilbert_imdb_padding10model_realgon_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Realgon/N_distilbert_imdb_padding10model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-nadi2024_baseline_ar.md b/docs/_posts/ahmedlone127/2024-09-02-nadi2024_baseline_ar.md new file mode 100644 index 00000000000000..1430fd746eb840 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-nadi2024_baseline_ar.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Arabic nadi2024_baseline BertForSequenceClassification from AMR-KELEG +author: John Snow Labs +name: nadi2024_baseline +date: 2024-09-02 +tags: [ar, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nadi2024_baseline` is a Arabic model originally trained by AMR-KELEG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nadi2024_baseline_ar_5.5.0_3.0_1725293237294.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nadi2024_baseline_ar_5.5.0_3.0_1725293237294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("nadi2024_baseline","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("nadi2024_baseline", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nadi2024_baseline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|608.8 MB| + +## References + +https://huggingface.co/AMR-KELEG/NADI2024-baseline \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-nadi2024_baseline_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-02-nadi2024_baseline_pipeline_ar.md new file mode 100644 index 00000000000000..4dae9d11a096f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-nadi2024_baseline_pipeline_ar.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Arabic nadi2024_baseline_pipeline pipeline BertForSequenceClassification from AMR-KELEG +author: John Snow Labs +name: nadi2024_baseline_pipeline +date: 2024-09-02 +tags: [ar, open_source, pipeline, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nadi2024_baseline_pipeline` is a Arabic model originally trained by AMR-KELEG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nadi2024_baseline_pipeline_ar_5.5.0_3.0_1725293269181.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nadi2024_baseline_pipeline_ar_5.5.0_3.0_1725293269181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nadi2024_baseline_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nadi2024_baseline_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nadi2024_baseline_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|608.8 MB| + +## References + +https://huggingface.co/AMR-KELEG/NADI2024-baseline + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-named_entity_recognition_distilbert_b_en.md b/docs/_posts/ahmedlone127/2024-09-02-named_entity_recognition_distilbert_b_en.md new file mode 100644 index 00000000000000..619eb70c1ef499 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-named_entity_recognition_distilbert_b_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English named_entity_recognition_distilbert_b DistilBertForTokenClassification from imrazaa +author: John Snow Labs +name: named_entity_recognition_distilbert_b +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`named_entity_recognition_distilbert_b` is a English model originally trained by imrazaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/named_entity_recognition_distilbert_b_en_5.5.0_3.0_1725267684558.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/named_entity_recognition_distilbert_b_en_5.5.0_3.0_1725267684558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("named_entity_recognition_distilbert_b","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("named_entity_recognition_distilbert_b", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|named_entity_recognition_distilbert_b| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/imrazaa/named-entity-recognition-distilbert-B \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-named_entity_recognition_distilbert_b_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-named_entity_recognition_distilbert_b_pipeline_en.md new file mode 100644 index 00000000000000..0cb628ffd9c301 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-named_entity_recognition_distilbert_b_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English named_entity_recognition_distilbert_b_pipeline pipeline DistilBertForTokenClassification from imrazaa +author: John Snow Labs +name: named_entity_recognition_distilbert_b_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`named_entity_recognition_distilbert_b_pipeline` is a English model originally trained by imrazaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/named_entity_recognition_distilbert_b_pipeline_en_5.5.0_3.0_1725267698028.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/named_entity_recognition_distilbert_b_pipeline_en_5.5.0_3.0_1725267698028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("named_entity_recognition_distilbert_b_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("named_entity_recognition_distilbert_b_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|named_entity_recognition_distilbert_b_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.4 MB| + +## References + +https://huggingface.co/imrazaa/named-entity-recognition-distilbert-B + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-national_climate_targets_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-national_climate_targets_pipeline_en.md new file mode 100644 index 00000000000000..7ce8e34478e0a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-national_climate_targets_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English national_climate_targets_pipeline pipeline RoBertaForSequenceClassification from ClimatePolicyRadar +author: John Snow Labs +name: national_climate_targets_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`national_climate_targets_pipeline` is a English model originally trained by ClimatePolicyRadar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/national_climate_targets_pipeline_en_5.5.0_3.0_1725238338115.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/national_climate_targets_pipeline_en_5.5.0_3.0_1725238338115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("national_climate_targets_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("national_climate_targets_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|national_climate_targets_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|309.7 MB| + +## References + +https://huggingface.co/ClimatePolicyRadar/national-climate-targets + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-negmpnet_en.md b/docs/_posts/ahmedlone127/2024-09-02-negmpnet_en.md new file mode 100644 index 00000000000000..57c9c80c77bf48 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-negmpnet_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English negmpnet MPNetEmbeddings from tum-nlp +author: John Snow Labs +name: negmpnet +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`negmpnet` is a English model originally trained by tum-nlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/negmpnet_en_5.5.0_3.0_1725280361176.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/negmpnet_en_5.5.0_3.0_1725280361176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("negmpnet","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("negmpnet","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|negmpnet| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/tum-nlp/NegMPNet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-negmpnet_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-negmpnet_pipeline_en.md new file mode 100644 index 00000000000000..41c6fe555b76d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-negmpnet_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English negmpnet_pipeline pipeline MPNetEmbeddings from tum-nlp +author: John Snow Labs +name: negmpnet_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`negmpnet_pipeline` is a English model originally trained by tum-nlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/negmpnet_pipeline_en_5.5.0_3.0_1725280391787.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/negmpnet_pipeline_en_5.5.0_3.0_1725280391787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("negmpnet_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("negmpnet_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|negmpnet_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/tum-nlp/NegMPNet + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-nepal_bhasa_trained_croatian_en.md b/docs/_posts/ahmedlone127/2024-09-02-nepal_bhasa_trained_croatian_en.md new file mode 100644 index 00000000000000..29e6144157cadb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-nepal_bhasa_trained_croatian_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nepal_bhasa_trained_croatian DistilBertForTokenClassification from annamariagnat +author: John Snow Labs +name: nepal_bhasa_trained_croatian +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_trained_croatian` is a English model originally trained by annamariagnat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_trained_croatian_en_5.5.0_3.0_1725268135711.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_trained_croatian_en_5.5.0_3.0_1725268135711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("nepal_bhasa_trained_croatian","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("nepal_bhasa_trained_croatian", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nepal_bhasa_trained_croatian| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|505.4 MB| + +## References + +https://huggingface.co/annamariagnat/NEW_trained_croatian \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-nepal_bhasa_trained_croatian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-nepal_bhasa_trained_croatian_pipeline_en.md new file mode 100644 index 00000000000000..c0c378af22096f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-nepal_bhasa_trained_croatian_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nepal_bhasa_trained_croatian_pipeline pipeline DistilBertForTokenClassification from annamariagnat +author: John Snow Labs +name: nepal_bhasa_trained_croatian_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_trained_croatian_pipeline` is a English model originally trained by annamariagnat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_trained_croatian_pipeline_en_5.5.0_3.0_1725268162105.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_trained_croatian_pipeline_en_5.5.0_3.0_1725268162105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nepal_bhasa_trained_croatian_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nepal_bhasa_trained_croatian_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nepal_bhasa_trained_croatian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|505.4 MB| + +## References + +https://huggingface.co/annamariagnat/NEW_trained_croatian + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-nepal_bhasa_trained_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-nepal_bhasa_trained_english_en.md new file mode 100644 index 00000000000000..d1136481d82265 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-nepal_bhasa_trained_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nepal_bhasa_trained_english DistilBertForTokenClassification from annamariagnat +author: John Snow Labs +name: nepal_bhasa_trained_english +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_trained_english` is a English model originally trained by annamariagnat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_trained_english_en_5.5.0_3.0_1725267993646.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_trained_english_en_5.5.0_3.0_1725267993646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("nepal_bhasa_trained_english","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("nepal_bhasa_trained_english", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nepal_bhasa_trained_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|505.4 MB| + +## References + +https://huggingface.co/annamariagnat/NEW_trained_english \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-nepal_bhasa_trained_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-nepal_bhasa_trained_english_pipeline_en.md new file mode 100644 index 00000000000000..7f19f09cd55bc5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-nepal_bhasa_trained_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nepal_bhasa_trained_english_pipeline pipeline DistilBertForTokenClassification from annamariagnat +author: John Snow Labs +name: nepal_bhasa_trained_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_trained_english_pipeline` is a English model originally trained by annamariagnat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_trained_english_pipeline_en_5.5.0_3.0_1725268021575.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_trained_english_pipeline_en_5.5.0_3.0_1725268021575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nepal_bhasa_trained_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nepal_bhasa_trained_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nepal_bhasa_trained_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|505.4 MB| + +## References + +https://huggingface.co/annamariagnat/NEW_trained_english + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ner_phi0108_en.md b/docs/_posts/ahmedlone127/2024-09-02-ner_phi0108_en.md new file mode 100644 index 00000000000000..6c1efd6c60647a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ner_phi0108_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ner_phi0108 DistilBertForTokenClassification from phi0108 +author: John Snow Labs +name: ner_phi0108 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_phi0108` is a English model originally trained by phi0108. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_phi0108_en_5.5.0_3.0_1725268048831.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_phi0108_en_5.5.0_3.0_1725268048831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("ner_phi0108","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_phi0108", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_phi0108| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/phi0108/ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ner_phi0108_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ner_phi0108_pipeline_en.md new file mode 100644 index 00000000000000..c7bd3d25aa8563 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ner_phi0108_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ner_phi0108_pipeline pipeline DistilBertForTokenClassification from phi0108 +author: John Snow Labs +name: ner_phi0108_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_phi0108_pipeline` is a English model originally trained by phi0108. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_phi0108_pipeline_en_5.5.0_3.0_1725268065147.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_phi0108_pipeline_en_5.5.0_3.0_1725268065147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ner_phi0108_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ner_phi0108_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_phi0108_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/phi0108/ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-nermembert_base_4entities_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-nermembert_base_4entities_pipeline_fr.md new file mode 100644 index 00000000000000..0d031aba94bf6b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-nermembert_base_4entities_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French nermembert_base_4entities_pipeline pipeline CamemBertForTokenClassification from CATIE-AQ +author: John Snow Labs +name: nermembert_base_4entities_pipeline +date: 2024-09-02 +tags: [fr, open_source, pipeline, onnx] +task: Named Entity Recognition +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nermembert_base_4entities_pipeline` is a French model originally trained by CATIE-AQ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nermembert_base_4entities_pipeline_fr_5.5.0_3.0_1725266012461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nermembert_base_4entities_pipeline_fr_5.5.0_3.0_1725266012461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nermembert_base_4entities_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nermembert_base_4entities_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nermembert_base_4entities_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|412.0 MB| + +## References + +https://huggingface.co/CATIE-AQ/NERmembert-base-4entities + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-nlp_hf_workshop_arshia_hz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-nlp_hf_workshop_arshia_hz_pipeline_en.md new file mode 100644 index 00000000000000..08913159ac6321 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-nlp_hf_workshop_arshia_hz_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nlp_hf_workshop_arshia_hz_pipeline pipeline DistilBertForSequenceClassification from Arshia-HZ +author: John Snow Labs +name: nlp_hf_workshop_arshia_hz_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_hf_workshop_arshia_hz_pipeline` is a English model originally trained by Arshia-HZ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_hf_workshop_arshia_hz_pipeline_en_5.5.0_3.0_1725305624698.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_hf_workshop_arshia_hz_pipeline_en_5.5.0_3.0_1725305624698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nlp_hf_workshop_arshia_hz_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nlp_hf_workshop_arshia_hz_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nlp_hf_workshop_arshia_hz_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|246.0 MB| + +## References + +https://huggingface.co/Arshia-HZ/NLP_HF_Workshop + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-nlp_transformer_distillbert_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-nlp_transformer_distillbert_sentiment_analysis_pipeline_en.md new file mode 100644 index 00000000000000..c13b73954a9ef2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-nlp_transformer_distillbert_sentiment_analysis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nlp_transformer_distillbert_sentiment_analysis_pipeline pipeline DistilBertForSequenceClassification from mwrites +author: John Snow Labs +name: nlp_transformer_distillbert_sentiment_analysis_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_transformer_distillbert_sentiment_analysis_pipeline` is a English model originally trained by mwrites. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_transformer_distillbert_sentiment_analysis_pipeline_en_5.5.0_3.0_1725306034262.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_transformer_distillbert_sentiment_analysis_pipeline_en_5.5.0_3.0_1725306034262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nlp_transformer_distillbert_sentiment_analysis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nlp_transformer_distillbert_sentiment_analysis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nlp_transformer_distillbert_sentiment_analysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/mwrites/nlp_transformer_distillbert_sentiment_analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_bert_ncc_male2female_en.md b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_bert_ncc_male2female_en.md new file mode 100644 index 00000000000000..ffc9a93534cd2b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_bert_ncc_male2female_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English norwegian_bokml_bert_ncc_male2female BertEmbeddings from NbAiLab +author: John Snow Labs +name: norwegian_bokml_bert_ncc_male2female +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_bert_ncc_male2female` is a English model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_ncc_male2female_en_5.5.0_3.0_1725318910383.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_ncc_male2female_en_5.5.0_3.0_1725318910383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = BertEmbeddings.pretrained("norwegian_bokml_bert_ncc_male2female","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("norwegian_bokml_bert_ncc_male2female","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_bert_ncc_male2female| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|en| +|Size:|666.0 MB| + +## References + +https://huggingface.co/NbAiLab/nb-bert-ncc-male2female \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_base_verbatim_nbailab_no.md b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_base_verbatim_nbailab_no.md new file mode 100644 index 00000000000000..e6c7638f4e35bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_base_verbatim_nbailab_no.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Norwegian norwegian_bokml_whisper_base_verbatim_nbailab WhisperForCTC from NbAiLab +author: John Snow Labs +name: norwegian_bokml_whisper_base_verbatim_nbailab +date: 2024-09-02 +tags: ["no", open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: "no" +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_whisper_base_verbatim_nbailab` is a Norwegian model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_base_verbatim_nbailab_no_5.5.0_3.0_1725247502195.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_base_verbatim_nbailab_no_5.5.0_3.0_1725247502195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("norwegian_bokml_whisper_base_verbatim_nbailab","no") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("norwegian_bokml_whisper_base_verbatim_nbailab", "no") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_whisper_base_verbatim_nbailab| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|no| +|Size:|633.6 MB| + +## References + +https://huggingface.co/NbAiLab/nb-whisper-base-verbatim \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_base_verbatim_nbailab_pipeline_no.md b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_base_verbatim_nbailab_pipeline_no.md new file mode 100644 index 00000000000000..58cdc9c7497665 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_base_verbatim_nbailab_pipeline_no.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Norwegian norwegian_bokml_whisper_base_verbatim_nbailab_pipeline pipeline WhisperForCTC from NbAiLab +author: John Snow Labs +name: norwegian_bokml_whisper_base_verbatim_nbailab_pipeline +date: 2024-09-02 +tags: ["no", open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: "no" +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_whisper_base_verbatim_nbailab_pipeline` is a Norwegian model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_base_verbatim_nbailab_pipeline_no_5.5.0_3.0_1725247543879.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_base_verbatim_nbailab_pipeline_no_5.5.0_3.0_1725247543879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("norwegian_bokml_whisper_base_verbatim_nbailab_pipeline", lang = "no") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("norwegian_bokml_whisper_base_verbatim_nbailab_pipeline", lang = "no") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_whisper_base_verbatim_nbailab_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|no| +|Size:|633.6 MB| + +## References + +https://huggingface.co/NbAiLab/nb-whisper-base-verbatim + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_small_nbailab_no.md b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_small_nbailab_no.md new file mode 100644 index 00000000000000..f7c6f4d1dfeb76 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_small_nbailab_no.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Norwegian norwegian_bokml_whisper_small_nbailab WhisperForCTC from NbAiLab +author: John Snow Labs +name: norwegian_bokml_whisper_small_nbailab +date: 2024-09-02 +tags: ["no", open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: "no" +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_whisper_small_nbailab` is a Norwegian model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_small_nbailab_no_5.5.0_3.0_1725290393721.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_small_nbailab_no_5.5.0_3.0_1725290393721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("norwegian_bokml_whisper_small_nbailab","no") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("norwegian_bokml_whisper_small_nbailab", "no") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_whisper_small_nbailab| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|no| +|Size:|1.7 GB| + +## References + +https://huggingface.co/NbAiLab/nb-whisper-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_small_nbailab_pipeline_no.md b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_small_nbailab_pipeline_no.md new file mode 100644 index 00000000000000..1143f9687c0b8e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_small_nbailab_pipeline_no.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Norwegian norwegian_bokml_whisper_small_nbailab_pipeline pipeline WhisperForCTC from NbAiLab +author: John Snow Labs +name: norwegian_bokml_whisper_small_nbailab_pipeline +date: 2024-09-02 +tags: ["no", open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: "no" +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_whisper_small_nbailab_pipeline` is a Norwegian model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_small_nbailab_pipeline_no_5.5.0_3.0_1725290480624.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_small_nbailab_pipeline_no_5.5.0_3.0_1725290480624.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("norwegian_bokml_whisper_small_nbailab_pipeline", lang = "no") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("norwegian_bokml_whisper_small_nbailab_pipeline", lang = "no") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_whisper_small_nbailab_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|no| +|Size:|1.7 GB| + +## References + +https://huggingface.co/NbAiLab/nb-whisper-small + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_tiny_semantic_no.md b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_tiny_semantic_no.md new file mode 100644 index 00000000000000..8b4d0c589b099f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_tiny_semantic_no.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Norwegian norwegian_bokml_whisper_tiny_semantic WhisperForCTC from NbAiLabBeta +author: John Snow Labs +name: norwegian_bokml_whisper_tiny_semantic +date: 2024-09-02 +tags: ["no", open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: "no" +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_whisper_tiny_semantic` is a Norwegian model originally trained by NbAiLabBeta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_tiny_semantic_no_5.5.0_3.0_1725287642038.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_tiny_semantic_no_5.5.0_3.0_1725287642038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("norwegian_bokml_whisper_tiny_semantic","no") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("norwegian_bokml_whisper_tiny_semantic", "no") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_whisper_tiny_semantic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|no| +|Size:|384.0 MB| + +## References + +https://huggingface.co/NbAiLabBeta/nb-whisper-tiny-semantic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_tiny_semantic_pipeline_no.md b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_tiny_semantic_pipeline_no.md new file mode 100644 index 00000000000000..20bb7e6bc69f7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_tiny_semantic_pipeline_no.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Norwegian norwegian_bokml_whisper_tiny_semantic_pipeline pipeline WhisperForCTC from NbAiLabBeta +author: John Snow Labs +name: norwegian_bokml_whisper_tiny_semantic_pipeline +date: 2024-09-02 +tags: ["no", open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: "no" +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_whisper_tiny_semantic_pipeline` is a Norwegian model originally trained by NbAiLabBeta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_tiny_semantic_pipeline_no_5.5.0_3.0_1725287664277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_tiny_semantic_pipeline_no_5.5.0_3.0_1725287664277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("norwegian_bokml_whisper_tiny_semantic_pipeline", lang = "no") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("norwegian_bokml_whisper_tiny_semantic_pipeline", lang = "no") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_whisper_tiny_semantic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|no| +|Size:|384.0 MB| + +## References + +https://huggingface.co/NbAiLabBeta/nb-whisper-tiny-semantic + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_tiny_verbatim_nbailab_no.md b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_tiny_verbatim_nbailab_no.md new file mode 100644 index 00000000000000..919a088d568d52 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_tiny_verbatim_nbailab_no.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Norwegian norwegian_bokml_whisper_tiny_verbatim_nbailab WhisperForCTC from NbAiLab +author: John Snow Labs +name: norwegian_bokml_whisper_tiny_verbatim_nbailab +date: 2024-09-02 +tags: ["no", open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: "no" +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_whisper_tiny_verbatim_nbailab` is a Norwegian model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_tiny_verbatim_nbailab_no_5.5.0_3.0_1725287782506.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_tiny_verbatim_nbailab_no_5.5.0_3.0_1725287782506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("norwegian_bokml_whisper_tiny_verbatim_nbailab","no") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("norwegian_bokml_whisper_tiny_verbatim_nbailab", "no") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_whisper_tiny_verbatim_nbailab| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|no| +|Size:|384.1 MB| + +## References + +https://huggingface.co/NbAiLab/nb-whisper-tiny-verbatim \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_tiny_verbatim_nbailab_pipeline_no.md b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_tiny_verbatim_nbailab_pipeline_no.md new file mode 100644 index 00000000000000..9eec26cf2d539e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_whisper_tiny_verbatim_nbailab_pipeline_no.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Norwegian norwegian_bokml_whisper_tiny_verbatim_nbailab_pipeline pipeline WhisperForCTC from NbAiLab +author: John Snow Labs +name: norwegian_bokml_whisper_tiny_verbatim_nbailab_pipeline +date: 2024-09-02 +tags: ["no", open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: "no" +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_whisper_tiny_verbatim_nbailab_pipeline` is a Norwegian model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_tiny_verbatim_nbailab_pipeline_no_5.5.0_3.0_1725287809310.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_tiny_verbatim_nbailab_pipeline_no_5.5.0_3.0_1725287809310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("norwegian_bokml_whisper_tiny_verbatim_nbailab_pipeline", lang = "no") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("norwegian_bokml_whisper_tiny_verbatim_nbailab_pipeline", lang = "no") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_whisper_tiny_verbatim_nbailab_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|no| +|Size:|384.1 MB| + +## References + +https://huggingface.co/NbAiLab/nb-whisper-tiny-verbatim + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ofa_multi_400_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ofa_multi_400_pipeline_en.md new file mode 100644 index 00000000000000..40d9458540f48c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ofa_multi_400_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ofa_multi_400_pipeline pipeline XlmRoBertaEmbeddings from yihongLiu +author: John Snow Labs +name: ofa_multi_400_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ofa_multi_400_pipeline` is a English model originally trained by yihongLiu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ofa_multi_400_pipeline_en_5.5.0_3.0_1725271676079.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ofa_multi_400_pipeline_en_5.5.0_3.0_1725271676079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ofa_multi_400_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ofa_multi_400_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ofa_multi_400_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/yihongLiu/ofa-multi-400 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ofm_clip_base_patch32_cifar100_en.md b/docs/_posts/ahmedlone127/2024-09-02-ofm_clip_base_patch32_cifar100_en.md new file mode 100644 index 00000000000000..e8cc59203de08d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ofm_clip_base_patch32_cifar100_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English ofm_clip_base_patch32_cifar100 CLIPForZeroShotClassification from yusx-swapp +author: John Snow Labs +name: ofm_clip_base_patch32_cifar100 +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ofm_clip_base_patch32_cifar100` is a English model originally trained by yusx-swapp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ofm_clip_base_patch32_cifar100_en_5.5.0_3.0_1725275509659.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ofm_clip_base_patch32_cifar100_en_5.5.0_3.0_1725275509659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("ofm_clip_base_patch32_cifar100","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("ofm_clip_base_patch32_cifar100","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ofm_clip_base_patch32_cifar100| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|521.5 MB| + +## References + +https://huggingface.co/yusx-swapp/ofm-clip-base-patch32-cifar100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ofm_clip_base_patch32_cifar100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ofm_clip_base_patch32_cifar100_pipeline_en.md new file mode 100644 index 00000000000000..2f7bf4766e9ec0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ofm_clip_base_patch32_cifar100_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English ofm_clip_base_patch32_cifar100_pipeline pipeline CLIPForZeroShotClassification from yusx-swapp +author: John Snow Labs +name: ofm_clip_base_patch32_cifar100_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ofm_clip_base_patch32_cifar100_pipeline` is a English model originally trained by yusx-swapp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ofm_clip_base_patch32_cifar100_pipeline_en_5.5.0_3.0_1725275556182.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ofm_clip_base_patch32_cifar100_pipeline_en_5.5.0_3.0_1725275556182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ofm_clip_base_patch32_cifar100_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ofm_clip_base_patch32_cifar100_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ofm_clip_base_patch32_cifar100_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|521.5 MB| + +## References + +https://huggingface.co/yusx-swapp/ofm-clip-base-patch32-cifar100 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ogbv_gender_indicbert_tamil_fire20_fin_en.md b/docs/_posts/ahmedlone127/2024-09-02-ogbv_gender_indicbert_tamil_fire20_fin_en.md new file mode 100644 index 00000000000000..5779c691075779 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ogbv_gender_indicbert_tamil_fire20_fin_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ogbv_gender_indicbert_tamil_fire20_fin AlbertForSequenceClassification from Maha +author: John Snow Labs +name: ogbv_gender_indicbert_tamil_fire20_fin +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ogbv_gender_indicbert_tamil_fire20_fin` is a English model originally trained by Maha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ogbv_gender_indicbert_tamil_fire20_fin_en_5.5.0_3.0_1725301686240.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ogbv_gender_indicbert_tamil_fire20_fin_en_5.5.0_3.0_1725301686240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("ogbv_gender_indicbert_tamil_fire20_fin","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("ogbv_gender_indicbert_tamil_fire20_fin", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ogbv_gender_indicbert_tamil_fire20_fin| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|127.7 MB| + +## References + +https://huggingface.co/Maha/OGBV-gender-indicbert-ta-fire20_fin \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ogbv_gender_indicbert_tamil_fire20_fin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ogbv_gender_indicbert_tamil_fire20_fin_pipeline_en.md new file mode 100644 index 00000000000000..73f9b4ed1900d3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ogbv_gender_indicbert_tamil_fire20_fin_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ogbv_gender_indicbert_tamil_fire20_fin_pipeline pipeline AlbertForSequenceClassification from Maha +author: John Snow Labs +name: ogbv_gender_indicbert_tamil_fire20_fin_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ogbv_gender_indicbert_tamil_fire20_fin_pipeline` is a English model originally trained by Maha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ogbv_gender_indicbert_tamil_fire20_fin_pipeline_en_5.5.0_3.0_1725301692651.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ogbv_gender_indicbert_tamil_fire20_fin_pipeline_en_5.5.0_3.0_1725301692651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ogbv_gender_indicbert_tamil_fire20_fin_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ogbv_gender_indicbert_tamil_fire20_fin_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ogbv_gender_indicbert_tamil_fire20_fin_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|127.8 MB| + +## References + +https://huggingface.co/Maha/OGBV-gender-indicbert-ta-fire20_fin + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ogbv_gender_indicbert_tamil_hasoc21_codemix_en.md b/docs/_posts/ahmedlone127/2024-09-02-ogbv_gender_indicbert_tamil_hasoc21_codemix_en.md new file mode 100644 index 00000000000000..b4741cdc4c1010 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ogbv_gender_indicbert_tamil_hasoc21_codemix_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ogbv_gender_indicbert_tamil_hasoc21_codemix AlbertForSequenceClassification from Maha +author: John Snow Labs +name: ogbv_gender_indicbert_tamil_hasoc21_codemix +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ogbv_gender_indicbert_tamil_hasoc21_codemix` is a English model originally trained by Maha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ogbv_gender_indicbert_tamil_hasoc21_codemix_en_5.5.0_3.0_1725301609249.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ogbv_gender_indicbert_tamil_hasoc21_codemix_en_5.5.0_3.0_1725301609249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("ogbv_gender_indicbert_tamil_hasoc21_codemix","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("ogbv_gender_indicbert_tamil_hasoc21_codemix", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ogbv_gender_indicbert_tamil_hasoc21_codemix| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|127.7 MB| + +## References + +https://huggingface.co/Maha/OGBV-gender-indicbert-ta-hasoc21_codemix \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ogbv_gender_indicbert_tamil_hasoc21_codemix_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ogbv_gender_indicbert_tamil_hasoc21_codemix_pipeline_en.md new file mode 100644 index 00000000000000..7d19dd6b0d66e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ogbv_gender_indicbert_tamil_hasoc21_codemix_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ogbv_gender_indicbert_tamil_hasoc21_codemix_pipeline pipeline AlbertForSequenceClassification from Maha +author: John Snow Labs +name: ogbv_gender_indicbert_tamil_hasoc21_codemix_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ogbv_gender_indicbert_tamil_hasoc21_codemix_pipeline` is a English model originally trained by Maha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ogbv_gender_indicbert_tamil_hasoc21_codemix_pipeline_en_5.5.0_3.0_1725301615883.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ogbv_gender_indicbert_tamil_hasoc21_codemix_pipeline_en_5.5.0_3.0_1725301615883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ogbv_gender_indicbert_tamil_hasoc21_codemix_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ogbv_gender_indicbert_tamil_hasoc21_codemix_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ogbv_gender_indicbert_tamil_hasoc21_codemix_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|127.8 MB| + +## References + +https://huggingface.co/Maha/OGBV-gender-indicbert-ta-hasoc21_codemix + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-omega_bioclip_en.md b/docs/_posts/ahmedlone127/2024-09-02-omega_bioclip_en.md new file mode 100644 index 00000000000000..17af4ac6ec7878 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-omega_bioclip_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English omega_bioclip CLIPForZeroShotClassification from Omega02gdfdd +author: John Snow Labs +name: omega_bioclip +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`omega_bioclip` is a English model originally trained by Omega02gdfdd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/omega_bioclip_en_5.5.0_3.0_1725256786183.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/omega_bioclip_en_5.5.0_3.0_1725256786183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("omega_bioclip","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("omega_bioclip","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|omega_bioclip| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|567.0 MB| + +## References + +https://huggingface.co/Omega02gdfdd/Omega-bioclip \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-omega_bioclip_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-omega_bioclip_pipeline_en.md new file mode 100644 index 00000000000000..90b1871c334670 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-omega_bioclip_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English omega_bioclip_pipeline pipeline CLIPForZeroShotClassification from Omega02gdfdd +author: John Snow Labs +name: omega_bioclip_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`omega_bioclip_pipeline` is a English model originally trained by Omega02gdfdd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/omega_bioclip_pipeline_en_5.5.0_3.0_1725256815865.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/omega_bioclip_pipeline_en_5.5.0_3.0_1725256815865.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("omega_bioclip_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("omega_bioclip_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|omega_bioclip_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.0 MB| + +## References + +https://huggingface.co/Omega02gdfdd/Omega-bioclip + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_pipeline_en.md new file mode 100644 index 00000000000000..6fdfb5f0a44eef --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_pipeline pipeline MarianTransformer from kaiku03 +author: John Snow Labs +name: open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_pipeline` is a English model originally trained by kaiku03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_pipeline_en_5.5.0_3.0_1725294524928.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_pipeline_en_5.5.0_3.0_1725294524928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|497.1 MB| + +## References + +https://huggingface.co/kaiku03/open_subtitles-finetuned-opus-mt-en-tl-accelerate + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-optimizer_ner_finetune_lst2021_en.md b/docs/_posts/ahmedlone127/2024-09-02-optimizer_ner_finetune_lst2021_en.md new file mode 100644 index 00000000000000..83faf32bde5cde --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-optimizer_ner_finetune_lst2021_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English optimizer_ner_finetune_lst2021 CamemBertForTokenClassification from famodde +author: John Snow Labs +name: optimizer_ner_finetune_lst2021 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, camembert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`optimizer_ner_finetune_lst2021` is a English model originally trained by famodde. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/optimizer_ner_finetune_lst2021_en_5.5.0_3.0_1725266653837.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/optimizer_ner_finetune_lst2021_en_5.5.0_3.0_1725266653837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = CamemBertForTokenClassification.pretrained("optimizer_ner_finetune_lst2021","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = CamemBertForTokenClassification.pretrained("optimizer_ner_finetune_lst2021", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|optimizer_ner_finetune_lst2021| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|392.2 MB| + +## References + +https://huggingface.co/famodde/optimizer-ner-fineTune-lst2021 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_base_simple_freq_wce_unsampled_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_base_simple_freq_wce_unsampled_en.md new file mode 100644 index 00000000000000..9015ee358d22f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_base_simple_freq_wce_unsampled_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_base_simple_freq_wce_unsampled MarianTransformer from ethansimrm +author: John Snow Labs +name: opus_base_simple_freq_wce_unsampled +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_base_simple_freq_wce_unsampled` is a English model originally trained by ethansimrm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_base_simple_freq_wce_unsampled_en_5.5.0_3.0_1725304851863.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_base_simple_freq_wce_unsampled_en_5.5.0_3.0_1725304851863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_base_simple_freq_wce_unsampled","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_base_simple_freq_wce_unsampled","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_base_simple_freq_wce_unsampled| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.4 MB| + +## References + +https://huggingface.co/ethansimrm/opus_base_simple_freq_wce_unsampled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_big_enfr_ft_choi_2022_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_big_enfr_ft_choi_2022_en.md new file mode 100644 index 00000000000000..3031941a090501 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_big_enfr_ft_choi_2022_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_big_enfr_ft_choi_2022 MarianTransformer from ethansimrm +author: John Snow Labs +name: opus_big_enfr_ft_choi_2022 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_big_enfr_ft_choi_2022` is a English model originally trained by ethansimrm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_big_enfr_ft_choi_2022_en_5.5.0_3.0_1725304189077.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_big_enfr_ft_choi_2022_en_5.5.0_3.0_1725304189077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_big_enfr_ft_choi_2022","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_big_enfr_ft_choi_2022","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_big_enfr_ft_choi_2022| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ethansimrm/opus_big_enfr_FT_choi_2022 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_big_enfr_ft_choi_2022_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_big_enfr_ft_choi_2022_pipeline_en.md new file mode 100644 index 00000000000000..74e221a9e20359 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_big_enfr_ft_choi_2022_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_big_enfr_ft_choi_2022_pipeline pipeline MarianTransformer from ethansimrm +author: John Snow Labs +name: opus_big_enfr_ft_choi_2022_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_big_enfr_ft_choi_2022_pipeline` is a English model originally trained by ethansimrm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_big_enfr_ft_choi_2022_pipeline_en_5.5.0_3.0_1725304252053.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_big_enfr_ft_choi_2022_pipeline_en_5.5.0_3.0_1725304252053.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_big_enfr_ft_choi_2022_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_big_enfr_ft_choi_2022_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_big_enfr_ft_choi_2022_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ethansimrm/opus_big_enfr_FT_choi_2022 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_big_wce_antagonistic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_big_wce_antagonistic_pipeline_en.md new file mode 100644 index 00000000000000..cbcffd82476e80 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_big_wce_antagonistic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_big_wce_antagonistic_pipeline pipeline MarianTransformer from ethansimrm +author: John Snow Labs +name: opus_big_wce_antagonistic_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_big_wce_antagonistic_pipeline` is a English model originally trained by ethansimrm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_big_wce_antagonistic_pipeline_en_5.5.0_3.0_1725304387833.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_big_wce_antagonistic_pipeline_en_5.5.0_3.0_1725304387833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_big_wce_antagonistic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_big_wce_antagonistic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_big_wce_antagonistic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ethansimrm/opus_big_wce_antagonistic + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_em_deberta_3_large_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_em_deberta_3_large_v2_en.md new file mode 100644 index 00000000000000..5c29b7432cecd6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_em_deberta_3_large_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_em_deberta_3_large_v2 DeBertaForSequenceClassification from kerpr +author: John Snow Labs +name: opus_em_deberta_3_large_v2 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_em_deberta_3_large_v2` is a English model originally trained by kerpr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_em_deberta_3_large_v2_en_5.5.0_3.0_1725283664456.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_em_deberta_3_large_v2_en_5.5.0_3.0_1725283664456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("opus_em_deberta_3_large_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("opus_em_deberta_3_large_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_em_deberta_3_large_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/kerpr/opus-em-deberta-3-large-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_em_deberta_3_large_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_em_deberta_3_large_v2_pipeline_en.md new file mode 100644 index 00000000000000..2e8b994a04d15a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_em_deberta_3_large_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_em_deberta_3_large_v2_pipeline pipeline DeBertaForSequenceClassification from kerpr +author: John Snow Labs +name: opus_em_deberta_3_large_v2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_em_deberta_3_large_v2_pipeline` is a English model originally trained by kerpr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_em_deberta_3_large_v2_pipeline_en_5.5.0_3.0_1725283810263.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_em_deberta_3_large_v2_pipeline_en_5.5.0_3.0_1725283810263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_em_deberta_3_large_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_em_deberta_3_large_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_em_deberta_3_large_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/kerpr/opus-em-deberta-3-large-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_en.md new file mode 100644 index 00000000000000..33d48726d97780 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english MarianTransformer from Jezia +author: John Snow Labs +name: opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english` is a English model originally trained by Jezia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_en_5.5.0_3.0_1725295641252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_en_5.5.0_3.0_1725295641252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|527.8 MB| + +## References + +https://huggingface.co/Jezia/opus-mt-ar-en-finetuned_augmented_synthetic_cleaned-ar-to-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_pipeline_en.md new file mode 100644 index 00000000000000..8f0c6b2afcb73b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from Jezia +author: John Snow Labs +name: opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_pipeline` is a English model originally trained by Jezia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725295669438.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725295669438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_arabic_english_finetuned_augmented_synthetic_cleaned_arabic_tonga_tonga_islands_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|528.4 MB| + +## References + +https://huggingface.co/Jezia/opus-mt-ar-en-finetuned_augmented_synthetic_cleaned-ar-to-en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_cantonese_v1_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_cantonese_v1_en.md new file mode 100644 index 00000000000000..89df71ac14a47f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_cantonese_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_cantonese_v1 MarianTransformer from edwinlaw +author: John Snow Labs +name: opus_maltese_cantonese_v1 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_cantonese_v1` is a English model originally trained by edwinlaw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_cantonese_v1_en_5.5.0_3.0_1725295087496.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_cantonese_v1_en_5.5.0_3.0_1725295087496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_cantonese_v1","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_cantonese_v1","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_cantonese_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|540.7 MB| + +## References + +https://huggingface.co/edwinlaw/opus-mt-cantonese-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_cantonese_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_cantonese_v1_pipeline_en.md new file mode 100644 index 00000000000000..a3a74846147408 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_cantonese_v1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_cantonese_v1_pipeline pipeline MarianTransformer from edwinlaw +author: John Snow Labs +name: opus_maltese_cantonese_v1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_cantonese_v1_pipeline` is a English model originally trained by edwinlaw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_cantonese_v1_pipeline_en_5.5.0_3.0_1725295115409.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_cantonese_v1_pipeline_en_5.5.0_3.0_1725295115409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_cantonese_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_cantonese_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_cantonese_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|541.3 MB| + +## References + +https://huggingface.co/edwinlaw/opus-mt-cantonese-v1 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_cantonese_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_cantonese_v2_en.md new file mode 100644 index 00000000000000..bbfb37a97c0295 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_cantonese_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_cantonese_v2 MarianTransformer from edwinlaw +author: John Snow Labs +name: opus_maltese_cantonese_v2 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_cantonese_v2` is a English model originally trained by edwinlaw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_cantonese_v2_en_5.5.0_3.0_1725295443717.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_cantonese_v2_en_5.5.0_3.0_1725295443717.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_cantonese_v2","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_cantonese_v2","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_cantonese_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|540.7 MB| + +## References + +https://huggingface.co/edwinlaw/opus-mt-cantonese-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_celtic_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_celtic_english_en.md new file mode 100644 index 00000000000000..5906f3b22caf9a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_celtic_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_celtic_english MarianTransformer from sshleifer +author: John Snow Labs +name: opus_maltese_celtic_english +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_celtic_english` is a English model originally trained by sshleifer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_celtic_english_en_5.5.0_3.0_1725243971153.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_celtic_english_en_5.5.0_3.0_1725243971153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_celtic_english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_celtic_english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_celtic_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|218.6 MB| + +## References + +https://huggingface.co/sshleifer/opus-mt-CELTIC-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_celtic_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_celtic_english_pipeline_en.md new file mode 100644 index 00000000000000..d377925d2aaf03 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_celtic_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_celtic_english_pipeline pipeline MarianTransformer from sshleifer +author: John Snow Labs +name: opus_maltese_celtic_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_celtic_english_pipeline` is a English model originally trained by sshleifer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_celtic_english_pipeline_en_5.5.0_3.0_1725243982779.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_celtic_english_pipeline_en_5.5.0_3.0_1725243982779.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_celtic_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_celtic_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_celtic_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|219.2 MB| + +## References + +https://huggingface.co/sshleifer/opus-mt-CELTIC-en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_en.md new file mode 100644 index 00000000000000..72646887cd4c29 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english MarianTransformer from dadada +author: John Snow Labs +name: opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english` is a English model originally trained by dadada. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_en_5.5.0_3.0_1725243196241.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_en_5.5.0_3.0_1725243196241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|540.3 MB| + +## References + +https://huggingface.co/dadada/opus-mt-zh-en-ep1-renri-zh-to-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_pipeline_en.md new file mode 100644 index 00000000000000..46b25f55810409 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from dadada +author: John Snow Labs +name: opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_pipeline` is a English model originally trained by dadada. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725243225064.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725243225064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_chinese_english_ep1_renri_chinese_tonga_tonga_islands_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|540.8 MB| + +## References + +https://huggingface.co/dadada/opus-mt-zh-en-ep1-renri-zh-to-en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_bengali_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_bengali_en.md new file mode 100644 index 00000000000000..4878276a0a114b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_bengali_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_english_bengali MarianTransformer from sarwarshafee8709809365 +author: John Snow Labs +name: opus_maltese_english_bengali +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_bengali` is a English model originally trained by sarwarshafee8709809365. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bengali_en_5.5.0_3.0_1725304807821.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bengali_en_5.5.0_3.0_1725304807821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_english_bengali","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_english_bengali","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_bengali| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|530.8 MB| + +## References + +https://huggingface.co/sarwarshafee8709809365/opus-mt-en-bn \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_bengali_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_bengali_pipeline_en.md new file mode 100644 index 00000000000000..1e60c4d9bc3d05 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_bengali_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_english_bengali_pipeline pipeline MarianTransformer from sarwarshafee8709809365 +author: John Snow Labs +name: opus_maltese_english_bengali_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_bengali_pipeline` is a English model originally trained by sarwarshafee8709809365. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bengali_pipeline_en_5.5.0_3.0_1725304836283.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bengali_pipeline_en_5.5.0_3.0_1725304836283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_english_bengali_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_english_bengali_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_bengali_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|531.4 MB| + +## References + +https://huggingface.co/sarwarshafee8709809365/opus-mt-en-bn + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_bkm_10e32_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_bkm_10e32_en.md new file mode 100644 index 00000000000000..2a7fae9c823ef5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_bkm_10e32_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_english_bkm_10e32 MarianTransformer from kalese +author: John Snow Labs +name: opus_maltese_english_bkm_10e32 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_bkm_10e32` is a English model originally trained by kalese. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_10e32_en_5.5.0_3.0_1725304078367.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_10e32_en_5.5.0_3.0_1725304078367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_english_bkm_10e32","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_english_bkm_10e32","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_bkm_10e32| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|507.8 MB| + +## References + +https://huggingface.co/kalese/opus-mt-en-bkm-10e32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_bkm_10e32_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_bkm_10e32_pipeline_en.md new file mode 100644 index 00000000000000..9c6e6d9a102a20 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_bkm_10e32_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_english_bkm_10e32_pipeline pipeline MarianTransformer from kalese +author: John Snow Labs +name: opus_maltese_english_bkm_10e32_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_bkm_10e32_pipeline` is a English model originally trained by kalese. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_10e32_pipeline_en_5.5.0_3.0_1725304104328.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_10e32_pipeline_en_5.5.0_3.0_1725304104328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_english_bkm_10e32_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_english_bkm_10e32_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_bkm_10e32_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.4 MB| + +## References + +https://huggingface.co/kalese/opus-mt-en-bkm-10e32 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_en.md new file mode 100644 index 00000000000000..d03d57412ddf0b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva MarianTransformer from muvva +author: John Snow Labs +name: opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva` is a English model originally trained by muvva. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_en_5.5.0_3.0_1725242569203.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_en_5.5.0_3.0_1725242569203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|523.0 MB| + +## References + +https://huggingface.co/muvva/opus-mt-en-hi-finetuned-en-to-hi \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_pipeline_en.md new file mode 100644 index 00000000000000..2955bf8a01d86c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_pipeline pipeline MarianTransformer from muvva +author: John Snow Labs +name: opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_pipeline` is a English model originally trained by muvva. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_pipeline_en_5.5.0_3.0_1725242601949.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_pipeline_en_5.5.0_3.0_1725242601949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_muvva_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|523.5 MB| + +## References + +https://huggingface.co/muvva/opus-mt-en-hi-finetuned-en-to-hi + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_indonesian_ccmatrix_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_indonesian_ccmatrix_v2_en.md new file mode 100644 index 00000000000000..2746d7a42a5dc9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_indonesian_ccmatrix_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_english_indonesian_ccmatrix_v2 MarianTransformer from yonathanstwn +author: John Snow Labs +name: opus_maltese_english_indonesian_ccmatrix_v2 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_indonesian_ccmatrix_v2` is a English model originally trained by yonathanstwn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_indonesian_ccmatrix_v2_en_5.5.0_3.0_1725243529031.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_indonesian_ccmatrix_v2_en_5.5.0_3.0_1725243529031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_english_indonesian_ccmatrix_v2","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_english_indonesian_ccmatrix_v2","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_indonesian_ccmatrix_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|481.9 MB| + +## References + +https://huggingface.co/yonathanstwn/opus-mt-en-id-ccmatrix-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_indonesian_ccmatrix_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_indonesian_ccmatrix_v2_pipeline_en.md new file mode 100644 index 00000000000000..d86884686456fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_indonesian_ccmatrix_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_english_indonesian_ccmatrix_v2_pipeline pipeline MarianTransformer from yonathanstwn +author: John Snow Labs +name: opus_maltese_english_indonesian_ccmatrix_v2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_indonesian_ccmatrix_v2_pipeline` is a English model originally trained by yonathanstwn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_indonesian_ccmatrix_v2_pipeline_en_5.5.0_3.0_1725243554858.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_indonesian_ccmatrix_v2_pipeline_en_5.5.0_3.0_1725243554858.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_english_indonesian_ccmatrix_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_english_indonesian_ccmatrix_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_indonesian_ccmatrix_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|482.4 MB| + +## References + +https://huggingface.co/yonathanstwn/opus-mt-en-id-ccmatrix-v2 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_pipeline_en.md new file mode 100644 index 00000000000000..2139e2b8d42419 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_pipeline pipeline MarianTransformer from dagger667 +author: John Snow Labs +name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_pipeline` is a English model originally trained by dagger667. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_pipeline_en_5.5.0_3.0_1725295300339.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_pipeline_en_5.5.0_3.0_1725295300339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|509.2 MB| + +## References + +https://huggingface.co/dagger667/opus-mt-en-ro-finetuned-en-to-ro + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_en.md new file mode 100644 index 00000000000000..7473022ae08efe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal MarianTransformer from devyanikoshal +author: John Snow Labs +name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal` is a English model originally trained by devyanikoshal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_en_5.5.0_3.0_1725305177627.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_en_5.5.0_3.0_1725305177627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.5 MB| + +## References + +https://huggingface.co/devyanikoshal/opus-mt-en-ro-finetuned-en-to-ro \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_pipeline_en.md new file mode 100644 index 00000000000000..1ae9c1b35dabd2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_pipeline pipeline MarianTransformer from devyanikoshal +author: John Snow Labs +name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_pipeline` is a English model originally trained by devyanikoshal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_pipeline_en_5.5.0_3.0_1725305203522.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_pipeline_en_5.5.0_3.0_1725305203522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_devyanikoshal_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|509.1 MB| + +## References + +https://huggingface.co/devyanikoshal/opus-mt-en-ro-finetuned-en-to-ro + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pankaj10034_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pankaj10034_pipeline_en.md new file mode 100644 index 00000000000000..3b1914418deba3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pankaj10034_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pankaj10034_pipeline pipeline MarianTransformer from pankaj10034 +author: John Snow Labs +name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pankaj10034_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pankaj10034_pipeline` is a English model originally trained by pankaj10034. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pankaj10034_pipeline_en_5.5.0_3.0_1725295614028.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pankaj10034_pipeline_en_5.5.0_3.0_1725295614028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pankaj10034_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pankaj10034_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pankaj10034_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|509.2 MB| + +## References + +https://huggingface.co/pankaj10034/opus-mt-en-ro-finetuned-en-to-ro + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_en.md new file mode 100644 index 00000000000000..b63431b1beee61 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus MarianTransformer from PontifexMaximus +author: John Snow Labs +name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus` is a English model originally trained by PontifexMaximus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_en_5.5.0_3.0_1725304756466.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_en_5.5.0_3.0_1725304756466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.6 MB| + +## References + +https://huggingface.co/PontifexMaximus/opus-mt-en-ro-finetuned-en-to-ro \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_pipeline_en.md new file mode 100644 index 00000000000000..81771abb6a6cda --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_pipeline pipeline MarianTransformer from PontifexMaximus +author: John Snow Labs +name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_pipeline` is a English model originally trained by PontifexMaximus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_pipeline_en_5.5.0_3.0_1725304783506.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_pipeline_en_5.5.0_3.0_1725304783506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_pontifexmaximus_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|509.1 MB| + +## References + +https://huggingface.co/PontifexMaximus/opus-mt-en-ro-finetuned-en-to-ro + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_en.md new file mode 100644 index 00000000000000..b95ba391fb259e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk MarianTransformer from niktiuk +author: John Snow Labs +name: opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk` is a English model originally trained by niktiuk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_en_5.5.0_3.0_1725304811252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_en_5.5.0_3.0_1725304811252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|525.3 MB| + +## References + +https://huggingface.co/niktiuk/opus-mt-en-ru-finetuned-en-to-ru \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_pipeline_en.md new file mode 100644 index 00000000000000..2a0e2c71102e14 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_pipeline pipeline MarianTransformer from niktiuk +author: John Snow Labs +name: opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_pipeline` is a English model originally trained by niktiuk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_pipeline_en_5.5.0_3.0_1725304839220.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_pipeline_en_5.5.0_3.0_1725304839220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_niktiuk_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|525.8 MB| + +## References + +https://huggingface.co/niktiuk/opus-mt-en-ru-finetuned-en-to-ru + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_jv.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_jv.md new file mode 100644 index 00000000000000..4e03748057d34c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_jv.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Javanese opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese MarianTransformer from hermanshid +author: John Snow Labs +name: opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese +date: 2024-09-02 +tags: [jv, open_source, onnx, translation, marian] +task: Translation +language: jv +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese` is a Javanese model originally trained by hermanshid. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_jv_5.5.0_3.0_1725243840211.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_jv_5.5.0_3.0_1725243840211.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese","jv") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese","jv") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|jv| +|Size:|507.5 MB| + +## References + +https://huggingface.co/hermanshid/opus-mt-finetuned-id-to-jv \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_pipeline_jv.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_pipeline_jv.md new file mode 100644 index 00000000000000..1ce05fbea5caa1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_pipeline_jv.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Javanese opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_pipeline pipeline MarianTransformer from hermanshid +author: John Snow Labs +name: opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_pipeline +date: 2024-09-02 +tags: [jv, open_source, pipeline, onnx] +task: Translation +language: jv +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_pipeline` is a Javanese model originally trained by hermanshid. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_pipeline_jv_5.5.0_3.0_1725243868832.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_pipeline_jv_5.5.0_3.0_1725243868832.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_pipeline", lang = "jv") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_pipeline", lang = "jv") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_finetuned_indonesian_tonga_tonga_islands_javanese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|jv| +|Size:|508.0 MB| + +## References + +https://huggingface.co/hermanshid/opus-mt-finetuned-id-to-jv + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_ft_6_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_ft_6_en.md new file mode 100644 index 00000000000000..9d345fe5ecfe5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_ft_6_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_ft_6 MarianTransformer from abdiharyadi +author: John Snow Labs +name: opus_maltese_ft_6 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_ft_6` is a English model originally trained by abdiharyadi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_ft_6_en_5.5.0_3.0_1725295109313.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_ft_6_en_5.5.0_3.0_1725295109313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_ft_6","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_ft_6","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_ft_6| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|482.1 MB| + +## References + +https://huggingface.co/abdiharyadi/opus-mt-ft-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_ft_6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_ft_6_pipeline_en.md new file mode 100644 index 00000000000000..9d5bf268f5752e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_ft_6_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_ft_6_pipeline pipeline MarianTransformer from abdiharyadi +author: John Snow Labs +name: opus_maltese_ft_6_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_ft_6_pipeline` is a English model originally trained by abdiharyadi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_ft_6_pipeline_en_5.5.0_3.0_1725295134730.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_ft_6_pipeline_en_5.5.0_3.0_1725295134730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_ft_6_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_ft_6_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_ft_6_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|482.6 MB| + +## References + +https://huggingface.co/abdiharyadi/opus-mt-ft-6 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_en.md new file mode 100644 index 00000000000000..7bb757800f34dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney MarianTransformer from NiallRooney +author: John Snow Labs +name: opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney` is a English model originally trained by NiallRooney. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_en_5.5.0_3.0_1725243259774.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_en_5.5.0_3.0_1725243259774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|499.4 MB| + +## References + +https://huggingface.co/NiallRooney/opus-mt-de-en-finetuned-de-to-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_pipeline_en.md new file mode 100644 index 00000000000000..65be353f477401 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_pipeline pipeline MarianTransformer from NiallRooney +author: John Snow Labs +name: opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_pipeline` is a English model originally trained by NiallRooney. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_pipeline_en_5.5.0_3.0_1725243297281.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_pipeline_en_5.5.0_3.0_1725243297281.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_niallrooney_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|500.0 MB| + +## References + +https://huggingface.co/NiallRooney/opus-mt-de-en-finetuned-de-to-en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_bleu_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_bleu_en.md new file mode 100644 index 00000000000000..0ec0b58b85b912 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_bleu_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_bleu MarianTransformer from yonathanstwn +author: John Snow Labs +name: opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_bleu +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_bleu` is a English model originally trained by yonathanstwn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_bleu_en_5.5.0_3.0_1725295980053.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_bleu_en_5.5.0_3.0_1725295980053.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_bleu","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_bleu","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_bleu| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|481.4 MB| + +## References + +https://huggingface.co/yonathanstwn/opus-mt-id-en-ccmatrix-no-warmup-best-bleu \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_en.md new file mode 100644 index 00000000000000..4c9a13c5f87a4b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test MarianTransformer from Edomonndo +author: John Snow Labs +name: opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test` is a English model originally trained by Edomonndo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_en_5.5.0_3.0_1725243455842.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_en_5.5.0_3.0_1725243455842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|514.9 MB| + +## References + +https://huggingface.co/Edomonndo/opus-mt-ja-en-finetuned-ja-to-en_test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_pipeline_en.md new file mode 100644 index 00000000000000..9bebc2f4d089a4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_pipeline pipeline MarianTransformer from Edomonndo +author: John Snow Labs +name: opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_pipeline` is a English model originally trained by Edomonndo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_pipeline_en_5.5.0_3.0_1725243483292.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_pipeline_en_5.5.0_3.0_1725243483292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_japanese_english_finetuned_japanese_tonga_tonga_islands_english_test_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|515.4 MB| + +## References + +https://huggingface.co/Edomonndo/opus-mt-ja-en-finetuned-ja-to-en_test + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_japanese_polish_pop_pipeline_pl.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_japanese_polish_pop_pipeline_pl.md new file mode 100644 index 00000000000000..791310078c39ea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_japanese_polish_pop_pipeline_pl.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Polish opus_maltese_japanese_polish_pop_pipeline pipeline MarianTransformer from Vimek +author: John Snow Labs +name: opus_maltese_japanese_polish_pop_pipeline +date: 2024-09-02 +tags: [pl, open_source, pipeline, onnx] +task: Translation +language: pl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_japanese_polish_pop_pipeline` is a Polish model originally trained by Vimek. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_japanese_polish_pop_pipeline_pl_5.5.0_3.0_1725242874265.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_japanese_polish_pop_pipeline_pl_5.5.0_3.0_1725242874265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_japanese_polish_pop_pipeline", lang = "pl") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_japanese_polish_pop_pipeline", lang = "pl") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_japanese_polish_pop_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|pl| +|Size:|541.3 MB| + +## References + +https://huggingface.co/Vimek/opus-mt-ja-pl-pop + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_japanese_polish_pop_pl.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_japanese_polish_pop_pl.md new file mode 100644 index 00000000000000..421bc2ae26e905 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_japanese_polish_pop_pl.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Polish opus_maltese_japanese_polish_pop MarianTransformer from Vimek +author: John Snow Labs +name: opus_maltese_japanese_polish_pop +date: 2024-09-02 +tags: [pl, open_source, onnx, translation, marian] +task: Translation +language: pl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_japanese_polish_pop` is a Polish model originally trained by Vimek. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_japanese_polish_pop_pl_5.5.0_3.0_1725242845446.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_japanese_polish_pop_pl_5.5.0_3.0_1725242845446.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_japanese_polish_pop","pl") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_japanese_polish_pop","pl") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_japanese_polish_pop| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|pl| +|Size:|540.7 MB| + +## References + +https://huggingface.co/Vimek/opus-mt-ja-pl-pop \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_portuguese_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_portuguese_english_pipeline_en.md new file mode 100644 index 00000000000000..57744118dbd404 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_portuguese_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_portuguese_english_pipeline pipeline MarianTransformer from geralt +author: John Snow Labs +name: opus_maltese_portuguese_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_portuguese_english_pipeline` is a English model originally trained by geralt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_portuguese_english_pipeline_en_5.5.0_3.0_1725295345817.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_portuguese_english_pipeline_en_5.5.0_3.0_1725295345817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_portuguese_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_portuguese_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_portuguese_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|322.0 MB| + +## References + +https://huggingface.co/geralt/Opus-mt-pt-en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_en.md new file mode 100644 index 00000000000000..31b331e19e9edb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova MarianTransformer from akardashova +author: John Snow Labs +name: opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova` is a English model originally trained by akardashova. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_en_5.5.0_3.0_1725305188480.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_en_5.5.0_3.0_1725305188480.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|526.4 MB| + +## References + +https://huggingface.co/akardashova/opus-mt-ru-en-finetuned-ru-to-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_en.md new file mode 100644 index 00000000000000..3d1872ffce1bbd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin MarianTransformer from parutin +author: John Snow Labs +name: opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin` is a English model originally trained by parutin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_en_5.5.0_3.0_1725303731239.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_en_5.5.0_3.0_1725303731239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|526.4 MB| + +## References + +https://huggingface.co/parutin/opus-mt-ru-en-finetuned-ru-to-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_pipeline_en.md new file mode 100644 index 00000000000000..9c04fd1041ba75 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_pipeline pipeline MarianTransformer from parutin +author: John Snow Labs +name: opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_pipeline` is a English model originally trained by parutin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_pipeline_en_5.5.0_3.0_1725303759975.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_pipeline_en_5.5.0_3.0_1725303759975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_parutin_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|526.9 MB| + +## References + +https://huggingface.co/parutin/opus-mt-ru-en-finetuned-ru-to-en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_en.md new file mode 100644 index 00000000000000..2a3052bedf5db1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese MarianTransformer from arcadinis +author: John Snow Labs +name: opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese` is a English model originally trained by arcadinis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_en_5.5.0_3.0_1725242674019.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_en_5.5.0_3.0_1725242674019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/arcadinis/opus-mt-tc-big-en-pt-finetuned-en-to-pt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_pipeline_en.md new file mode 100644 index 00000000000000..19f051d7ce23ee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_pipeline pipeline MarianTransformer from arcadinis +author: John Snow Labs +name: opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_pipeline` is a English model originally trained by arcadinis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_pipeline_en_5.5.0_3.0_1725242743329.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_pipeline_en_5.5.0_3.0_1725242743329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_tc_big_english_portuguese_finetuned_english_tonga_tonga_islands_portuguese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/arcadinis/opus-mt-tc-big-en-pt-finetuned-en-to-pt + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_en.md new file mode 100644 index 00000000000000..93834d5a3c5c45 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english MarianTransformer from PontifexMaximus +author: John Snow Labs +name: opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english` is a English model originally trained by PontifexMaximus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_en_5.5.0_3.0_1725242573258.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_en_5.5.0_3.0_1725242573258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|511.8 MB| + +## References + +https://huggingface.co/PontifexMaximus/opus-mt-tr-en-finetuned-az-to-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_pipeline_en.md new file mode 100644 index 00000000000000..144ba5c4e5cadb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from PontifexMaximus +author: John Snow Labs +name: opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_pipeline` is a English model originally trained by PontifexMaximus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725242609976.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725242609976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_turkish_english_finetuned_azerbaijani_tonga_tonga_islands_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|512.3 MB| + +## References + +https://huggingface.co/PontifexMaximus/opus-mt-tr-en-finetuned-az-to-en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_en.md new file mode 100644 index 00000000000000..f834ccf8ee266b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish MarianTransformer from emre +author: John Snow Labs +name: opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish` is a English model originally trained by emre. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_en_5.5.0_3.0_1725242656645.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_en_5.5.0_3.0_1725242656645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|524.6 MB| + +## References + +https://huggingface.co/emre/opus-mt-tr-en-finetuned-en-to-tr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_pipeline_en.md new file mode 100644 index 00000000000000..a558313b413ea2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_pipeline pipeline MarianTransformer from emre +author: John Snow Labs +name: opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_pipeline` is a English model originally trained by emre. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_pipeline_en_5.5.0_3.0_1725242684219.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_pipeline_en_5.5.0_3.0_1725242684219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_turkish_english_finetuned_english_tonga_tonga_islands_turkish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|525.2 MB| + +## References + +https://huggingface.co/emre/opus-mt-tr-en-finetuned-en-to-tr + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_pipeline_en.md new file mode 100644 index 00000000000000..717e09c3064d76 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from PontifexMaximus +author: John Snow Labs +name: opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_pipeline` is a English model originally trained by PontifexMaximus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725243919052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725243919052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|521.3 MB| + +## References + +https://huggingface.co/PontifexMaximus/opus-mt-ur-en-finetuned-ur-to-en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_pipeline_en.md new file mode 100644 index 00000000000000..26fcd1630186fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-opus_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_pipeline pipeline MarianTransformer from andrejaystevenson +author: John Snow Labs +name: opus_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_pipeline` is a English model originally trained by andrejaystevenson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_pipeline_en_5.5.0_3.0_1725304895277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_pipeline_en_5.5.0_3.0_1725304895277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|330.6 MB| + +## References + +https://huggingface.co/andrejaystevenson/opus + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-out_en.md b/docs/_posts/ahmedlone127/2024-09-02-out_en.md new file mode 100644 index 00000000000000..461b96685d1e12 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-out_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English out AlbertForQuestionAnswering from haibotamiu +author: John Snow Labs +name: out +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`out` is a English model originally trained by haibotamiu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/out_en_5.5.0_3.0_1725236844762.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/out_en_5.5.0_3.0_1725236844762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("out","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("out", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|out| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/haibotamiu/out \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-out_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-out_pipeline_en.md new file mode 100644 index 00000000000000..3ed51607dbf8c3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-out_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English out_pipeline pipeline AlbertForQuestionAnswering from haibotamiu +author: John Snow Labs +name: out_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`out_pipeline` is a English model originally trained by haibotamiu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/out_pipeline_en_5.5.0_3.0_1725236847099.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/out_pipeline_en_5.5.0_3.0_1725236847099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("out_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("out_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|out_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/haibotamiu/out + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_en.md b/docs/_posts/ahmedlone127/2024-09-02-output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_en.md new file mode 100644 index 00000000000000..bafc48fce7f45f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1 RoBertaForQuestionAnswering from AnonymousSub +author: John Snow Labs +name: output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1` is a English model originally trained by AnonymousSub. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_en_5.5.0_3.0_1725252286733.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_en_5.5.0_3.0_1725252286733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/AnonymousSub/output_mask_TWO_STEPS_pretraining_plus_contr_roberta-large_EASY_EPOCHS_1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_pipeline_en.md new file mode 100644 index 00000000000000..ee3182a30f1261 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub +author: John Snow Labs +name: output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_pipeline` is a English model originally trained by AnonymousSub. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_pipeline_en_5.5.0_3.0_1725252357459.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_pipeline_en_5.5.0_3.0_1725252357459.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|output_mask_two_steps_pretraining_plus_contr_roberta_large_easy_epochs_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/AnonymousSub/output_mask_TWO_STEPS_pretraining_plus_contr_roberta-large_EASY_EPOCHS_1 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-parsbert_quran_qa_en.md b/docs/_posts/ahmedlone127/2024-09-02-parsbert_quran_qa_en.md new file mode 100644 index 00000000000000..627186bee10182 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-parsbert_quran_qa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English parsbert_quran_qa BertForQuestionAnswering from NeginShams +author: John Snow Labs +name: parsbert_quran_qa +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`parsbert_quran_qa` is a English model originally trained by NeginShams. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/parsbert_quran_qa_en_5.5.0_3.0_1725313093388.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/parsbert_quran_qa_en_5.5.0_3.0_1725313093388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("parsbert_quran_qa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("parsbert_quran_qa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|parsbert_quran_qa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|441.5 MB| + +## References + +https://huggingface.co/NeginShams/parsbert-Quran_QA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-parsbert_quran_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-parsbert_quran_qa_pipeline_en.md new file mode 100644 index 00000000000000..e17669e8196806 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-parsbert_quran_qa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English parsbert_quran_qa_pipeline pipeline BertForQuestionAnswering from NeginShams +author: John Snow Labs +name: parsbert_quran_qa_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`parsbert_quran_qa_pipeline` is a English model originally trained by NeginShams. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/parsbert_quran_qa_pipeline_en_5.5.0_3.0_1725313119404.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/parsbert_quran_qa_pipeline_en_5.5.0_3.0_1725313119404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("parsbert_quran_qa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("parsbert_quran_qa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|parsbert_quran_qa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|441.5 MB| + +## References + +https://huggingface.co/NeginShams/parsbert-Quran_QA + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-partypress_monolingual_ukrainian_en.md b/docs/_posts/ahmedlone127/2024-09-02-partypress_monolingual_ukrainian_en.md new file mode 100644 index 00000000000000..c8ad7f49e89e7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-partypress_monolingual_ukrainian_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English partypress_monolingual_ukrainian RoBertaForSequenceClassification from partypress +author: John Snow Labs +name: partypress_monolingual_ukrainian +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`partypress_monolingual_ukrainian` is a English model originally trained by partypress. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/partypress_monolingual_ukrainian_en_5.5.0_3.0_1725277008750.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/partypress_monolingual_ukrainian_en_5.5.0_3.0_1725277008750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("partypress_monolingual_ukrainian","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("partypress_monolingual_ukrainian", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|partypress_monolingual_ukrainian| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|446.8 MB| + +## References + +https://huggingface.co/partypress/partypress-monolingual-uk \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-partypress_monolingual_ukrainian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-partypress_monolingual_ukrainian_pipeline_en.md new file mode 100644 index 00000000000000..38fccad6c6d5ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-partypress_monolingual_ukrainian_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English partypress_monolingual_ukrainian_pipeline pipeline RoBertaForSequenceClassification from partypress +author: John Snow Labs +name: partypress_monolingual_ukrainian_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`partypress_monolingual_ukrainian_pipeline` is a English model originally trained by partypress. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/partypress_monolingual_ukrainian_pipeline_en_5.5.0_3.0_1725277045782.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/partypress_monolingual_ukrainian_pipeline_en_5.5.0_3.0_1725277045782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("partypress_monolingual_ukrainian_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("partypress_monolingual_ukrainian_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|partypress_monolingual_ukrainian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|446.8 MB| + +## References + +https://huggingface.co/partypress/partypress-monolingual-uk + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-personal_whisper_distilled_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-personal_whisper_distilled_model_pipeline_en.md new file mode 100644 index 00000000000000..6c7d49507a6304 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-personal_whisper_distilled_model_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English personal_whisper_distilled_model_pipeline pipeline WhisperForCTC from fractalego +author: John Snow Labs +name: personal_whisper_distilled_model_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`personal_whisper_distilled_model_pipeline` is a English model originally trained by fractalego. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/personal_whisper_distilled_model_pipeline_en_5.5.0_3.0_1725290594149.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/personal_whisper_distilled_model_pipeline_en_5.5.0_3.0_1725290594149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("personal_whisper_distilled_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("personal_whisper_distilled_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|personal_whisper_distilled_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|2.2 GB| + +## References + +https://huggingface.co/fractalego/personal-whisper-distilled-model + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-personality_lm_kevsun_en.md b/docs/_posts/ahmedlone127/2024-09-02-personality_lm_kevsun_en.md new file mode 100644 index 00000000000000..cebc0f4dcb96f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-personality_lm_kevsun_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English personality_lm_kevsun RoBertaForSequenceClassification from KevSun +author: John Snow Labs +name: personality_lm_kevsun +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`personality_lm_kevsun` is a English model originally trained by KevSun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/personality_lm_kevsun_en_5.5.0_3.0_1725237803600.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/personality_lm_kevsun_en_5.5.0_3.0_1725237803600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("personality_lm_kevsun","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("personality_lm_kevsun", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|personality_lm_kevsun| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|466.4 MB| + +## References + +https://huggingface.co/KevSun/Personality_LM \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-personality_lm_kevsun_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-personality_lm_kevsun_pipeline_en.md new file mode 100644 index 00000000000000..e35a1fec4f7b91 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-personality_lm_kevsun_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English personality_lm_kevsun_pipeline pipeline RoBertaForSequenceClassification from KevSun +author: John Snow Labs +name: personality_lm_kevsun_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`personality_lm_kevsun_pipeline` is a English model originally trained by KevSun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/personality_lm_kevsun_pipeline_en_5.5.0_3.0_1725237831270.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/personality_lm_kevsun_pipeline_en_5.5.0_3.0_1725237831270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("personality_lm_kevsun_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("personality_lm_kevsun_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|personality_lm_kevsun_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|466.4 MB| + +## References + +https://huggingface.co/KevSun/Personality_LM + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-plant_model_en.md b/docs/_posts/ahmedlone127/2024-09-02-plant_model_en.md new file mode 100644 index 00000000000000..f139f879c44f80 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-plant_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English plant_model DistilBertForTokenClassification from KHEYH +author: John Snow Labs +name: plant_model +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`plant_model` is a English model originally trained by KHEYH. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/plant_model_en_5.5.0_3.0_1725267811112.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/plant_model_en_5.5.0_3.0_1725267811112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("plant_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("plant_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|plant_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/KHEYH/plant_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-plant_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-plant_model_pipeline_en.md new file mode 100644 index 00000000000000..ff5d8b7ed4f968 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-plant_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English plant_model_pipeline pipeline DistilBertForTokenClassification from KHEYH +author: John Snow Labs +name: plant_model_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`plant_model_pipeline` is a English model originally trained by KHEYH. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/plant_model_pipeline_en_5.5.0_3.0_1725267824475.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/plant_model_pipeline_en_5.5.0_3.0_1725267824475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("plant_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("plant_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|plant_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/KHEYH/plant_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-plip_en.md b/docs/_posts/ahmedlone127/2024-09-02-plip_en.md new file mode 100644 index 00000000000000..f25c5ebd8650c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-plip_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English plip CLIPForZeroShotClassification from vinid +author: John Snow Labs +name: plip +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`plip` is a English model originally trained by vinid. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/plip_en_5.5.0_3.0_1725275401988.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/plip_en_5.5.0_3.0_1725275401988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("plip","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("plip","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|plip| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/vinid/plip \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-plip_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-plip_pipeline_en.md new file mode 100644 index 00000000000000..9d0dbd510351c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-plip_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English plip_pipeline pipeline CLIPForZeroShotClassification from vinid +author: John Snow Labs +name: plip_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`plip_pipeline` is a English model originally trained by vinid. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/plip_pipeline_en_5.5.0_3.0_1725275501205.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/plip_pipeline_en_5.5.0_3.0_1725275501205.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("plip_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("plip_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|plip_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.5 MB| + +## References + +https://huggingface.co/vinid/plip + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-poitreqm_model_sentiment_tweets_en.md b/docs/_posts/ahmedlone127/2024-09-02-poitreqm_model_sentiment_tweets_en.md new file mode 100644 index 00000000000000..da0a0a70d4b961 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-poitreqm_model_sentiment_tweets_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English poitreqm_model_sentiment_tweets RoBertaForSequenceClassification from Poitreqm +author: John Snow Labs +name: poitreqm_model_sentiment_tweets +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`poitreqm_model_sentiment_tweets` is a English model originally trained by Poitreqm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/poitreqm_model_sentiment_tweets_en_5.5.0_3.0_1725277002655.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/poitreqm_model_sentiment_tweets_en_5.5.0_3.0_1725277002655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("poitreqm_model_sentiment_tweets","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("poitreqm_model_sentiment_tweets", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|poitreqm_model_sentiment_tweets| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/Poitreqm/poitreqm-model-sentiment-tweets \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-poitreqm_model_sentiment_tweets_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-poitreqm_model_sentiment_tweets_pipeline_en.md new file mode 100644 index 00000000000000..09d00b1afb9a43 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-poitreqm_model_sentiment_tweets_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English poitreqm_model_sentiment_tweets_pipeline pipeline RoBertaForSequenceClassification from Poitreqm +author: John Snow Labs +name: poitreqm_model_sentiment_tweets_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`poitreqm_model_sentiment_tweets_pipeline` is a English model originally trained by Poitreqm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/poitreqm_model_sentiment_tweets_pipeline_en_5.5.0_3.0_1725277030733.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/poitreqm_model_sentiment_tweets_pipeline_en_5.5.0_3.0_1725277030733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("poitreqm_model_sentiment_tweets_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("poitreqm_model_sentiment_tweets_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|poitreqm_model_sentiment_tweets_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/Poitreqm/poitreqm-model-sentiment-tweets + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-pokemon_english_tonga_tonga_islands_chinese_en.md b/docs/_posts/ahmedlone127/2024-09-02-pokemon_english_tonga_tonga_islands_chinese_en.md new file mode 100644 index 00000000000000..5b8585f0cb6a22 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-pokemon_english_tonga_tonga_islands_chinese_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English pokemon_english_tonga_tonga_islands_chinese MarianTransformer from nkuAlexLee +author: John Snow Labs +name: pokemon_english_tonga_tonga_islands_chinese +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pokemon_english_tonga_tonga_islands_chinese` is a English model originally trained by nkuAlexLee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pokemon_english_tonga_tonga_islands_chinese_en_5.5.0_3.0_1725305105813.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pokemon_english_tonga_tonga_islands_chinese_en_5.5.0_3.0_1725305105813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("pokemon_english_tonga_tonga_islands_chinese","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("pokemon_english_tonga_tonga_islands_chinese","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pokemon_english_tonga_tonga_islands_chinese| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|541.0 MB| + +## References + +https://huggingface.co/nkuAlexLee/Pokemon_EN_to_ZH \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-pokemon_english_tonga_tonga_islands_chinese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-pokemon_english_tonga_tonga_islands_chinese_pipeline_en.md new file mode 100644 index 00000000000000..a6f7af8092d52d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-pokemon_english_tonga_tonga_islands_chinese_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English pokemon_english_tonga_tonga_islands_chinese_pipeline pipeline MarianTransformer from nkuAlexLee +author: John Snow Labs +name: pokemon_english_tonga_tonga_islands_chinese_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pokemon_english_tonga_tonga_islands_chinese_pipeline` is a English model originally trained by nkuAlexLee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pokemon_english_tonga_tonga_islands_chinese_pipeline_en_5.5.0_3.0_1725305133441.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pokemon_english_tonga_tonga_islands_chinese_pipeline_en_5.5.0_3.0_1725305133441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("pokemon_english_tonga_tonga_islands_chinese_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("pokemon_english_tonga_tonga_islands_chinese_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pokemon_english_tonga_tonga_islands_chinese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|541.6 MB| + +## References + +https://huggingface.co/nkuAlexLee/Pokemon_EN_to_ZH + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-preposition_dbg_german_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-preposition_dbg_german_v2_en.md new file mode 100644 index 00000000000000..f8e7ca5fd66925 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-preposition_dbg_german_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English preposition_dbg_german_v2 CamemBertForTokenClassification from gguichard +author: John Snow Labs +name: preposition_dbg_german_v2 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, camembert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`preposition_dbg_german_v2` is a English model originally trained by gguichard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/preposition_dbg_german_v2_en_5.5.0_3.0_1725266224667.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/preposition_dbg_german_v2_en_5.5.0_3.0_1725266224667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = CamemBertForTokenClassification.pretrained("preposition_dbg_german_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = CamemBertForTokenClassification.pretrained("preposition_dbg_german_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|preposition_dbg_german_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|904.4 MB| + +## References + +https://huggingface.co/gguichard/preposition_dbg_de_v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-preposition_dbg_german_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-preposition_dbg_german_v2_pipeline_en.md new file mode 100644 index 00000000000000..7c50b03ef48f9f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-preposition_dbg_german_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English preposition_dbg_german_v2_pipeline pipeline CamemBertForTokenClassification from gguichard +author: John Snow Labs +name: preposition_dbg_german_v2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`preposition_dbg_german_v2_pipeline` is a English model originally trained by gguichard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/preposition_dbg_german_v2_pipeline_en_5.5.0_3.0_1725266430064.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/preposition_dbg_german_v2_pipeline_en_5.5.0_3.0_1725266430064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("preposition_dbg_german_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("preposition_dbg_german_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|preposition_dbg_german_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|904.4 MB| + +## References + +https://huggingface.co/gguichard/preposition_dbg_de_v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-prev_lab1_random_en.md b/docs/_posts/ahmedlone127/2024-09-02-prev_lab1_random_en.md new file mode 100644 index 00000000000000..33fa83b1511fa6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-prev_lab1_random_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English prev_lab1_random MarianTransformer from minhngca +author: John Snow Labs +name: prev_lab1_random +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`prev_lab1_random` is a English model originally trained by minhngca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/prev_lab1_random_en_5.5.0_3.0_1725294440517.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/prev_lab1_random_en_5.5.0_3.0_1725294440517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("prev_lab1_random","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("prev_lab1_random","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|prev_lab1_random| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.3 MB| + +## References + +https://huggingface.co/minhngca/prev_lab1_random \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-prev_lab1_random_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-prev_lab1_random_pipeline_en.md new file mode 100644 index 00000000000000..4f190432000a74 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-prev_lab1_random_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English prev_lab1_random_pipeline pipeline MarianTransformer from minhngca +author: John Snow Labs +name: prev_lab1_random_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`prev_lab1_random_pipeline` is a English model originally trained by minhngca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/prev_lab1_random_pipeline_en_5.5.0_3.0_1725294482586.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/prev_lab1_random_pipeline_en_5.5.0_3.0_1725294482586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("prev_lab1_random_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("prev_lab1_random_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|prev_lab1_random_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.8 MB| + +## References + +https://huggingface.co/minhngca/prev_lab1_random + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-privacy_masknig_en.md b/docs/_posts/ahmedlone127/2024-09-02-privacy_masknig_en.md new file mode 100644 index 00000000000000..180ce6dbcea06c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-privacy_masknig_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English privacy_masknig DistilBertForTokenClassification from taro-pudding +author: John Snow Labs +name: privacy_masknig +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, distilbert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`privacy_masknig` is a English model originally trained by taro-pudding. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/privacy_masknig_en_5.5.0_3.0_1725267426778.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/privacy_masknig_en_5.5.0_3.0_1725267426778.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = DistilBertForTokenClassification.pretrained("privacy_masknig","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DistilBertForTokenClassification.pretrained("privacy_masknig", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|privacy_masknig| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|505.6 MB| + +## References + +https://huggingface.co/taro-pudding/privacy-masknig \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-privacy_masknig_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-privacy_masknig_pipeline_en.md new file mode 100644 index 00000000000000..e8dd95be2126e5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-privacy_masknig_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English privacy_masknig_pipeline pipeline DistilBertForTokenClassification from taro-pudding +author: John Snow Labs +name: privacy_masknig_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`privacy_masknig_pipeline` is a English model originally trained by taro-pudding. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/privacy_masknig_pipeline_en_5.5.0_3.0_1725267456314.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/privacy_masknig_pipeline_en_5.5.0_3.0_1725267456314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("privacy_masknig_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("privacy_masknig_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|privacy_masknig_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|505.6 MB| + +## References + +https://huggingface.co/taro-pudding/privacy-masknig + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-pubchem10m_smiles_bpe_60k_en.md b/docs/_posts/ahmedlone127/2024-09-02-pubchem10m_smiles_bpe_60k_en.md new file mode 100644 index 00000000000000..be45455f4179e5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-pubchem10m_smiles_bpe_60k_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English pubchem10m_smiles_bpe_60k RoBertaEmbeddings from seyonec +author: John Snow Labs +name: pubchem10m_smiles_bpe_60k +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubchem10m_smiles_bpe_60k` is a English model originally trained by seyonec. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pubchem10m_smiles_bpe_60k_en_5.5.0_3.0_1725264265628.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubchem10m_smiles_bpe_60k_en_5.5.0_3.0_1725264265628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("pubchem10m_smiles_bpe_60k","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("pubchem10m_smiles_bpe_60k","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pubchem10m_smiles_bpe_60k| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|310.2 MB| + +## References + +https://huggingface.co/seyonec/PubChem10M_SMILES_BPE_60k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-punjabi_albert_en.md b/docs/_posts/ahmedlone127/2024-09-02-punjabi_albert_en.md new file mode 100644 index 00000000000000..8a591cd392889a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-punjabi_albert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English punjabi_albert AlbertEmbeddings from mirfan899 +author: John Snow Labs +name: punjabi_albert +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, albert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`punjabi_albert` is a English model originally trained by mirfan899. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/punjabi_albert_en_5.5.0_3.0_1725306691986.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/punjabi_albert_en_5.5.0_3.0_1725306691986.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = AlbertEmbeddings.pretrained("punjabi_albert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = AlbertEmbeddings.pretrained("punjabi_albert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|punjabi_albert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[albert]| +|Language:|en| +|Size:|62.6 MB| + +## References + +https://huggingface.co/mirfan899/punjabi_albert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-punjabi_albert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-punjabi_albert_pipeline_en.md new file mode 100644 index 00000000000000..cb58537ed57ec5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-punjabi_albert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English punjabi_albert_pipeline pipeline AlbertEmbeddings from mirfan899 +author: John Snow Labs +name: punjabi_albert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`punjabi_albert_pipeline` is a English model originally trained by mirfan899. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/punjabi_albert_pipeline_en_5.5.0_3.0_1725306695195.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/punjabi_albert_pipeline_en_5.5.0_3.0_1725306695195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("punjabi_albert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("punjabi_albert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|punjabi_albert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|62.6 MB| + +## References + +https://huggingface.co/mirfan899/punjabi_albert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-qa_persian_albert_persian_farsi_zwnj_base_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-qa_persian_albert_persian_farsi_zwnj_base_v2_en.md new file mode 100644 index 00000000000000..e7694385e1ada8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-qa_persian_albert_persian_farsi_zwnj_base_v2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English qa_persian_albert_persian_farsi_zwnj_base_v2 AlbertForQuestionAnswering from makhataei +author: John Snow Labs +name: qa_persian_albert_persian_farsi_zwnj_base_v2 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_persian_albert_persian_farsi_zwnj_base_v2` is a English model originally trained by makhataei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_persian_albert_persian_farsi_zwnj_base_v2_en_5.5.0_3.0_1725236729719.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_persian_albert_persian_farsi_zwnj_base_v2_en_5.5.0_3.0_1725236729719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("qa_persian_albert_persian_farsi_zwnj_base_v2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("qa_persian_albert_persian_farsi_zwnj_base_v2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qa_persian_albert_persian_farsi_zwnj_base_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|41.9 MB| + +## References + +https://huggingface.co/makhataei/qa-persian-albert-fa-zwnj-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-qa_persian_albert_persian_farsi_zwnj_base_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-qa_persian_albert_persian_farsi_zwnj_base_v2_pipeline_en.md new file mode 100644 index 00000000000000..66b3aa49818770 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-qa_persian_albert_persian_farsi_zwnj_base_v2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English qa_persian_albert_persian_farsi_zwnj_base_v2_pipeline pipeline AlbertForQuestionAnswering from makhataei +author: John Snow Labs +name: qa_persian_albert_persian_farsi_zwnj_base_v2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_persian_albert_persian_farsi_zwnj_base_v2_pipeline` is a English model originally trained by makhataei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_persian_albert_persian_farsi_zwnj_base_v2_pipeline_en_5.5.0_3.0_1725236732434.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_persian_albert_persian_farsi_zwnj_base_v2_pipeline_en_5.5.0_3.0_1725236732434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("qa_persian_albert_persian_farsi_zwnj_base_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("qa_persian_albert_persian_farsi_zwnj_base_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qa_persian_albert_persian_farsi_zwnj_base_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|41.9 MB| + +## References + +https://huggingface.co/makhataei/qa-persian-albert-fa-zwnj-base-v2 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-qa_persian_farsi_mdeberta_v3_base_en.md b/docs/_posts/ahmedlone127/2024-09-02-qa_persian_farsi_mdeberta_v3_base_en.md new file mode 100644 index 00000000000000..d2299805be9e49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-qa_persian_farsi_mdeberta_v3_base_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English qa_persian_farsi_mdeberta_v3_base DeBertaForQuestionAnswering from makhataei +author: John Snow Labs +name: qa_persian_farsi_mdeberta_v3_base +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, deberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_persian_farsi_mdeberta_v3_base` is a English model originally trained by makhataei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_persian_farsi_mdeberta_v3_base_en_5.5.0_3.0_1725269609669.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_persian_farsi_mdeberta_v3_base_en_5.5.0_3.0_1725269609669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DeBertaForQuestionAnswering.pretrained("qa_persian_farsi_mdeberta_v3_base","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DeBertaForQuestionAnswering.pretrained("qa_persian_farsi_mdeberta_v3_base", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qa_persian_farsi_mdeberta_v3_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|795.2 MB| + +## References + +https://huggingface.co/makhataei/qa-fa-mdeberta-v3-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-qa_persian_farsi_mdeberta_v3_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-qa_persian_farsi_mdeberta_v3_base_pipeline_en.md new file mode 100644 index 00000000000000..400b23c5ee817b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-qa_persian_farsi_mdeberta_v3_base_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English qa_persian_farsi_mdeberta_v3_base_pipeline pipeline DeBertaForQuestionAnswering from makhataei +author: John Snow Labs +name: qa_persian_farsi_mdeberta_v3_base_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_persian_farsi_mdeberta_v3_base_pipeline` is a English model originally trained by makhataei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_persian_farsi_mdeberta_v3_base_pipeline_en_5.5.0_3.0_1725269765792.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_persian_farsi_mdeberta_v3_base_pipeline_en_5.5.0_3.0_1725269765792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("qa_persian_farsi_mdeberta_v3_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("qa_persian_farsi_mdeberta_v3_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qa_persian_farsi_mdeberta_v3_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|795.2 MB| + +## References + +https://huggingface.co/makhataei/qa-fa-mdeberta-v3-base + +## Included Models + +- MultiDocumentAssembler +- DeBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-qa_synth_data_with_unanswerable_28_aug_v1_en.md b/docs/_posts/ahmedlone127/2024-09-02-qa_synth_data_with_unanswerable_28_aug_v1_en.md new file mode 100644 index 00000000000000..e6d59f621c13a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-qa_synth_data_with_unanswerable_28_aug_v1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English qa_synth_data_with_unanswerable_28_aug_v1 XlmRoBertaForQuestionAnswering from am-infoweb +author: John Snow Labs +name: qa_synth_data_with_unanswerable_28_aug_v1 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synth_data_with_unanswerable_28_aug_v1` is a English model originally trained by am-infoweb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synth_data_with_unanswerable_28_aug_v1_en_5.5.0_3.0_1725253376514.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synth_data_with_unanswerable_28_aug_v1_en_5.5.0_3.0_1725253376514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_synth_data_with_unanswerable_28_aug_v1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_synth_data_with_unanswerable_28_aug_v1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qa_synth_data_with_unanswerable_28_aug_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|805.7 MB| + +## References + +https://huggingface.co/am-infoweb/QA_SYNTH_DATA_WITH_UNANSWERABLE_28_AUG_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-qa_synth_data_with_unanswerable_28_aug_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-qa_synth_data_with_unanswerable_28_aug_v1_pipeline_en.md new file mode 100644 index 00000000000000..dfcd40e41a3d44 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-qa_synth_data_with_unanswerable_28_aug_v1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English qa_synth_data_with_unanswerable_28_aug_v1_pipeline pipeline XlmRoBertaForQuestionAnswering from am-infoweb +author: John Snow Labs +name: qa_synth_data_with_unanswerable_28_aug_v1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synth_data_with_unanswerable_28_aug_v1_pipeline` is a English model originally trained by am-infoweb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synth_data_with_unanswerable_28_aug_v1_pipeline_en_5.5.0_3.0_1725253493535.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synth_data_with_unanswerable_28_aug_v1_pipeline_en_5.5.0_3.0_1725253493535.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("qa_synth_data_with_unanswerable_28_aug_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("qa_synth_data_with_unanswerable_28_aug_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qa_synth_data_with_unanswerable_28_aug_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|805.7 MB| + +## References + +https://huggingface.co/am-infoweb/QA_SYNTH_DATA_WITH_UNANSWERABLE_28_AUG_v1 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-query_classification_en.md b/docs/_posts/ahmedlone127/2024-09-02-query_classification_en.md new file mode 100644 index 00000000000000..7621a8ec433819 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-query_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English query_classification DistilBertForSequenceClassification from nullpointer-ind +author: John Snow Labs +name: query_classification +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`query_classification` is a English model originally trained by nullpointer-ind. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/query_classification_en_5.5.0_3.0_1725292004175.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/query_classification_en_5.5.0_3.0_1725292004175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("query_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("query_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|query_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/nullpointer-ind/Query-Classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-query_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-query_classification_pipeline_en.md new file mode 100644 index 00000000000000..ee150206ade0ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-query_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English query_classification_pipeline pipeline DistilBertForSequenceClassification from nullpointer-ind +author: John Snow Labs +name: query_classification_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`query_classification_pipeline` is a English model originally trained by nullpointer-ind. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/query_classification_pipeline_en_5.5.0_3.0_1725292017687.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/query_classification_pipeline_en_5.5.0_3.0_1725292017687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("query_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("query_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|query_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/nullpointer-ind/Query-Classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-query_quality_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-02-query_quality_classifier_en.md new file mode 100644 index 00000000000000..c4e2dfa77a6762 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-query_quality_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English query_quality_classifier AlbertForSequenceClassification from dejanseo +author: John Snow Labs +name: query_quality_classifier +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`query_quality_classifier` is a English model originally trained by dejanseo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/query_quality_classifier_en_5.5.0_3.0_1725278971492.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/query_quality_classifier_en_5.5.0_3.0_1725278971492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = AlbertForSequenceClassification.pretrained("query_quality_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("query_quality_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|query_quality_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/dejanseo/Query-Quality-Classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-query_quality_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-query_quality_classifier_pipeline_en.md new file mode 100644 index 00000000000000..422d1598705da6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-query_quality_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English query_quality_classifier_pipeline pipeline AlbertForSequenceClassification from dejanseo +author: John Snow Labs +name: query_quality_classifier_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`query_quality_classifier_pipeline` is a English model originally trained by dejanseo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/query_quality_classifier_pipeline_en_5.5.0_3.0_1725278973969.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/query_quality_classifier_pipeline_en_5.5.0_3.0_1725278973969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("query_quality_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("query_quality_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|query_quality_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/dejanseo/Query-Quality-Classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-radiology_report_english_chinese_ft_base_en.md b/docs/_posts/ahmedlone127/2024-09-02-radiology_report_english_chinese_ft_base_en.md new file mode 100644 index 00000000000000..447bff46414a94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-radiology_report_english_chinese_ft_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English radiology_report_english_chinese_ft_base MarianTransformer from sindri101 +author: John Snow Labs +name: radiology_report_english_chinese_ft_base +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`radiology_report_english_chinese_ft_base` is a English model originally trained by sindri101. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/radiology_report_english_chinese_ft_base_en_5.5.0_3.0_1725243029007.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/radiology_report_english_chinese_ft_base_en_5.5.0_3.0_1725243029007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("radiology_report_english_chinese_ft_base","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("radiology_report_english_chinese_ft_base","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|radiology_report_english_chinese_ft_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|540.7 MB| + +## References + +https://huggingface.co/sindri101/radiology-report-en-zh-ft-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-radiology_report_english_chinese_ft_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-radiology_report_english_chinese_ft_base_pipeline_en.md new file mode 100644 index 00000000000000..ba80d19be8fc9c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-radiology_report_english_chinese_ft_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English radiology_report_english_chinese_ft_base_pipeline pipeline MarianTransformer from sindri101 +author: John Snow Labs +name: radiology_report_english_chinese_ft_base_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`radiology_report_english_chinese_ft_base_pipeline` is a English model originally trained by sindri101. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/radiology_report_english_chinese_ft_base_pipeline_en_5.5.0_3.0_1725243057946.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/radiology_report_english_chinese_ft_base_pipeline_en_5.5.0_3.0_1725243057946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("radiology_report_english_chinese_ft_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("radiology_report_english_chinese_ft_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|radiology_report_english_chinese_ft_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|541.2 MB| + +## References + +https://huggingface.co/sindri101/radiology-report-en-zh-ft-base + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_pipeline_en.md new file mode 100644 index 00000000000000..002dff52409fcd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_pipeline pipeline XlmRoBertaForTokenClassification from ajtamayoh +author: John Snow Labs +name: re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_pipeline` is a English model originally trained by ajtamayoh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_pipeline_en_5.5.0_3.0_1725308312312.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_pipeline_en_5.5.0_3.0_1725308312312.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|848.2 MB| + +## References + +https://huggingface.co/ajtamayoh/RE_NegREF_NSD_Nubes_Training_Development_dataset_xlm_RoBERTa_base_fine_tuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-readabert_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-readabert_english_en.md new file mode 100644 index 00000000000000..cbfa493ac07cab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-readabert_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English readabert_english BertForSequenceClassification from tareknaous +author: John Snow Labs +name: readabert_english +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`readabert_english` is a English model originally trained by tareknaous. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/readabert_english_en_5.5.0_3.0_1725293898625.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/readabert_english_en_5.5.0_3.0_1725293898625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("readabert_english","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("readabert_english", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|readabert_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/tareknaous/readabert-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-readabert_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-readabert_english_pipeline_en.md new file mode 100644 index 00000000000000..94681b3a454282 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-readabert_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English readabert_english_pipeline pipeline BertForSequenceClassification from tareknaous +author: John Snow Labs +name: readabert_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`readabert_english_pipeline` is a English model originally trained by tareknaous. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/readabert_english_pipeline_en_5.5.0_3.0_1725293919569.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/readabert_english_pipeline_en_5.5.0_3.0_1725293919569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("readabert_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("readabert_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|readabert_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/tareknaous/readabert-en + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-reddit_left_en.md b/docs/_posts/ahmedlone127/2024-09-02-reddit_left_en.md new file mode 100644 index 00000000000000..fbc74870adddec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-reddit_left_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English reddit_left RoBertaEmbeddings from haleyej +author: John Snow Labs +name: reddit_left +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reddit_left` is a English model originally trained by haleyej. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reddit_left_en_5.5.0_3.0_1725265055547.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reddit_left_en_5.5.0_3.0_1725265055547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("reddit_left","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("reddit_left","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reddit_left| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|306.7 MB| + +## References + +https://huggingface.co/haleyej/reddit-left \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-reddit_left_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-reddit_left_pipeline_en.md new file mode 100644 index 00000000000000..8cfccaf0122cc6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-reddit_left_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English reddit_left_pipeline pipeline RoBertaEmbeddings from haleyej +author: John Snow Labs +name: reddit_left_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reddit_left_pipeline` is a English model originally trained by haleyej. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reddit_left_pipeline_en_5.5.0_3.0_1725265072454.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reddit_left_pipeline_en_5.5.0_3.0_1725265072454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("reddit_left_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("reddit_left_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reddit_left_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|306.7 MB| + +## References + +https://huggingface.co/haleyej/reddit-left + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-reduplication_repetition_xlmr_v2_hi.md b/docs/_posts/ahmedlone127/2024-09-02-reduplication_repetition_xlmr_v2_hi.md new file mode 100644 index 00000000000000..63d2c06704c920 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-reduplication_repetition_xlmr_v2_hi.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Hindi reduplication_repetition_xlmr_v2 XlmRoBertaForTokenClassification from theArif +author: John Snow Labs +name: reduplication_repetition_xlmr_v2 +date: 2024-09-02 +tags: [hi, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: hi +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reduplication_repetition_xlmr_v2` is a Hindi model originally trained by theArif. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reduplication_repetition_xlmr_v2_hi_5.5.0_3.0_1725317908148.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reduplication_repetition_xlmr_v2_hi_5.5.0_3.0_1725317908148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("reduplication_repetition_xlmr_v2","hi") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("reduplication_repetition_xlmr_v2", "hi") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reduplication_repetition_xlmr_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|hi| +|Size:|790.9 MB| + +## References + +https://huggingface.co/theArif/reduplication-repetition-xlmr-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-reduplication_repetition_xlmr_v2_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-02-reduplication_repetition_xlmr_v2_pipeline_hi.md new file mode 100644 index 00000000000000..9456624f6f6de6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-reduplication_repetition_xlmr_v2_pipeline_hi.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Hindi reduplication_repetition_xlmr_v2_pipeline pipeline XlmRoBertaForTokenClassification from theArif +author: John Snow Labs +name: reduplication_repetition_xlmr_v2_pipeline +date: 2024-09-02 +tags: [hi, open_source, pipeline, onnx] +task: Named Entity Recognition +language: hi +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reduplication_repetition_xlmr_v2_pipeline` is a Hindi model originally trained by theArif. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reduplication_repetition_xlmr_v2_pipeline_hi_5.5.0_3.0_1725318035291.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reduplication_repetition_xlmr_v2_pipeline_hi_5.5.0_3.0_1725318035291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("reduplication_repetition_xlmr_v2_pipeline", lang = "hi") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("reduplication_repetition_xlmr_v2_pipeline", lang = "hi") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reduplication_repetition_xlmr_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|hi| +|Size:|790.9 MB| + +## References + +https://huggingface.co/theArif/reduplication-repetition-xlmr-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-refpydst_1p_referredstates_split_v1_en.md b/docs/_posts/ahmedlone127/2024-09-02-refpydst_1p_referredstates_split_v1_en.md new file mode 100644 index 00000000000000..6de34b5f11faec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-refpydst_1p_referredstates_split_v1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English refpydst_1p_referredstates_split_v1 MPNetEmbeddings from Brendan +author: John Snow Labs +name: refpydst_1p_referredstates_split_v1 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`refpydst_1p_referredstates_split_v1` is a English model originally trained by Brendan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/refpydst_1p_referredstates_split_v1_en_5.5.0_3.0_1725280486460.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/refpydst_1p_referredstates_split_v1_en_5.5.0_3.0_1725280486460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("refpydst_1p_referredstates_split_v1","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("refpydst_1p_referredstates_split_v1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|refpydst_1p_referredstates_split_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/Brendan/refpydst-1p-referredstates-split-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-refpydst_1p_referredstates_split_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-refpydst_1p_referredstates_split_v1_pipeline_en.md new file mode 100644 index 00000000000000..cd907f7539d120 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-refpydst_1p_referredstates_split_v1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English refpydst_1p_referredstates_split_v1_pipeline pipeline MPNetEmbeddings from Brendan +author: John Snow Labs +name: refpydst_1p_referredstates_split_v1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`refpydst_1p_referredstates_split_v1_pipeline` is a English model originally trained by Brendan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/refpydst_1p_referredstates_split_v1_pipeline_en_5.5.0_3.0_1725280507991.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/refpydst_1p_referredstates_split_v1_pipeline_en_5.5.0_3.0_1725280507991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("refpydst_1p_referredstates_split_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("refpydst_1p_referredstates_split_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|refpydst_1p_referredstates_split_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/Brendan/refpydst-1p-referredstates-split-v1 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-refpydst_1p_referredstates_split_v3_en.md b/docs/_posts/ahmedlone127/2024-09-02-refpydst_1p_referredstates_split_v3_en.md new file mode 100644 index 00000000000000..2acfbda083c2e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-refpydst_1p_referredstates_split_v3_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English refpydst_1p_referredstates_split_v3 MPNetEmbeddings from Brendan +author: John Snow Labs +name: refpydst_1p_referredstates_split_v3 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`refpydst_1p_referredstates_split_v3` is a English model originally trained by Brendan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/refpydst_1p_referredstates_split_v3_en_5.5.0_3.0_1725313795811.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/refpydst_1p_referredstates_split_v3_en_5.5.0_3.0_1725313795811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("refpydst_1p_referredstates_split_v3","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("refpydst_1p_referredstates_split_v3","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|refpydst_1p_referredstates_split_v3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/Brendan/refpydst-1p-referredstates-split-v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-refpydst_1p_referredstates_split_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-refpydst_1p_referredstates_split_v3_pipeline_en.md new file mode 100644 index 00000000000000..40abf043de2d1a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-refpydst_1p_referredstates_split_v3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English refpydst_1p_referredstates_split_v3_pipeline pipeline MPNetEmbeddings from Brendan +author: John Snow Labs +name: refpydst_1p_referredstates_split_v3_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`refpydst_1p_referredstates_split_v3_pipeline` is a English model originally trained by Brendan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/refpydst_1p_referredstates_split_v3_pipeline_en_5.5.0_3.0_1725313816904.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/refpydst_1p_referredstates_split_v3_pipeline_en_5.5.0_3.0_1725313816904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("refpydst_1p_referredstates_split_v3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("refpydst_1p_referredstates_split_v3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|refpydst_1p_referredstates_split_v3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/Brendan/refpydst-1p-referredstates-split-v3 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-reviews_roberta_base_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-02-reviews_roberta_base_sentiment_analysis_en.md new file mode 100644 index 00000000000000..8f2e86624a4f94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-reviews_roberta_base_sentiment_analysis_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English reviews_roberta_base_sentiment_analysis RoBertaForSequenceClassification from AnkitAI +author: John Snow Labs +name: reviews_roberta_base_sentiment_analysis +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reviews_roberta_base_sentiment_analysis` is a English model originally trained by AnkitAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reviews_roberta_base_sentiment_analysis_en_5.5.0_3.0_1725238603902.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reviews_roberta_base_sentiment_analysis_en_5.5.0_3.0_1725238603902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("reviews_roberta_base_sentiment_analysis","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("reviews_roberta_base_sentiment_analysis", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reviews_roberta_base_sentiment_analysis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.2 MB| + +## References + +https://huggingface.co/AnkitAI/reviews-roberta-base-sentiment-analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-reviews_roberta_base_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-reviews_roberta_base_sentiment_analysis_pipeline_en.md new file mode 100644 index 00000000000000..a6dbfd05a968b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-reviews_roberta_base_sentiment_analysis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English reviews_roberta_base_sentiment_analysis_pipeline pipeline RoBertaForSequenceClassification from AnkitAI +author: John Snow Labs +name: reviews_roberta_base_sentiment_analysis_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reviews_roberta_base_sentiment_analysis_pipeline` is a English model originally trained by AnkitAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reviews_roberta_base_sentiment_analysis_pipeline_en_5.5.0_3.0_1725238627812.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reviews_roberta_base_sentiment_analysis_pipeline_en_5.5.0_3.0_1725238627812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("reviews_roberta_base_sentiment_analysis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("reviews_roberta_base_sentiment_analysis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reviews_roberta_base_sentiment_analysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.2 MB| + +## References + +https://huggingface.co/AnkitAI/reviews-roberta-base-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-reward_deberta_v3_large_aspect_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-reward_deberta_v3_large_aspect_pipeline_xx.md new file mode 100644 index 00000000000000..5bd76870d63fab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-reward_deberta_v3_large_aspect_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual reward_deberta_v3_large_aspect_pipeline pipeline DeBertaForSequenceClassification from theblackcat102 +author: John Snow Labs +name: reward_deberta_v3_large_aspect_pipeline +date: 2024-09-02 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reward_deberta_v3_large_aspect_pipeline` is a Multilingual model originally trained by theblackcat102. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reward_deberta_v3_large_aspect_pipeline_xx_5.5.0_3.0_1725282119939.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reward_deberta_v3_large_aspect_pipeline_xx_5.5.0_3.0_1725282119939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("reward_deberta_v3_large_aspect_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("reward_deberta_v3_large_aspect_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reward_deberta_v3_large_aspect_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|1.0 GB| + +## References + +https://huggingface.co/theblackcat102/reward-deberta-v3-large-aspect + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-robbert_2023_dutch_base_nl.md b/docs/_posts/ahmedlone127/2024-09-02-robbert_2023_dutch_base_nl.md new file mode 100644 index 00000000000000..145e13de3b9d5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-robbert_2023_dutch_base_nl.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Dutch, Flemish robbert_2023_dutch_base RoBertaEmbeddings from DTAI-KULeuven +author: John Snow Labs +name: robbert_2023_dutch_base +date: 2024-09-02 +tags: [nl, open_source, onnx, embeddings, roberta] +task: Embeddings +language: nl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_2023_dutch_base` is a Dutch, Flemish model originally trained by DTAI-KULeuven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_base_nl_5.5.0_3.0_1725264394868.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_base_nl_5.5.0_3.0_1725264394868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("robbert_2023_dutch_base","nl") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("robbert_2023_dutch_base","nl") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|robbert_2023_dutch_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|nl| +|Size:|464.8 MB| + +## References + +https://huggingface.co/DTAI-KULeuven/robbert-2023-dutch-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-robbert_2023_dutch_base_pipeline_nl.md b/docs/_posts/ahmedlone127/2024-09-02-robbert_2023_dutch_base_pipeline_nl.md new file mode 100644 index 00000000000000..70414e918ab95a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-robbert_2023_dutch_base_pipeline_nl.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Dutch, Flemish robbert_2023_dutch_base_pipeline pipeline RoBertaEmbeddings from DTAI-KULeuven +author: John Snow Labs +name: robbert_2023_dutch_base_pipeline +date: 2024-09-02 +tags: [nl, open_source, pipeline, onnx] +task: Embeddings +language: nl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_2023_dutch_base_pipeline` is a Dutch, Flemish model originally trained by DTAI-KULeuven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_base_pipeline_nl_5.5.0_3.0_1725264419722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_base_pipeline_nl_5.5.0_3.0_1725264419722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("robbert_2023_dutch_base_pipeline", lang = "nl") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("robbert_2023_dutch_base_pipeline", lang = "nl") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|robbert_2023_dutch_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|nl| +|Size:|464.8 MB| + +## References + +https://huggingface.co/DTAI-KULeuven/robbert-2023-dutch-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-robbert_2023_dutch_large_nl.md b/docs/_posts/ahmedlone127/2024-09-02-robbert_2023_dutch_large_nl.md new file mode 100644 index 00000000000000..e5a02cfa32df99 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-robbert_2023_dutch_large_nl.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Dutch, Flemish robbert_2023_dutch_large RoBertaEmbeddings from DTAI-KULeuven +author: John Snow Labs +name: robbert_2023_dutch_large +date: 2024-09-02 +tags: [nl, open_source, onnx, embeddings, roberta] +task: Embeddings +language: nl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_2023_dutch_large` is a Dutch, Flemish model originally trained by DTAI-KULeuven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_large_nl_5.5.0_3.0_1725264666306.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_large_nl_5.5.0_3.0_1725264666306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("robbert_2023_dutch_large","nl") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("robbert_2023_dutch_large","nl") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|robbert_2023_dutch_large| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|nl| +|Size:|1.3 GB| + +## References + +https://huggingface.co/DTAI-KULeuven/robbert-2023-dutch-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-robbert_2023_dutch_large_pipeline_nl.md b/docs/_posts/ahmedlone127/2024-09-02-robbert_2023_dutch_large_pipeline_nl.md new file mode 100644 index 00000000000000..565c6eb75885f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-robbert_2023_dutch_large_pipeline_nl.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Dutch, Flemish robbert_2023_dutch_large_pipeline pipeline RoBertaEmbeddings from DTAI-KULeuven +author: John Snow Labs +name: robbert_2023_dutch_large_pipeline +date: 2024-09-02 +tags: [nl, open_source, pipeline, onnx] +task: Embeddings +language: nl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_2023_dutch_large_pipeline` is a Dutch, Flemish model originally trained by DTAI-KULeuven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_large_pipeline_nl_5.5.0_3.0_1725264735529.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_large_pipeline_nl_5.5.0_3.0_1725264735529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("robbert_2023_dutch_large_pipeline", lang = "nl") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("robbert_2023_dutch_large_pipeline", lang = "nl") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|robbert_2023_dutch_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|nl| +|Size:|1.3 GB| + +## References + +https://huggingface.co/DTAI-KULeuven/robbert-2023-dutch-large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta22_model_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta22_model_en.md new file mode 100644 index 00000000000000..f23237f6f5a8be --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta22_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta22_model RoBertaForSequenceClassification from abdulrahman4111 +author: John Snow Labs +name: roberta22_model +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta22_model` is a English model originally trained by abdulrahman4111. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta22_model_en_5.5.0_3.0_1725277721303.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta22_model_en_5.5.0_3.0_1725277721303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta22_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta22_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta22_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|425.3 MB| + +## References + +https://huggingface.co/abdulrahman4111/roberta22-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta22_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta22_model_pipeline_en.md new file mode 100644 index 00000000000000..69609ac27fb525 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta22_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta22_model_pipeline pipeline RoBertaForSequenceClassification from abdulrahman4111 +author: John Snow Labs +name: roberta22_model_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta22_model_pipeline` is a English model originally trained by abdulrahman4111. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta22_model_pipeline_en_5.5.0_3.0_1725277750804.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta22_model_pipeline_en_5.5.0_3.0_1725277750804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta22_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta22_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta22_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|425.3 MB| + +## References + +https://huggingface.co/abdulrahman4111/roberta22-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_base_facebookai_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_facebookai_en.md new file mode 100644 index 00000000000000..15941c104aece1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_facebookai_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_facebookai RoBertaEmbeddings from FacebookAI +author: John Snow Labs +name: roberta_base_facebookai +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_facebookai` is a English model originally trained by FacebookAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_facebookai_en_5.5.0_3.0_1725264643077.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_facebookai_en_5.5.0_3.0_1725264643077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("roberta_base_facebookai","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("roberta_base_facebookai","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_facebookai| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|298.2 MB| + +## References + +https://huggingface.co/FacebookAI/roberta-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_base_facebookai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_facebookai_pipeline_en.md new file mode 100644 index 00000000000000..9edc4cf6541c73 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_facebookai_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_facebookai_pipeline pipeline RoBertaEmbeddings from FacebookAI +author: John Snow Labs +name: roberta_base_facebookai_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_facebookai_pipeline` is a English model originally trained by FacebookAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_facebookai_pipeline_en_5.5.0_3.0_1725264734025.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_facebookai_pipeline_en_5.5.0_3.0_1725264734025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_facebookai_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_facebookai_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_facebookai_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|298.2 MB| + +## References + +https://huggingface.co/FacebookAI/roberta-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_en.md new file mode 100644 index 00000000000000..e06f9708184064 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset RoBertaForSequenceClassification from abdiharyadi +author: John Snow Labs +name: roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset` is a English model originally trained by abdiharyadi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_en_5.5.0_3.0_1725238113897.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_en_5.5.0_3.0_1725238113897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|473.0 MB| + +## References + +https://huggingface.co/abdiharyadi/roberta-base-indonesian-522M-with-sa-william-dataset \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_pipeline_en.md new file mode 100644 index 00000000000000..17e02d109ee54e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_pipeline pipeline RoBertaForSequenceClassification from abdiharyadi +author: John Snow Labs +name: roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_pipeline` is a English model originally trained by abdiharyadi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_pipeline_en_5.5.0_3.0_1725238141592.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_pipeline_en_5.5.0_3.0_1725238141592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_indonesian_522m_with_sanskrit_saskta_william_dataset_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|473.0 MB| + +## References + +https://huggingface.co/abdiharyadi/roberta-base-indonesian-522M-with-sa-william-dataset + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_base_nepali_ne.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_nepali_ne.md new file mode 100644 index 00000000000000..16a4637c503203 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_nepali_ne.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Nepali (macrolanguage) roberta_base_nepali RoBertaEmbeddings from amitness +author: John Snow Labs +name: roberta_base_nepali +date: 2024-09-02 +tags: [ne, open_source, onnx, embeddings, roberta] +task: Embeddings +language: ne +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_nepali` is a Nepali (macrolanguage) model originally trained by amitness. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_nepali_ne_5.5.0_3.0_1725264502063.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_nepali_ne_5.5.0_3.0_1725264502063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("roberta_base_nepali","ne") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("roberta_base_nepali","ne") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_nepali| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|ne| +|Size:|311.9 MB| + +## References + +https://huggingface.co/amitness/roberta-base-ne \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_base_on_cuad_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_on_cuad_finetuned_squad_en.md new file mode 100644 index 00000000000000..082ce195c7563e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_on_cuad_finetuned_squad_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_base_on_cuad_finetuned_squad RoBertaForQuestionAnswering from ygory +author: John Snow Labs +name: roberta_base_on_cuad_finetuned_squad +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_on_cuad_finetuned_squad` is a English model originally trained by ygory. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_on_cuad_finetuned_squad_en_5.5.0_3.0_1725252140419.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_on_cuad_finetuned_squad_en_5.5.0_3.0_1725252140419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_on_cuad_finetuned_squad","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_on_cuad_finetuned_squad", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_on_cuad_finetuned_squad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|454.2 MB| + +## References + +https://huggingface.co/ygory/roberta-base-on-cuad-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_base_on_cuad_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_on_cuad_finetuned_squad_pipeline_en.md new file mode 100644 index 00000000000000..daf0bc16336464 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_on_cuad_finetuned_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_base_on_cuad_finetuned_squad_pipeline pipeline RoBertaForQuestionAnswering from ygory +author: John Snow Labs +name: roberta_base_on_cuad_finetuned_squad_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_on_cuad_finetuned_squad_pipeline` is a English model originally trained by ygory. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_on_cuad_finetuned_squad_pipeline_en_5.5.0_3.0_1725252165940.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_on_cuad_finetuned_squad_pipeline_en_5.5.0_3.0_1725252165940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_on_cuad_finetuned_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_on_cuad_finetuned_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_on_cuad_finetuned_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|454.2 MB| + +## References + +https://huggingface.co/ygory/roberta-base-on-cuad-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_base_suicide_prediction_phr_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_suicide_prediction_phr_v2_en.md new file mode 100644 index 00000000000000..293df0677181d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_suicide_prediction_phr_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_suicide_prediction_phr_v2 RoBertaForSequenceClassification from vibhorag101 +author: John Snow Labs +name: roberta_base_suicide_prediction_phr_v2 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_suicide_prediction_phr_v2` is a English model originally trained by vibhorag101. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_suicide_prediction_phr_v2_en_5.5.0_3.0_1725277003275.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_suicide_prediction_phr_v2_en_5.5.0_3.0_1725277003275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_suicide_prediction_phr_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_suicide_prediction_phr_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_suicide_prediction_phr_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|464.0 MB| + +## References + +https://huggingface.co/vibhorag101/roberta-base-suicide-prediction-phr-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_fever_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_fever_en.md new file mode 100644 index 00000000000000..bcd69f132e475b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_fever_en.md @@ -0,0 +1,104 @@ +--- +layout: model +title: English RoBertaForSequenceClassification Cased model (from stanleychu2) +author: John Snow Labs +name: roberta_classifier_fever +date: 2024-09-02 +tags: [en, open_source, roberta, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-fever` is a English model originally trained by `stanleychu2`. + +## Predicted Entities + +`1`, `0` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_fever_en_5.5.0_3.0_1725237840722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_fever_en_5.5.0_3.0_1725237840722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_fever","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_fever","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.roberta.fever.").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_fever| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.6 MB| + +## References + +References + +- https://huggingface.co/stanleychu2/roberta-fever \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_fever_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_fever_pipeline_en.md new file mode 100644 index 00000000000000..3ced61f1ac88e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_fever_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_classifier_fever_pipeline pipeline RoBertaForSequenceClassification from stanleychu2 +author: John Snow Labs +name: roberta_classifier_fever_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classifier_fever_pipeline` is a English model originally trained by stanleychu2. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_fever_pipeline_en_5.5.0_3.0_1725237865763.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_fever_pipeline_en_5.5.0_3.0_1725237865763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_classifier_fever_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_classifier_fever_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_fever_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.6 MB| + +## References + +https://huggingface.co/stanleychu2/roberta-fever + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_financial_large_sentiment_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_financial_large_sentiment_en.md new file mode 100644 index 00000000000000..b805021b7b71d8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_financial_large_sentiment_en.md @@ -0,0 +1,105 @@ +--- +layout: model +title: English RoBertaForSequenceClassification Large Cased model (from soleimanian) +author: John Snow Labs +name: roberta_classifier_financial_large_sentiment +date: 2024-09-02 +tags: [en, open_source, roberta, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `financial-roberta-large-sentiment` is a English model originally trained by `soleimanian`. + +## Predicted Entities + +`neutral`, `negative`, `positive` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_financial_large_sentiment_en_5.5.0_3.0_1725238637650.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_financial_large_sentiment_en_5.5.0_3.0_1725238637650.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_financial_large_sentiment","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_financial_large_sentiment","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.roberta.sentiment.large.by_soleimanian").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_financial_large_sentiment| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +References + +- https://huggingface.co/soleimanian/financial-roberta-large-sentiment +- https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4115943 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_financial_large_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_financial_large_sentiment_pipeline_en.md new file mode 100644 index 00000000000000..fe41a4cfd27387 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_financial_large_sentiment_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_classifier_financial_large_sentiment_pipeline pipeline RoBertaForSequenceClassification from soleimanian +author: John Snow Labs +name: roberta_classifier_financial_large_sentiment_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classifier_financial_large_sentiment_pipeline` is a English model originally trained by soleimanian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_financial_large_sentiment_pipeline_en_5.5.0_3.0_1725238704828.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_financial_large_sentiment_pipeline_en_5.5.0_3.0_1725238704828.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_classifier_financial_large_sentiment_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_classifier_financial_large_sentiment_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_financial_large_sentiment_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/soleimanian/financial-roberta-large-sentiment + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_sentiment_analysis_custom_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_sentiment_analysis_custom_en.md new file mode 100644 index 00000000000000..b7b4501bedd960 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_sentiment_analysis_custom_en.md @@ -0,0 +1,104 @@ +--- +layout: model +title: English RoBertaForSequenceClassification Cased model (from acho0057) +author: John Snow Labs +name: roberta_classifier_sentiment_analysis_custom +date: 2024-09-02 +tags: [en, open_source, roberta, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `sentiment_analysis_custom` is a English model originally trained by `acho0057`. + +## Predicted Entities + +`Negative`, `Positive`, `Neutral` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_sentiment_analysis_custom_en_5.5.0_3.0_1725277347682.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_sentiment_analysis_custom_en_5.5.0_3.0_1725277347682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_sentiment_analysis_custom","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_sentiment_analysis_custom","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.roberta.sentiment.by_acho0057").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_sentiment_analysis_custom| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.3 MB| + +## References + +References + +- https://huggingface.co/acho0057/sentiment_analysis_custom \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_sentiment_analysis_custom_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_sentiment_analysis_custom_pipeline_en.md new file mode 100644 index 00000000000000..4c21199821c91a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_sentiment_analysis_custom_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_classifier_sentiment_analysis_custom_pipeline pipeline RoBertaForSequenceClassification from acho0057 +author: John Snow Labs +name: roberta_classifier_sentiment_analysis_custom_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classifier_sentiment_analysis_custom_pipeline` is a English model originally trained by acho0057. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_sentiment_analysis_custom_pipeline_en_5.5.0_3.0_1725277372904.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_sentiment_analysis_custom_pipeline_en_5.5.0_3.0_1725277372904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_classifier_sentiment_analysis_custom_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_classifier_sentiment_analysis_custom_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_sentiment_analysis_custom_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/acho0057/sentiment_analysis_custom + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_tweet_sentiment_eval_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_tweet_sentiment_eval_en.md new file mode 100644 index 00000000000000..e97c1234a13b5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_tweet_sentiment_eval_en.md @@ -0,0 +1,104 @@ +--- +layout: model +title: English RobertaForSequenceClassification Cased model (from elozano) +author: John Snow Labs +name: roberta_classifier_tweet_sentiment_eval +date: 2024-09-02 +tags: [en, open_source, roberta, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tweet_sentiment_eval` is a English model originally trained by `elozano`. + +## Predicted Entities + +`Positive`, `Neutral`, `Negative` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_tweet_sentiment_eval_en_5.5.0_3.0_1725237798268.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_tweet_sentiment_eval_en_5.5.0_3.0_1725237798268.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_tweet_sentiment_eval","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_tweet_sentiment_eval","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.roberta.tweet_sentiment.").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_tweet_sentiment_eval| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|460.4 MB| + +## References + +References + +- https://huggingface.co/elozano/tweet_sentiment_eval \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_tweet_sentiment_eval_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_tweet_sentiment_eval_pipeline_en.md new file mode 100644 index 00000000000000..3c24322d7485a3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_tweet_sentiment_eval_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_classifier_tweet_sentiment_eval_pipeline pipeline RoBertaForSequenceClassification from elozano +author: John Snow Labs +name: roberta_classifier_tweet_sentiment_eval_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classifier_tweet_sentiment_eval_pipeline` is a English model originally trained by elozano. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_tweet_sentiment_eval_pipeline_en_5.5.0_3.0_1725237823812.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_tweet_sentiment_eval_pipeline_en_5.5.0_3.0_1725237823812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_classifier_tweet_sentiment_eval_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_classifier_tweet_sentiment_eval_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_tweet_sentiment_eval_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|460.4 MB| + +## References + +https://huggingface.co/elozano/tweet_sentiment_eval + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_en.md new file mode 100644 index 00000000000000..ff7e7566a0fa4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_en.md @@ -0,0 +1,104 @@ +--- +layout: model +title: English RoBertaForSequenceClassification Base Cased model (from lucaordronneau) +author: John Snow Labs +name: roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news +date: 2024-09-02 +tags: [en, open_source, roberta, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `twitter-roberta-base-sentiment-latest-finetuned-FG-SINGLE_SENTENCE-NEWS` is a English model originally trained by `lucaordronneau`. + +## Predicted Entities + +`neutral`, `greed`, `fear` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_en_5.5.0_3.0_1725237935975.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_en_5.5.0_3.0_1725237935975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.roberta.news_sentiment_twitter.base_finetuned").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.3 MB| + +## References + +References + +- https://huggingface.co/lucaordronneau/twitter-roberta-base-sentiment-latest-finetuned-FG-SINGLE_SENTENCE-NEWS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_pipeline_en.md new file mode 100644 index 00000000000000..0226a8b9ba3844 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_pipeline pipeline RoBertaForSequenceClassification from lucaordronneau +author: John Snow Labs +name: roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_pipeline` is a English model originally trained by lucaordronneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_pipeline_en_5.5.0_3.0_1725237965022.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_pipeline_en_5.5.0_3.0_1725237965022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_twitter_base_sentiment_latest_finetuned_fg_single_sentence_news_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/lucaordronneau/twitter-roberta-base-sentiment-latest-finetuned-FG-SINGLE_SENTENCE-NEWS + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_classweight_sentiment_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_classweight_sentiment_classifier_en.md new file mode 100644 index 00000000000000..b8c0c4ef3aec65 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_classweight_sentiment_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_classweight_sentiment_classifier RoBertaForSequenceClassification from gArthur98 +author: John Snow Labs +name: roberta_classweight_sentiment_classifier +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classweight_sentiment_classifier` is a English model originally trained by gArthur98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classweight_sentiment_classifier_en_5.5.0_3.0_1725277926245.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classweight_sentiment_classifier_en_5.5.0_3.0_1725277926245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_classweight_sentiment_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_classweight_sentiment_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classweight_sentiment_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|435.7 MB| + +## References + +https://huggingface.co/gArthur98/Roberta-classweight-Sentiment-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_classweight_sentiment_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_classweight_sentiment_classifier_pipeline_en.md new file mode 100644 index 00000000000000..66dc2ce12d2079 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_classweight_sentiment_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_classweight_sentiment_classifier_pipeline pipeline RoBertaForSequenceClassification from gArthur98 +author: John Snow Labs +name: roberta_classweight_sentiment_classifier_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classweight_sentiment_classifier_pipeline` is a English model originally trained by gArthur98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classweight_sentiment_classifier_pipeline_en_5.5.0_3.0_1725277952897.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classweight_sentiment_classifier_pipeline_en_5.5.0_3.0_1725277952897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_classweight_sentiment_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_classweight_sentiment_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classweight_sentiment_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|435.7 MB| + +## References + +https://huggingface.co/gArthur98/Roberta-classweight-Sentiment-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_daigt_kaggle_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_daigt_kaggle_en.md new file mode 100644 index 00000000000000..47a5f2ccfc9051 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_daigt_kaggle_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_daigt_kaggle RoBertaForSequenceClassification from zeyadusf +author: John Snow Labs +name: roberta_daigt_kaggle +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_daigt_kaggle` is a English model originally trained by zeyadusf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_daigt_kaggle_en_5.5.0_3.0_1725237913399.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_daigt_kaggle_en_5.5.0_3.0_1725237913399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_daigt_kaggle","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_daigt_kaggle", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_daigt_kaggle| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|457.2 MB| + +## References + +https://huggingface.co/zeyadusf/roberta-DAIGT-kaggle \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_daigt_kaggle_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_daigt_kaggle_pipeline_en.md new file mode 100644 index 00000000000000..1603a1a7889926 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_daigt_kaggle_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_daigt_kaggle_pipeline pipeline RoBertaForSequenceClassification from zeyadusf +author: John Snow Labs +name: roberta_daigt_kaggle_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_daigt_kaggle_pipeline` is a English model originally trained by zeyadusf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_daigt_kaggle_pipeline_en_5.5.0_3.0_1725237940458.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_daigt_kaggle_pipeline_en_5.5.0_3.0_1725237940458.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_daigt_kaggle_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_daigt_kaggle_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_daigt_kaggle_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|457.2 MB| + +## References + +https://huggingface.co/zeyadusf/roberta-DAIGT-kaggle + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_embeddings_legal_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_embeddings_legal_roberta_base_en.md new file mode 100644 index 00000000000000..8c4bc8b72886f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_embeddings_legal_roberta_base_en.md @@ -0,0 +1,108 @@ +--- +layout: model +title: English Legal RoBERTa Embeddings (CaseLaw, Base, Cased) +author: John Snow Labs +name: roberta_embeddings_legal_roberta_base +date: 2024-09-02 +tags: [roberta, embeddings, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Legal RoBERTa Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. `legal-roberta-base` is a English model orginally trained by `saibo`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_embeddings_legal_roberta_base_en_5.5.0_3.0_1725264385593.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_embeddings_legal_roberta_base_en_5.5.0_3.0_1725264385593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ +.setInputCol("text") \ +.setOutputCol("document") + +tokenizer = Tokenizer() \ +.setInputCols("document") \ +.setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_legal_roberta_base","en") \ +.setInputCols(["document", "token"]) \ +.setOutputCol("embeddings") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings]) + +data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() +.setInputCol("text") +.setOutputCol("document") + +val tokenizer = new Tokenizer() +.setInputCols(Array("document")) +.setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_legal_roberta_base","en") +.setInputCols(Array("document", "token")) +.setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) + +val data = Seq("I love Spark NLP").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.embed.legal_roberta_base").predict("""I love Spark NLP""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_embeddings_legal_roberta_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|466.0 MB| + +## References + +References + +- https://huggingface.co/saibo/legal-roberta-base +- https://www.kaggle.com/uspto/patent-litigations +- https://case.law/ +- https://www.kaggle.com/bigquery/patents +- https://www.kaggle.com/sohier/beyond-queries-exploring-the-bigquery-api \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_embeddings_roberta_large_bne_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_embeddings_roberta_large_bne_es.md new file mode 100644 index 00000000000000..9c265e0a5709af --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_embeddings_roberta_large_bne_es.md @@ -0,0 +1,110 @@ +--- +layout: model +title: Spanish RoBERTa Embeddings (Large) +author: John Snow Labs +name: roberta_embeddings_roberta_large_bne +date: 2024-09-02 +tags: [roberta, embeddings, es, open_source, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBERTa Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. `roberta-large-bne` is a Spanish model orginally trained by `PlanTL-GOB-ES`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_embeddings_roberta_large_bne_es_5.5.0_3.0_1725265428913.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_embeddings_roberta_large_bne_es_5.5.0_3.0_1725265428913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ +.setInputCol("text") \ +.setOutputCol("document") + +tokenizer = Tokenizer() \ +.setInputCols("document") \ +.setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_roberta_large_bne","es") \ +.setInputCols(["document", "token"]) \ +.setOutputCol("embeddings") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings]) + +data = spark.createDataFrame([["Me encanta chispa nlp"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() +.setInputCol("text") +.setOutputCol("document") + +val tokenizer = new Tokenizer() +.setInputCols(Array("document")) +.setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_roberta_large_bne","es") +.setInputCols(Array("document", "token")) +.setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) + +val data = Seq("Me encanta chispa nlp").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("es.embed.roberta_large_bne").predict("""Me encanta chispa nlp""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_embeddings_roberta_large_bne| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|es| +|Size:|843.3 MB| + +## References + +References + +- https://huggingface.co/PlanTL-GOB-ES/roberta-large-bne +- https://arxiv.org/abs/1907.11692 +- http://www.bne.es/en/Inicio/index.html +- http://www.bne.es/en/Inicio/index.html +- https://arxiv.org/abs/1907.11692 +- https://github.com/PlanTL-GOB-ES/lm-spanish +- https://arxiv.org/abs/2107.07253 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_embeddings_roberta_large_bne_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_embeddings_roberta_large_bne_pipeline_es.md new file mode 100644 index 00000000000000..4ec9cdf0640a7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_embeddings_roberta_large_bne_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish roberta_embeddings_roberta_large_bne_pipeline pipeline RoBertaEmbeddings from PlanTL-GOB-ES +author: John Snow Labs +name: roberta_embeddings_roberta_large_bne_pipeline +date: 2024-09-02 +tags: [es, open_source, pipeline, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_embeddings_roberta_large_bne_pipeline` is a Castilian, Spanish model originally trained by PlanTL-GOB-ES. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_embeddings_roberta_large_bne_pipeline_es_5.5.0_3.0_1725265674189.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_embeddings_roberta_large_bne_pipeline_es_5.5.0_3.0_1725265674189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_embeddings_roberta_large_bne_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_embeddings_roberta_large_bne_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_embeddings_roberta_large_bne_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|843.3 MB| + +## References + +https://huggingface.co/PlanTL-GOB-ES/roberta-large-bne + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_large_bne_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_bne_pipeline_es.md new file mode 100644 index 00000000000000..940d66b9049fac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_bne_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish roberta_large_bne_pipeline pipeline RoBertaEmbeddings from BSC-LT +author: John Snow Labs +name: roberta_large_bne_pipeline +date: 2024-09-02 +tags: [es, open_source, pipeline, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_bne_pipeline` is a Castilian, Spanish model originally trained by BSC-LT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_bne_pipeline_es_5.5.0_3.0_1725264559182.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_bne_pipeline_es_5.5.0_3.0_1725264559182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_bne_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_bne_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_bne_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|843.3 MB| + +## References + +https://huggingface.co/BSC-LT/roberta-large-bne + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_large_cola_krishna2020_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_cola_krishna2020_en.md new file mode 100644 index 00000000000000..7d3fb76dfd5a1b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_cola_krishna2020_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_large_cola_krishna2020 RoBertaForSequenceClassification from cointegrated +author: John Snow Labs +name: roberta_large_cola_krishna2020 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_cola_krishna2020` is a English model originally trained by cointegrated. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_cola_krishna2020_en_5.5.0_3.0_1725278319550.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_cola_krishna2020_en_5.5.0_3.0_1725278319550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_cola_krishna2020","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_cola_krishna2020", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_cola_krishna2020| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|845.3 MB| + +## References + +https://huggingface.co/cointegrated/roberta-large-cola-krishna2020 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_large_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_en.md new file mode 100644 index 00000000000000..7b5ed75baf984f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_en.md @@ -0,0 +1,90 @@ +--- +layout: model +title: RoBERTa large model +author: John Snow Labs +name: roberta_large +date: 2024-09-02 +tags: [en, english, embeddings, roberta, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in [this paper](https://arxiv.org/abs/1907.11692) and first released in [this repository](https://github.com/pytorch/fairseq/tree/master/examples/roberta). This model is case-sensitive: it makes a difference between english and English. + +RoBERTa is a transformers model pretrained on a large corpus of English data in a self-supervised fashion. This means it was pretrained on the raw texts only, with no humans labeling them in any way (which is why it can use lots of publicly available data) with an automatic process to generate inputs and labels from those texts. + +More precisely, it was pretrained with the Masked language modeling (MLM) objective. Taking a sentence, the model randomly masks 15% of the words in the input then runs the entire masked sentence through the model and has to predict the masked words. This is different from traditional recurrent neural networks (RNNs) that usually see the words one after the other, or from autoregressive models like GPT which internally mask the future tokens. It allows the model to learn a bidirectional representation of the sentence. + +This way, the model learns an inner representation of the English language that can then be used to extract features useful for downstream tasks: if you have a dataset of labeled sentences, for instance, you can train a standard classifier using the features produced by the BERT model as inputs. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_en_5.5.0_3.0_1725265519613.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_en_5.5.0_3.0_1725265519613.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +embeddings = RoBertaEmbeddings.pretrained("roberta_large", "en") \ +.setInputCols("sentence", "token") \ +.setOutputCol("embeddings") +``` +```scala +val embeddings = RoBertaEmbeddings.pretrained("roberta_large", "en") +.setInputCols("sentence", "token") +.setOutputCol("embeddings") +val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, embeddings)) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.embed.roberta.large").predict("""Put your text here.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|842.5 MB| + +## Benchmarking + +```bash + +When fine-tuned on downstream tasks, this model achieves the following results: + +Glue test results: + +| Task | MNLI | QQP | QNLI | SST-2 | CoLA | STS-B | MRPC | RTE | +|:----:|:----:|:----:|:----:|:-----:|:----:|:-----:|:----:|:----:| +| | 90.2 | 92.2 | 94.7 | 96.4 | 68.0 | 96.4 | 90.9 | 86.6 | +``` \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_large_pfg_donation_detection_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_pfg_donation_detection_en.md new file mode 100644 index 00000000000000..50a17c43f948f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_pfg_donation_detection_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_large_pfg_donation_detection RoBertaForSequenceClassification from LACAI +author: John Snow Labs +name: roberta_large_pfg_donation_detection +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_pfg_donation_detection` is a English model originally trained by LACAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_pfg_donation_detection_en_5.5.0_3.0_1725238522374.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_pfg_donation_detection_en_5.5.0_3.0_1725238522374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_pfg_donation_detection","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_pfg_donation_detection", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_pfg_donation_detection| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/LACAI/roberta-large-PFG-donation-detection \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_large_pfg_donation_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_pfg_donation_detection_pipeline_en.md new file mode 100644 index 00000000000000..0afdd84b00380d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_pfg_donation_detection_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_large_pfg_donation_detection_pipeline pipeline RoBertaForSequenceClassification from LACAI +author: John Snow Labs +name: roberta_large_pfg_donation_detection_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_pfg_donation_detection_pipeline` is a English model originally trained by LACAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_pfg_donation_detection_pipeline_en_5.5.0_3.0_1725238612447.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_pfg_donation_detection_pipeline_en_5.5.0_3.0_1725238612447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_pfg_donation_detection_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_pfg_donation_detection_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_pfg_donation_detection_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/LACAI/roberta-large-PFG-donation-detection + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_large_swiss_legal_gsw.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_swiss_legal_gsw.md new file mode 100644 index 00000000000000..e7e06422763836 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_swiss_legal_gsw.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Swiss Legal Roberta Embeddings +author: John Snow Labs +name: roberta_large_swiss_legal +date: 2024-09-02 +tags: [gsw, swiss, embeddings, transformer, open_source, legal, onnx] +task: Embeddings +language: gsw +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Legal Roberta Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `legal-swiss-roberta-large` is a Swiss model originally trained by `joelito`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_swiss_legal_gsw_5.5.0_3.0_1725264232623.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_swiss_legal_gsw_5.5.0_3.0_1725264232623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +sentence_embeddings = RoBertaEmbeddings.pretrained("roberta_large_swiss_legal", "gsw")\ + .setInputCols(["sentence"])\ + .setOutputCol("embeddings") +``` +```scala +val sentence_embeddings = RoBertaEmbeddings.pretrained("roberta_large_swiss_legal", "gsw") + .setInputCols("sentence") + .setOutputCol("embeddings")) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_swiss_legal| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|gsw| +|Size:|1.6 GB| + +## References + +References + +https://huggingface.co/joelito/legal-swiss-roberta-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_large_yelp2class_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_yelp2class_en.md new file mode 100644 index 00000000000000..8b6ac797238230 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_yelp2class_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_large_yelp2class RoBertaForSequenceClassification from Siki-77 +author: John Snow Labs +name: roberta_large_yelp2class +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_yelp2class` is a English model originally trained by Siki-77. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_yelp2class_en_5.5.0_3.0_1725238047655.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_yelp2class_en_5.5.0_3.0_1725238047655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_yelp2class","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_yelp2class", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_yelp2class| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Siki-77/roberta_large_yelp2class \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_long_answer_nq_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_long_answer_nq_en.md new file mode 100644 index 00000000000000..c4ed31e49638f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_long_answer_nq_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_long_answer_nq RoBertaForSequenceClassification from RameshArvind +author: John Snow Labs +name: roberta_long_answer_nq +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_long_answer_nq` is a English model originally trained by RameshArvind. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_long_answer_nq_en_5.5.0_3.0_1725277593460.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_long_answer_nq_en_5.5.0_3.0_1725277593460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_long_answer_nq","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_long_answer_nq", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_long_answer_nq| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|467.7 MB| + +## References + +https://huggingface.co/RameshArvind/roberta_long_answer_nq \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_long_answer_nq_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_long_answer_nq_pipeline_en.md new file mode 100644 index 00000000000000..1053048e7de7fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_long_answer_nq_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_long_answer_nq_pipeline pipeline RoBertaForSequenceClassification from RameshArvind +author: John Snow Labs +name: roberta_long_answer_nq_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_long_answer_nq_pipeline` is a English model originally trained by RameshArvind. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_long_answer_nq_pipeline_en_5.5.0_3.0_1725277618163.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_long_answer_nq_pipeline_en_5.5.0_3.0_1725277618163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_long_answer_nq_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_long_answer_nq_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_long_answer_nq_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|467.7 MB| + +## References + +https://huggingface.co/RameshArvind/roberta_long_answer_nq + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_graphpolygot_MT4TS_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_graphpolygot_MT4TS_en.md new file mode 100644 index 00000000000000..5d2561bf58b68b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_graphpolygot_MT4TS_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English RobertaForTokenClassification Cased model (from kevinjesse) +author: John Snow Labs +name: roberta_ner_graphpolygot_MT4TS +date: 2024-09-02 +tags: [bert, ner, open_source, en, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `graphpolygot-MT4TS` is a English model originally trained by `kevinjesse`. + +## Predicted Entities + +`Framebuffer`, `CryptoService`, `ClientLocation`, `AliasMapEntry`, `KeysType`, `CodeGen`, `DOMExplorerClient`, `GetAssessmentCommandInput`, `OnSaveProps`, `IKeyBinding`, `FirmwareUpdateMetaDataCC`, `DropHandlerProps`, `UpdateApplicationCommand`, `ItemProperties`, `CreateTopicResponse`, `HttpInterceptor`, `ClusterOptions`, `ex.PostUpdateEvent`, `AddTagsToResourceCommand`, `HookContext`, `LogFormatter`, `VisibilityEdge`, `BaseRoute`, `IpcRendererService`, `VocabularySortType`, `TweetItem`, `TwStyle`, `AbstractStatusBarLabelItem`, `GetByEmailAccountsValidationResult`, `TypeValues`, `Utxo`, `IGetRefParamsExternal`, `SubDirectory`, `Promisable`, `TRoutes`, `HostRef`, `DeleteGroupCommandInput`, `TMigrableEnvelope`, `ContextWithActive`, `CreatedInstance`, `ErrorPaths`, `XYZ`, `MatGridList`, `TemplateCategory`, `InterfaceVpcEndpoint`, `Config3D`, `DebounceOptions`, `HighlightSet`, `AnyRenderFunction`, `CompositeAnimation`, `BitstreamFormat`, `NamedImport`, `ProviderOverride`, `MonitoringOutput`, `KeywordCxt`, `msRest.OperationParameter`, `TSVBTables`, `WorkspaceFoldersChangeEvent`, `IReporter`, `KeyframeTrack`, `ObservableArrayAdministration`, `IGitExtension`, `PoolingService`, `BasicCredentialHandler`, `TNSDOMMatrixBase`, `ParseSuccess`, `AggregationData`, `WebSiteManagementModels.StringDictionary`, `PossibilityChild`, `SnackBarService`, `FlushEventArgs`, `DataTableDirective`, `RoseChartSlice`, `BINModelInstance`, `DefaultProps`, `ValueState`, `Box`, `ValidationFuncArg`, `ast.Grammar`, `IToolbarProps`, `RtcpRrPacket`, `ProductUpdateReason`, `MappingPatternInfo`, `GroupKeysOrKeyFn`, `ArrayBindingElement`, `GenerateFileCommandParameters`, `PrivateInstance`, `t.Type`, `StartTransformsRequestSchema`, `CreateDistributionCommandInput`, `GeoCoordLike`, `GraphQLModules.ModuleContext`, `ISPUser`, `IceCandidate`, `AddToQueryLogDependencies`, `InputObjectType`, `ProgressBarState`, `EventHandlerInfosForElement`, `StorageObjectAck`, `MorphOptions`, `CppConfigItem`, `TxInput`, `NotionalAndUnrealizedPnlReturns`, `PortingLocation`, `Check`, `SetRepositoryPolicyCommandInput`, `AlertIconProps`, `ProgramIds`, `IColorMappingFunction`, `GetFieldFormat`, `lsp.TextDocumentPositionParams`, `SInt64`, `LitvisNarrative`, `DescribeJobsCommandInput`, `WorkspaceNode`, `YargsArgs`, `requests.ListLimitValuesRequest`, `TerminalService`, `requests.ListUserAnalyticsRequest`, `Group.Scalar`, `ParsedOptions`, `NavbarProps`, `RoleProps`, `OAuthException`, `AuthPartialState`, `Hooks`, `DeprecationsRegistry`, `MockCacheService`, `IFieldCustomizerCellEventParameters`, `ILauncher`, `RelationAttrInfo`, `IEditor`, `HierarchyOfMaps`, `SpellInfoDetails`, `ProcessId`, `ServerSideTransactionResult`, `MotionResult`, `ResolvedConceptAtomType`, `Club`, `HttpContentType`, `QuestionSelectBase`, `UIRoastingMachineStorage`, `BSPTraversalAction`, `cc.BoxCollider`, `FixCreator`, `DeleteClusterRequest`, `FacebookAuthProvider`, `StructureListMember`, `webpack.RuleSetRule`, `configuration.Publications`, `VerifyRes`, `S3Service`, `RequestParser`, `ArgsOf`, `types.Transport`, `Toxic`, `MonitoringAdapter`, `MockOracleInstance`, `IActionMethodAttribute`, `SlotData`, `UserData`, `SearchPredicate`, `FilterFunctionReturnType`, `AccountsService`, `DeleteRepositoryPayload`, `TSESTree.Expression`, `ITaskItem`, `QueryToken`, `DashboardState`, `ElasticsearchServiceStart`, `BridgeableGuildChannel`, `Const`, `btQuaternion`, `CustomFunctions`, `JWK`, `evt_disasm_sub`, `TabifyBuckets`, `Pokedex`, `EscrowedPayment`, `Hsla`, `Promise`, `IMetadataStorage`, `ModalsStateEntry`, `HttpRequestConfig`, `UserFacingSerializedSingleAssetDataTypes`, `ExpenseCategoriesService`, `CanvasMethod`, `GX.AttenuationFunction`, `PDFHexString`, `DataPersistence`, `TagMap`, `LayertreeItemNode`, `LoggerClient`, `SignatureOptions`, `StaticQueryDocument`, `SendMessageCommandInput`, `InputOperation`, `ParticleEmitter2Object`, `SavedObjectsUpdateOptions`, `TransferBtcBasedBlockchain`, `CaptureStdout`, `RemoteProvider`, `LabelPosition`, `DeleteThemeCommandInput`, `PersonType`, `NotificationConfig`, `BasicDataProvider`, `RequestStatus`, `MessageBoxOptions`, `LightSetting`, `TranscriptConsequenceSummary`, `RgbColor`, `GLRenderHash`, `AnyObject`, `MapEntity`, `url.URL`, `IPolygonData`, `QueuedResponse`, `OfficeMockObject`, `DayKey`, `ListControllerProps`, `LoadCollections`, `CallArgs`, `DeleteApplicationInputProcessingConfigurationCommandInput`, `IRenderInfo`, `EnvironmentConfig`, `HIDDevice`, `TransmartCountItem`, `ExpShapeSymbol`, `HsSaveMapManagerService`, `Runtime`, `RowData`, `ObservableState`, `TemplateSpan`, `TargetColumnGeometry`, `BarcodeMetadata`, `DescribePendingMaintenanceActionsMessage`, `DistributionProps`, `KeyObject`, `IOpdsLinkView`, `FormattedStatus`, `def.Matrix44`, `IFileWithMeta`, `IGaeaSetting`, `SVGNode`, `DateInputProps`, `DejaPopupReponse`, `TaskStore`, `OpenLinkComponent`, `ComponentName`, `NodeSpec`, `IMrepoDigestConfigFilePath`, `SLabel`, `Themes`, `SingleAssetTwoPartyIntermediaryAgreement`, `Child`, `GeoAngle`, `WorkSheet`, `IApplicationHealthStateChunk`, `LongitudeLatitudeNumber`, `postcss.AtRule`, `RetentionPeriod`, `RuleActionChange`, `OPCUAServerEndPoint`, `AtomList`, `SelectOptionProps`, `BoardType`, `ChannelCredentials`, `DirectoryWatcherCallback`, `ComponentFunction`, `StationComplementPlugin`, `BaThemeConfigProvider`, `StackGroupConfigNode`, `TorrentInfo.Info`, `ProfileNode`, `BrowsePath`, `INodeProperties`, `MockDomController`, `Campaign`, `ENDAttribute`, `PositionStyleProps`, `LogAnalyticsLabelAlias`, `inquirerTypes.PromptModule`, `cc.Vec2`, `ast.ParserRule`, `RTCSctpCapabilities`, `androidx.fragment.app.FragmentManager`, `LeaveAction`, `KeyCombine`, `WorkRequestCollection`, `DinoErrorController`, `ISearchResultState`, `IfScope`, `CacheType`, `ActionCreator`, `IPane`, `ClassStaticBlockDeclaration`, `SocketProxy`, `ResponseMetadata`, `ParseIterator`, `StartCliConfig`, `DmmfDocument`, `ActionStatus`, `ERC1155OperatorMock`, `IBucketHistogramAggConfig`, `NumberArray`, `ChainID.Mainnet`, `ArgGetter`, `KeyPairEthereumPaymentsConfig`, `SubModel`, `ts.PropertySignature`, `ListLeaderboardRecordsAroundOwnerRequest`, `NotebookInfo`, `FakeProgbar`, `TRPCClientError`, `IAssetActionTypes`, `RequestEnvelope`, `TelemetryWorker`, `DeployStacksIO`, `TamaguiInternalConfig`, `RequestAPI`, `CommentUI`, `DestinationCertificate`, `GbTreeNode`, `symbol`, `LowpassCombFilter`, `EntityElements`, `PreparedQuery`, `RStream`, `AutoImporter`, `Pack`, `MetaReducer`, `CeramicClient`, `MetaIndexState`, `MetroConfig`, `IFlavorInfo`, `IPC.IShellProcess`, `IDeliState`, `IListMultipleData`, `PullRequestOpened`, `HandlerInput`, `DataManager`, `RangeFilter`, `IContextErrorData`, `Joplin`, `IProjectType`, `StackStyleProps`, `ControlledStateProperies`, `EasyPZ`, `SymbolParam`, `SessionRefreshRequest`, `Env`, `ChannelListItem`, `ICustomValidatorResponse`, `KeyboardProps`, `Solo`, `RelativeLink`, `TransactionOptions`, `ConnectionArguments`, `HoverInsertActions`, `Types.ReadyType`, `_DeepReadonlyObject`, `StorageProvider`, `QueryOrdersRequest`, `VideoStreamIndex`, `ICharaProfile`, `reduxForm.ConverterForm`, `IBaseTaskParams`, `EqualityMap`, `CodeBlockWriter`, `HitSensorInfo`, `JRPCEngineEndCallback`, `AndroidOutput`, `RenderPassContext`, `WebGLContextAttributes`, `TableForeignKey`, `PutLoggingOptionsCommandInput`, `actions.Args`, `PublicModelRouter`, `CodelistService`, `WhereFilterOp`, `IConvectorControllerClient`, `Refiner`, `ReadAllCallback`, `ShadowsocksManagerService`, `SchemaComparator`, `Monitor`, `ProjectConfigData`, `UpdateAssetCommandInput`, `IUpsertScalingPolicyCommand`, `ResourceTypeSummary`, `InfluxVersion`, `HtmlTemplate`, `GraphQLRequestContextDidResolveOperation`, `Perspective`, `CompareLookup`, `Contact`, `SetIamPolicyRequest`, `CollectionManifest`, `MetadataReader`, `MetaesContext`, `CryptographyService`, `ProviderDef`, `BoxStyleProps`, `UberChoice`, `STColumn`, `TipsLabels`, `SymbolWithParent`, `FilePropertyProps`, `AnyRawBuilder`, `K6`, `MockRequestInit`, `DiscordMessageReactionAdd`, `MessageInfo`, `LogicOperator`, `TStyle`, `IBookmarkState`, `Animate`, `ChangeEventHandler`, `NormalizedOptions`, `DeleteServiceRequest`, `PluralSub`, `ContractCallPayload`, `SerializedError`, `vscode.TextEditorSelectionChangeEvent`, `LicenseStatus`, `SourceDescription`, `ClsService`, `xDatum`, `RequestLimitConfig`, `RegExpExecArray`, `MarkedString`, `ClampedValue`, `ProcessExecution`, `FetchedBalances`, `ModelerFourOptions`, `MidiInstrument`, `Callable`, `CloudFormation`, `IViewHandler`, `BlockPos`, `Just`, `TVariables`, `PrimitiveValue`, `NamedExoticComponent`, `TClientData`, `IFriend`, `V.Scheme`, `MyButton`, `AsyncIterableQuery`, `StackUndeployOperation`, `TreeConfiguration`, `com.google.ar.sceneform.Node`, `DiagnosticsCallFeatureState`, `ComponentSID`, `TSContinue`, `LocalStorageIndex`, `Webview`, `ReactFramework`, `ThySlideConfig`, `MangoCache`, `jsdoc.Annotation`, `PSPoint`, `TabFragmentImplementation`, `InputWithModel`, `BufferViewResult`, `SavedObjectsClient`, `TxStatus`, `TimelineChartRange`, `ExperimentalStickering`, `MarkMap`, `ResourceArray`, `InputOption`, `IPnpmShrinkwrapDependencyYaml`, `TextClassification`, `PvsFormula`, `IBlob`, `MerkleInclusionQuantifier`, `Tx`, `PartialState`, `ListPositionCacheEntry`, `TestToken`, `MetricsStore`, `ExpandPanelActionContext`, `PageListProps`, `EmailActionConnector`, `AllureTest`, `SharingUpdate`, `EnumerationDefinitionSchema`, `IBufferLine`, `cp.SpawnOptions`, `OpenSearchRawResponseExpressionTypeDefinition`, `ComponentComment`, `EvaluationConfig`, `ScopeFilter`, `IAppConfig`, `QualifiedRules`, `IMutationTree`, `BaseManifestGenerator`, `NowResponse`, `GetRecordsCommandInput`, `LogParams`, `QuoteOptions`, `FinancialViewEntry`, `DecryptionMaterial`, `AnyKey`, `EdgeAttributes`, `OptionObject`, `IRECProduct`, `VisualizationDimensionGroupConfig`, `IInternalActionContext`, `SlpTransactionDetails`, `RouteMatcher`, `MiddlewareFactory`, `RectShape`, `IDropDownTreeViewNode`, `StyleTokens`, `NewTootState`, `SendChannelMessageCommandInput`, `LuaThread`, `ECS`, `Entry`, `Anchored`, `OnPreResponseToolkit`, `CategorizedSettings`, `IParseHandler`, `ArcoOptions`, `ConfigYaml`, `KGS.DataDigest`, `ChainId`, `CookiesOptions`, `DialogProperty`, `TranslationConfig`, `DestinationConfig`, `EdgeData`, `BaseTx`, `NgxsWebsocketPluginOptions`, `TRgb`, `SearchFormLayoutProps`, `PoolState`, `OrganizationProjectService`, `VscodeWrapper`, `MatchNode`, `AlertContextOptions`, `Rec`, `XRFrame`, `RegistrationData`, `dScnKy_env_light_c`, `ValueFilterPlugin`, `GfxRenderInstManager`, `SearchSource`, `CallHierarchyService`, `NoteNumberOrName`, `PagedResp`, `DaySpan`, `ExtendedPOIDetails`, `CreateTableCommandInput`, `Menu`, `RawSavedDashboardPanel630`, `InitializeHandlerArguments`, `OpenCVOperatipnParams`, `MatAutocompleteSelectedEvent`, `ReferencesResult`, `PrivKey`, `ColExpression`, `Planet`, `AttributeKey`, `FsReadOptions`, `ChainMergeContext`, `ConfirmOptions`, `WsKey`, `HsCommonEndpointsService`, `FetchResult`, `IPatchList`, `StartApplicationCommandInput`, `t.ValidationError`, `PyChessModel`, `YarnLock`, `TeamService`, `MockTextNode`, `XMessageOption`, `AxisProps`, `Results`, `ExclusionVisibleVirtualNode`, `FixedDomPosition`, `SignedBlockType`, `SyntheticKeyboardEvent`, `FontCatalog`, `NextCharacter`, `MiBrushRepaintConfig`, `DejaSnackbarComponent`, `ExportOptions`, `AnimatedComponent`, `HandleReference`, `Awaiter`, `ConnectionHealthData`, `RequestEntity`, `TableColumnDirective`, `GltfAsset`, `GetReferenceOptions`, `VcsService`, `EPObject`, `IExternalHooksFunctions`, `ParticipantTracks`, `GraphQLSchemaPlugin`, `IRenderMime.IMimeModel`, `KeyframeNode`, `FormEvent`, `UpSetThemes`, `TwoSlashReturn`, `AppRecord`, `PageResource`, `FilePaths`, `IContextualMenuItem`, `ListenerType`, `ButteryNode`, `LoadingService`, `SimpleScalarXmlPropertiesCommandInput`, `d.OutputTargetDistCustomElements`, `KueryNode`, `DescribeDBSnapshotsCommandInput`, `RoutedPoint`, `MockRule`, `FeedId`, `PointLike`, `VqlClient`, `NetworkResolver`, `LoadableClassComponent`, `MenuData`, `ImageFilter`, `INvModule`, `SearchableItemPresenter`, `PublisherProperties`, `StyleSheetType`, `PreferenceProviderDataChange`, `Moize`, `PrepareReactRender`, `DownloadOptions`, `crypto.BinaryLike`, `IAddressBookState`, `EPPrimitiveDependencies`, `ActionsSdkApp`, `Yield`, `Primitives.Numeric`, `WhenToMatchOptions`, `IReduxState`, `AtomRef`, `ServiceCatalogSummary`, `TodoItem`, `VcalDateOrDateTimeProperty`, `SaveDialogOptions`, `IHawkularAlertsManager`, `CommanderStatic`, `ValidationResults`, `NzModalRef`, `LegacyVars`, `SubTypeBuilder`, `GetConnectivityInfoCommandInput`, `TransferData`, `BeInspireTreeNodes`, `TreeMap`, `GainEntry`, `vault`, `JupiterOneClient`, `CoapResponse`, `cc.SpriteFrame`, `LocalizeRouterService`, `PercentileRanksMetricAggDependencies`, `FnN2`, `ArgTypes`, `AttachmentInfo`, `CupertinoDynamicColor`, `MockDataset`, `msRest.ServiceCallback`, `EntityNameExpression`, `LogoutOptions`, `XSession`, `Aperture`, `ThisTypeNode`, `HotswappableChangeCandidate`, `SourceInfo`, `TContext`, `ColorSwatchProps`, `RulesTestContext`, `LoggerNamespace`, `RippleBalanceMonitor`, `TransactionObject`, `IFilterModel`, `MovieDetails`, `ProgressListener`, `IE`, `Protocol.Network.ResponseReceivedEvent`, `ThyClickDispatcher`, `IMGUI`, `MyTypeDeclarative`, `TObj`, `PeopleIterator`, `MessageAttributeMap`, `KeyChange`, `PipeState`, `FloatAnimationTrack`, `ListApmDomainWorkRequestsRequest`, `AggregationResponse`, `CurrencyType`, `DialogContentProps`, `LogoProps`, `IChunk`, `ComponentRequestTable`, `BigQueryRetrievalRow`, `PermissionState`, `TabView`, `Tag`, `Vector3D`, `DeleteEventSubscriptionMessage`, `DateConstructor`, `NetworkContracts`, `NettuAppResponse`, `TypeLiteral`, `CoordinateXYZ`, `FactoryFunction`, `SkyhookDndService`, `IRawHealthEvaluation`, `LoadingManager`, `TableCellSlot`, `TabBarToolbarRegistry`, `ResponseFormat`, `ListFleetsCommandInput`, `ReduxLikeStateContainer`, `SendMessageOptions`, `SceneItem`, `ExtendedHttpsTestServer`, `SpacesService`, `IInspectorState`, `D3LinkNode`, `EndpointDescription`, `TypedThunk`, `VTF`, `RemoveTagsCommandInput`, `ChartPointSourceItem`, `Counter__factory`, `AccessKeyStorageJson`, `Diagram`, `ProductJson`, `PathNode`, `VpcSubnetArgs`, `TimelineEvent`, `GitHubEventModel`, `DebugOption`, `ImmutableCollection`, `AccountingRecord`, `IChainForkConfig`, `OpenPGPKey`, `AuthorizationRules`, `DeleteAccessPointCommandInput`, `core.CallbackOptionallyAsync`, `TerritoryAliasMap`, `CreateDedicatedIpPoolCommandInput`, `RecipientType`, `CalendarObject`, `InterfaceWithCallSignatureReturn`, `IObjectWillChange`, `JDevice`, `Paint`, `TextChannel`, `PostProcessingRule`, `DestroyArgv`, `WatchEvent`, `EventStreamSeed`, `IBaseImageryLayer`, `DAL.DEVICE_ID_COMPONENT`, `later`, `StopDeploymentCommandInput`, `P2PRequestPacketBufferData`, `EventListener`, `Text.JSON`, `GlobalParameter`, `Schema$RowData`, `interfaces.Target`, `React.FC`, `AnimationInternal`, `IfStmt`, `DefinitionElementProps`, `postcss.Node`, `MockComment`, `Insights`, `VisitResult`, `BlockbookConnectedConfig`, `Detector`, `ValidationRunData`, `AmmLiquidityPool`, `ITasksGetByContactState`, `VRMDebugOptions`, `UpdateThemeDto`, `CartItemsResponse`, `FileBox`, `MeetingCompositeStrings`, `tinycolor.Instance`, `BaseScreen`, `MarketResponse`, `TransactionGasPriceComputator`, `FactorySession`, `ScopeDef`, `LifecycleEvent`, `Tile`, `BundleEntry`, `Transducer`, `ScriptCompiler`, `UpdatePortalCommandInput`, `MouseMoveEvent`, `d.CompilerRequest`, `IProductOptionTranslatable`, `TradeType`, `ScriptInfo`, `Conversion`, `ControlPanelsContainerProps`, `NameIdentifierNode`, `VisitorInvocation`, `JournalMetadata`, `CompareFunction`, `ExprVisitor`, `LoginService`, `ModProperty`, `DragRef`, `Testrec`, `TClient`, `InstanceGeometryData`, `DescribeLimitsCommandInput`, `UiActionsPlugin`, `DatasourceOverwrite`, `CalculatorTestContext`, `EntryContext`, `SupportedEncoding`, `FileGroup`, `AggregateQuery`, `NetplayPlayer`, `PortalInfo`, `HeroesState`, `NormalizeStateContext`, `MockEnv`, `ModelQueryBuilderContract`, `AttrNode`, `providers.Provider`, `BrowserObject`, `GlobalVariantGroupConfig`, `SeverityLevel`, `GetPartitionIndexesCommandInput`, `DataSourceInstanceSettings`, `QuizReaction`, `ts.ElementAccessExpression`, `sdk.SpeechSynthesisResult`, `MiddlewareNext`, `Resp`, `DecoratorDef`, `ComponentStyle`, `Mesh3D`, `GcpCloudProvider`, `IRes`, `Nightmare`, `SHA512_256`, `GetSelector`, `RenderWizardArguments`, `InterfaceMapValue`, `ResizeObserver`, `TypeBinding`, `JoinedReturnType`, `FetchRequestId`, `JacobianPoint`, `ICoordinate`, `PaymentV1`, `ResourceMap`, `CodeBuilderConcrete`, `ResolvedDeclarationList`, `WalkMemberContext`, `requests.ListVolumeGroupBackupsRequest`, `SpecPickerInput`, `AccountRefresh`, `CheatModeMachineContext`, `CompletionSymbol`, `DateLocale`, `KontentItemInput`, `CommentDoc`, `SwaggerLambdas`, `MaterialParams`, `CompareFunc`, `ArgumentBuilder`, `Library`, `NoteEditorState`, `ViewableGrid`, `google.maps.Marker`, `TradeProvider`, `LineChart`, `NzUploadChangeParam`, `MockLogger`, `ModuleKey`, `DashboardData`, `pageNo`, `IconMenuItem`, `AzureDataTablesTestEntity`, `SObjectRefreshOutput`, `ChangeState`, `ITechnology`, `SessionStateControllerAction`, `InitializeParams`, `OrderedIndex`, `ShortConnectionDTO`, `Type_List`, `INotebookTracker`, `ColProps`, `StatefulSearchBarProps`, `ts.ExportSpecifier`, `StatusActionQueue`, `TRPCResponse`, `IUpdateStacksCommandArgs`, `RstStreamFrame`, `AvailableFeature`, `IFormControlContext`, `Dict`, `FormLayoutProps`, `ClientProxy`, `AdbSocket`, `INetworkPlayer`, `Valid`, `VolumeAttachment`, `AlertingRouter`, `OnPreAuthToolkit`, `ClJobs`, `SegmentDetail`, `IRecordReference`, `ICommandArguments`, `LitecoinAddressFormat.Modern`, `IAppInfo`, `CreateDBClusterCommandInput`, `ServerDataItem`, `IQueryConfig`, `MigrationResult`, `CellService`, `PluginCtx`, `SafeExpr`, `App.services.IRequestService`, `ProxyConfiguration`, `SingleSigHashMode`, `ButtonListenerCallback`, `FoundNodeFunction`, `MsgDeleteProvider`, `IOpts`, `SummaryNode`, `StashTabSnapshot`, `BlockProps`, `StarknetERC721ContextInterface`, `CustomRouteShorthandOptions`, `RestoreRequest`, `SGMark`, `InstructionParams`, `BUTTON_SHAPE`, `EndpointType`, `SearchResultsPage`, `LaunchOptions`, `TradingPosition`, `Epoch`, `DateRangeItemInfo`, `BaseResourceOptions`, `StringFilter`, `RuntimeField`, `NavbarService`, `IThrottleService`, `PopupModelConfig`, `PropertyValue`, `ITable`, `EPersonDataService`, `ObservableLanguagePair`, `DefaultRequestOptions`, `FullIconifyIcon`, `Immediate`, `SpeakerActions`, `LogFilter`, `BitfinexWebsocket`, `TD.DataSchema`, `ThemedComponentThis`, `Optimizer`, `Fee`, `ListDeliverabilityTestReportsCommandInput`, `StateUpdate`, `SourceControl`, `ShortcutObject`, `ISerDeDataSet`, `BookmarkTreeNode`, `ProviderService`, `GraphQLError`, `d.RobotsTxtOpts`, `SpeechSynthesisUtterance`, `EntityDocumentResult`, `IgnoredCommentContext`, `CanaryScope`, `analyze.Options`, `ProductVariantService`, `InventoryStat`, `SimpleButton`, `CmsEditorFieldRendererPlugin`, `AnimationDirection`, `CollectionObj`, `TestServer`, `EditingData`, `FeaturesList`, `requests.ListVmClustersRequest`, `TCompactProtocol`, `IRoomObject`, `ContractConfig`, `Text_2`, `ParamInstance`, `QueryFieldMap`, `RehypeNode`, `ForbiddenWordsInfo`, `IDataModel`, `NgStyleInterface`, `RouterNavigatedAction`, `AlgoliaClient`, `RouterMock`, `QuantityLabel`, `jsiiReflect.Type`, `MeterCCGet`, `SDKModels`, `GLenum`, `LegendItemList`, `PromiseBase`, `AadHttpClient`, `Tournament`, `VerdaccioError`, `Media`, `FindAndModifyWriteOpResultObject`, `ActionSequence`, `AggHistoryEntry`, `ResolveSavedObjectsImportErrorsOptions`, `ContextModel`, `templateDataType`, `ExclusiveTestFunction`, `AppSocket`, `TypeCase`, `FunctionProperties`, `ParsedNode`, `Buntstift`, `ColumnData`, `PerpMarketConfig`, `CustomElement`, `MultiChannelCCCommandEncapsulation`, `AppProps`, `Vector2_`, `ResponseFixtures`, `requests.ListGroupsRequest`, `React.SyntheticEvent`, `NoticeProps`, `AssetServiceClient`, `GraphQLModelsRelationsEnums`, `TextStringNoLinebreakContext`, `SubscriptionEmit`, `ParserServices`, `RunOptions`, `PO`, `ExecuteTransactionCommandInput`, `DataPoint`, `StreamActivityModel`, `DaffAuthorizeNetReducerState`, `NavigationPluginStartDependencies`, `DefaultConfig`, `OracleConfig`, `UpdateUserAvatarService`, `builder.IDialogResult`, `AlertTitleProps`, `GraphVertex`, `F`, `TextureFormat`, `WorkflowExecuteMode`, `IXingInfoTag`, `ProjectLock`, `GleeConnection`, `IControllerConfig`, `IBucketDateHistogramAggConfig`, `requests.ListUpcomingScheduledJobsRequest`, `CreateChannelCommandInput`, `BlockDocument`, `DeleteProjectCommandInput`, `AbstractShaderNode`, `CkbMint`, `ListSafetyRulesCommandInput`, `ClientQuery`, `SidebarItem`, `StateNodeConfig`, `PatternMatchKind`, `TreeMeta`, `ConstantSourceNode`, `InMsg`, `ReadableQuery`, `SearchResultComponent`, `CategoricalChartProps`, `CoerceResult`, `RefactoringWithActionProvider`, `MDCDialogPresentationControllerDelegateImpl`, `IStartupInfo`, `IQuaternion`, `BaseRowDef`, `CaseReducer`, `Test`, `PreparedData`, `IAnyVisualization`, `IReminder`, `IosBuildName`, `TransactionAction`, `ITaskDataConnections`, `KeyRange`, `MemBuffer`, `OrderedComparator`, `ThreeEvent`, `DevicePixelRatioMonitor`, `ThyGuiderStep`, `ViewSlot`, `UploaderInputs`, `InputFieldsComponentsDef`, `ParticipantPermission`, `BitstreamFormatRegistryState`, `CstmHasuraCrudPluginConfig`, `Koa.Next`, `CodePrinter`, `ReferenceResolverState`, `UserQueryTask`, `FilterState`, `PanelData`, `WebGLSync`, `ReporterFactory`, `CanvasPath`, `ApiPackage`, `ISuggestionsCollector`, `BaseTransaction`, `ThrowIterable`, `MockDrake`, `MarkerInstanceType`, `LensState`, `VertexElement`, `ModelList`, `DAL.KEY_ESC`, `HsSidebarService`, `Ti18nDocument`, `BatchExecuteStatementCommandInput`, `CacheContent`, `RuleWithId`, `GfxBuffer`, `DiffOptionsNormalized`, `OsqueryAppContext`, `SelectChangeEvent`, `MarkerSet`, `MenuEvent`, `N3`, `TProtocol`, `EmailValidatorAdapter`, `PagerBase`, `IStyleObj`, `RouteData`, `SubstanceEnv`, `CreateProjectDto`, `DbUser`, `MenuStackItem`, `JSXExpressionContainer`, `IndexedCallback`, `OpGraphPath`, `Vec3Sym`, `DeepImmutable`, `ContinueStatement`, `IPointAttribute`, `SimpleSelector`, `UIRouter`, `ClassicComponentClass`, `Dual`, `AppServicePlan`, `ObjectView`, `DeleteValue`, `TreeNodeHTMLElement`, `IconComponentProps`, `UserProfileService`, `ImportFromAsNode`, `UpdateDocumentCommandInput`, `IterableIterator`, `WidgetView`, `FormErrorMessageType`, `requests.ListDatabaseUpgradeHistoryEntriesRequest`, `TestObservableLike`, `PopupStackItem`, `DocumentDeltaAtomicUpdate`, `DeleteDashboardCommandInput`, `DescriptorProto`, `DirectionLight`, `RequestCompleteEvent`, `EntityActionDataServiceError`, `CodegenDesignLanguage`, `Aggregator`, `DeprecationsClient`, `TimestampTrigger`, `SavedObjectsCreateOptions`, `HexcolorInfo`, `NotificationCreateProps`, `PDFForm`, `ClientOrderGoodsInfo`, `ValidationMetadata`, `TopLevel`, `AtomGridmaskImageElement`, `MemberLikeExpression`, `IntFormat`, `DirectoryObjectListResult`, `HTMLDice`, `OrgPass`, `SheetChild`, `BookService`, `IConversionValidation`, `SavedObjectSanitizedDoc`, `TLPointerEventHandler`, `FormStore`, `NextFnType`, `IWorkerArgs`, `XSort`, `TFnWatcher`, `Plugin.SNSAdaptor.Definition`, `EvAgentSession`, `NonEmptyArray`, `SQLVariables`, `ConfiguredPluginResource`, `EditableDocumentData`, `EntityItem`, `ResultType`, `QueryMany`, `IAmazonServerGroupDetailsSectionProps`, `RemovableAnalyserNode`, `EventExclusionPlugin`, `FluentBundle`, `RequestSpan`, `ExecutorState`, `StudioComponentInitializationScript`, `cBgS_GndChk`, `MappedSingleSourceQueryOperation`, `ListKeyManagerModifierKey`, `TemplatesManager`, `GraphQLList`, `Wrapper`, `QueryFilter`, `TagLimitExceededException`, `ClusterNode`, `RadioButtonProps`, `Operand`, `SpatialOctreeNode`, `StorageArea`, `PDFAcroComboBox`, `EntityChangeEvent`, `UberChart`, `SearchOpts`, `BubbleSeriesStyle`, `Operator.fλ`, `DescribeTasksCommandInput`, `Gzip`, `LegendType`, `WebGL1DisjointQueryTimerExtension`, `DialogPosition`, `RpcMessageSubject`, `t.Identifier`, `Ternary`, `StackProps`, `CoreHelpers`, `fhir.Task`, `unist.Node`, `CGSize`, `OfficeApp`, `DatePickerProps`, `BigintIsh`, `EdiElement`, `StepComponent`, `AccountLeague`, `RollupWatcher`, `PBRCustomMaterial`, `jdspec.PacketInfo`, `IMediaQueryCondition`, `ISPField`, `ServiceMetadata`, `BEMHelper`, `DescribeConnectorsCommandInput`, `ColumnPoint`, `AbstractRunner`, `CallHierarchyDataItem`, `IFabricWalletGenerator`, `ast.LetNode`, `SanityClient`, `ReorderAggs`, `RenderData`, `InterviewQuestionSortMap`, `Cubelet`, `TransportRequestOptions`, `SMTConstructorGenCode`, `Kubectl`, `IGetActivitiesStatistics`, `EditPropertyConfig`, `EmbedType`, `IRestApiContext`, `ObserverCallback`, `PerfToolsMutation`, `IModelConfiguration`, `TransferBrowserFftSpeechCommandRecognizer`, `IFocusedCellCoordinates`, `StyledProperties`, `TransformerOptions`, `ItemMap`, `KeyLabel`, `QuickPickItem`, `ColorConfig`, `CronosClient`, `GroupedOrderPremiumRow`, `ISparqlBinding`, `PullRequestViewModel`, `ImmutableCell`, `RoosterCommandBarProps`, `AddTagsOutput`, `Widget`, `CommandModule`, `StatefulCallClient`, `ListAnalyzedResourcesCommandInput`, `BarFile`, `estree.Program`, `TProps`, `UsersResponse`, `QueryOptionNames`, `IExportProvider`, `PointContainer`, `Int32Array`, `ViewRanges`, `ArrayBindingOrAssignmentPattern`, `AnimatedNode`, `AndDeciderInput`, `ColumnsSchema`, `LinkedListChild`, `BlockStackService`, `ConnectionGraphicsItem`, `ScrollSpyService`, `IReactExtension`, `BSplineSurface3d`, `UserGroup`, `SessionSourceControl`, `INestApplication`, `IEntityState`, `ComponentLayoutStyleEnum`, `LayerGroup`, `CompositeFilterDescriptorCollection`, `IExecutionContextContainer`, `SelectSeriesInfo`, `Safe`, `AutoTuneMaintenanceSchedule`, `ODataStructuredTypeParser`, `CancellationReceiverStrategy`, `SSBSource`, `AABB`, `GenericMetricsChart`, `NSMutableDictionary`, `SavedObjectsStartDeps`, `DeployedReplicaCollection`, `ModuleListener`, `PlaneTransformation`, `HRTime`, `ProjectItem`, `TreeBacked`, `BCSV.Bcsv`, `vscode.FileStat`, `HtmlRendererOptions`, `CoverConfiguration`, `next.Group`, `TRecord`, `NodeTypes`, `React.RefCallback`, `GetJobRequest`, `SliderHandle`, `tStringDecimalUnits`, `DeploymentImpl`, `RootVertex`, `ObservableChainQuery`, `Edition`, `ThemeColorDefinition`, `CallFrame`, `UniformPub`, `ContentFilter`, `AnimationAction`, `CacheUpdateEvent`, `DeSerializersT`, `near.NearSwapTransaction`, `CameraMatrix`, `SlashCommandConfig`, `KeyToIndexMap`, `TestEthersProvider`, `VpcConfig`, `IListSelectionConfig`, `GoogleStrategy.Profile`, `jest.SpyInstance`, `NetworkgraphSeries`, `UserFromToken`, `AlertDetails`, `ListDomain`, `Pickle`, `ExtendedCodeAction`, `DebugProtocol.StackTraceArguments`, `CollapsedTransform`, `InitialProperties`, `BodyPartConstant`, `CustomSeriesRenderItemParams`, `NineZoneManager`, `UniswapV2Pair`, `InvalidTagException`, `ts.ObjectType`, `DynamicsContext`, `core.ETHSignTx`, `TransactionApplyContext`, `WithLiteralTypescriptType`, `UserStoreReference`, `ClassVisitor`, `WebSocketTransport`, `IAst`, `ComponentGeneratorOptions`, `SavedObjectFinderUiProps`, `SalesforceFormValues`, `FolderResponse`, `LocaleService`, `CalendarConstants`, `RuleValidator`, `GX.SpotFunction`, `OperationData`, `DebugProtocol.InitializeRequestArguments`, `TileView`, `PredictionContextCache`, `GraphQLEnumType`, `IThrottlingMetrics`, `Technique`, `VirtualNetworkTap`, `DropdownButtonProps`, `MulticallResponse`, `DataSourceSnapshot`, `IQueryListProps`, `KeyUsage`, `SessionStateControllerState`, `RefreshTokenRepository`, `IColumnWrapper`, `AB`, `Graphin`, `TransactionSigner`, `SShapeElement`, `ParameterList`, `CreateConnectionCommand`, `ProjectFile`, `RpcContext`, `AESCipher`, `HumidityControlSetpointCCReport`, `TypeEvaluator`, `ProxyHandler`, `ObjectOptions`, `DescribeUserProfileCommandInput`, `CreditCardView`, `StructureTerminal`, `TypeTemplate`, `EightBittr`, `LegendPositionConfig`, `MapConfig`, `IAppSetting`, `SelectItemDirective`, `ActionFunction`, `Light_t`, `ModalService`, `MotionComponent`, `GradientDataNumber`, `UserPosition`, `FormFields`, `SubSequence`, `DataSourceConfiguration`, `Dockerode.Container`, `InformationPartitionElementProps`, `InterleavedBuffer`, `Responder`, `EmployeeStore`, `Effect`, `EntryControlCCNotification`, `ItemView`, `HookDecorator`, `SubConfig`, `CategorizedPropertyMemberDoc`, `IEntityType`, `TransactionId`, `WebWorker`, `requests.ListVmClusterPatchHistoryEntriesRequest`, `CollectionResult`, `CF.Subscribe`, `ColumnMetaData`, `AnnotationCollection`, `HintContext`, `Metas`, `UpdateStateValueFunc`, `Corner`, `GoldTokenWrapper`, `object`, `ICanvas`, `QConn`, `RegisterOutput`, `VerificationCode`, `CodeFlowReferenceExpressionNode`, `NextStep`, `BackgroundProcessState`, `NumBopType`, `FbBuilderFieldPlugin`, `Events.prekill`, `DestinationsByType`, `ActionsSubject`, `FieldProps`, `Diagnostic`, `ProcessRequestResult`, `TestFunctionImportEdmReturnTypeParameters`, `Patient`, `ICellRendererParams`, `Reflecting`, `DeleteDomainRequest`, `Champions`, `SyntheticErrorLabel`, `ZoneFileObject`, `d.OutputTargetDocsVscode`, `ListOdaInstancesRequest`, `UpdateEntryType`, `ListLeaderboardRecordsRequest`, `StoredFile`, `iDataTypes`, `INixieControlPanel`, `SVGTransform`, `RequestInit`, `CollectionTemplateable`, `Array3`, `SelectionSetNode`, `ExtConfig`, `TButtons`, `InfoPlist`, `PersistentVolumeClaim`, `Uuid`, `BubbleLegendItem.RangesOptions`, `ListNodesCommandInput`, `VisualizeEmbeddableContract`, `C51BaseCompileData`, `SourceMapSpan`, `GenericBinaryHeapPriorityQueue`, `UtilityInfo`, `XRFrameOfReference`, `EventSubscriptionsMessage`, `GasOption`, `GPUTextureFormat`, `InsertResult`, `FigurePart`, `SubsetStory`, `TransferTransaction`, `FileLoader`, `AWSSNSEvent`, `ModalInstance`, `SbbNotificationToastConfig`, `MaxPooling3D`, `ObservedNode`, `SocketAwareEvent`, `InjectorIndexes`, `DeleteDeviceCommandInput`, `CategoryResults`, `Portfolio`, `OpRecInterface`, `TransactionOutput`, `QueueOptions`, `RenderOptionFunction`, `ProcessingJobsMap`, `RouteMatch`, `K1`, `StorageValue`, `ListAttachmentsCommandInput`, `PaymentMethod`, `EmojiData`, `SubstituteOf`, `Indexes`, `PluginDeployerEntry`, `ts.Visitor`, `ProxyType`, `Keyframes`, `PackageContribution`, `ObservableMedia`, `NamedAttrMap`, `AngularFireDatabase`, `ShoppingCartState`, `ListDashboardsCommandInput`, `VaultItemID`, `IMinemeldCandidateConfigNode`, `EnvironmentProps`, `DisplayStyleProps`, `JGOFIntersection`, `DocUrl`, `TagValueType`, `NodeIdLike`, `AnimationEntry`, `BooleanLiteralExpr`, `SudokuBoard`, `FormFieldsProps`, `DecoratorType`, `Nodes`, `ts.MethodSignature`, `SPClientTemplates.RenderContext_Form`, `PUPPET.payloads.Room`, `DidDocument`, `StackEvent`, `Type_AnyPointer`, `RouterOptions`, `SubtitlesTrackId`, `LTypeResolver`, `AthenaClient`, `ParsedSite`, `NodeInstructure`, `NativeCallSyntax`, `CognitoUser`, `SchemaValidationContext`, `SsgRoute`, `FormApi`, `HintsConfigObject`, `angular.IIntervalService`, `SourceBuffer`, `RequestSet`, `R3`, `ShaderSlot`, `x.ec2.Vpc`, `RulesMap`, `StreamType`, `d.PrerenderUrlRequest`, `ICreateCommitParams`, `requests.ListExportSetsRequest`, `HttpResponseEncoding`, `languages.Language`, `Plural`, `Tense`, `BlockDefinitionCompiler`, `SimpleList`, `MockActivatedRoute`, `TimelineOptions`, `ConnectedSpace`, `Iam`, `EmbeddableInput`, `SeriesZonesOptions`, `DistanceExpression`, `ECB`, `vscode.Command`, `V1CommandInputParameterModel`, `ListSwipeAction`, `IContainerRuntimeOptions`, `PrebootDeps`, `IFilterOptions`, `XMLSerializer`, `TransactionGenerationAttempt`, `DeserializeWire`, `LicensingPluginSetup`, `LoadingProps`, `ControllerClient`, `QuickInputStep`, `RequestController`, `UpdatePublicData`, `Chord`, `SavedObjectMigrationContext`, `IGLTFRuntime`, `EngineArgs.CreateMigrationInput`, `BluetoothDevice`, `DeleteBotAliasCommandInput`, `CommandLineArguments`, `TextCanvasLayer`, `SummaryItem`, `ProgressBarData`, `ListTagsForResourceRequest`, `GetPolicyResponse`, `DefinitelyTypedTypeRun`, `GroupedFunnel`, `HistoryState`, `PaginationComponent`, `TextureUsage`, `models.NetFramework`, `DefaultEditorDataTabProps`, `VIS0`, `Freeze`, `ToastsApi`, `GlobalPositionStrategy`, `ContextMember`, `IPatch`, `ActionKey`, `OrderPremiumRow`, `RuntimeOptions`, `Torrent`, `PlaylistTrack`, `SObjectTransformer`, `BlogTag`, `AnyImportSyntax`, `StateService`, `SF`, `LinkedDashboardProps`, `KeyPair`, `NetworkManager`, `CustomPropertyHandler`, `$E.IBaseEdge`, `TydomController`, `ISyncedState`, `minimist.ParsedArgs`, `ListUsersCommandInput`, `KeyframeTrackType`, `bitcoinish.BitcoinishPaymentTx`, `AutoCompleteLabel`, `DashEncryption`, `Int32List`, `QueryDeploymentResponse`, `ListRepositoriesReadModel`, `Viewer`, `BluetoothRemoteGATTCharacteristic`, `UpdateOptions`, `KeySchema`, `IMappingsState`, `ControlElement`, `PackedBubbleLayout`, `AWSSNSRecordItem`, `IStats`, `ProjectMap`, `ClipboardEvent`, `ProfilerFrame`, `Yarguments`, `IntrospectionResult`, `FileId`, `DeleteWebACLCommandInput`, `SortClause`, `SubdomainAndZoneId`, `HttpParams`, `MetamaskState`, `MultigraphRequestOptions`, `RTCIceCandidateJSON`, `BoxPlotData`, `ExpressionTypeDefinition`, `IErrorCallback`, `ASNDBS`, `PredictableHook`, `anchor.BN`, `BubbleLegendItem.Options`, `PubEntry`, `imperative.IProfileLoaded`, `FilterOptionOption`, `MatSortable`, `V1Prometheus`, `LocalParticipant`, `ProcessedPackageConfig`, `p5exClass`, `GraphObject`, `IntraDayDataSourceType`, `d.EventSpy`, `ColorSpace`, `CallHierarchyOutgoingCallsParams`, `TestScheduler`, `MockStateContext`, `AnyConfigurationModel`, `CanvasEditorRenderer`, `SourceLocation`, `ArmParameters`, `IndexTree`, `IntlMessages`, `Responses.IListContentItemsResponse`, `GeoPointLike`, `BuiltinFrameworkMetadata`, `TestGraphic`, `Apply1`, `QExtension`, `ShellResult`, `OnReferenceInvalidatedEvent`, `ResourceRecord`, `PromiseResolver`, `Outlet`, `CreateStageCommandInput`, `HomebridgeConfig`, `AnimatableColor`, `SmsHandler`, `RespostaModel`, `PostType`, `IMergeNode`, `TodoType`, `RepositionScrollStrategyConfig`, `ArrayBinding`, `React.MutableRefObject`, `SyncEvent`, `IMYukkuriVoice`, `F.Function`, `TiledSquareObject`, `BaseUIManager`, `FilterGroupKey`, `ServerInfo`, `AnySchemeForm`, `SpacesClientService`, `MockedDataStore`, `IModelHubClientError`, `QueriesStore`, `StartStopContinue`, `ProfileRecord`, `u`, `TokenClaims`, `ExternalProject`, `RectResponderModel`, `IWholeSummaryPayload`, `MongoConnection`, `TemplateInput`, `WriteTournamentRecordRequest`, `SignatureHelp`, `IdentifierInfo`, `TopicId`, `RPC.IWatchResponse`, `KubernetesService`, `GlyphVertices`, `BundleItem`, `SuiteInfo`, `ContentCache`, `Encoder`, `AnimGroupData_Shape`, `AxisTitleOptions`, `FormFieldMetadataValueObject`, `LogsData`, `Employee`, `DataGatewayService`, `$NextFunctionVer`, `TimelineViewWrapper`, `ISO`, `ModuleCode`, `ArgPathOrRolesOrOpt`, `ConfigProviderProps`, `JRPCEngineNextCallback`, `cookie.CookieSerializeOptions`, `Vote`, `ClipRenderContext`, `TRef`, `Json.ObjectValue`, `IApiKubernetesResource`, `DatabaseService`, `ContrastColors`, `IonicModalController`, `EffectCallback`, `WebGLQuery`, `ObservationService`, `IMatrixEventProcessorResult`, `IThyDropContainerDirective`, `CreateProps`, `AWSError`, `BufferStream`, `SqipImageMetadata`, `InvalidInput`, `AxisGeometry`, `EditorChangeEvent`, `UserMessage`, `ICXListHTLCOptions`, `Show`, `AnchorPosition`, `ShippingMethod`, `ButtonComponent`, `IAmazonServerGroup`, `ContainerConfig`, `RigidBodyComponent`, `DisplayNameChangedListener`, `ElectronCertificate`, `DoOnStreamFns`, `StorageQuotaExceededFault`, `TypographyProps`, `GetMessageKeys`, `DDL2.IField`, `ts.ConstructorDeclaration`, `Package.ResolvedPackage`, `GetConfigOptions`, `ColumnAnimation`, `ArenaNodeText`, `Bezier`, `MsgCloseGroup`, `KameletModel`, `ToneEvent`, `GraphQLDirective`, `AzExtTreeDataProvider`, `ElementSourceAnalysis`, `Algorithm`, `AaiMessageTraitDefinition`, `NotificationDataFilled`, `Plane3dByOriginAndVectors`, `AliasOptions`, `FormInterface`, `CommentType`, `VaultID`, `coreClient.OperationArguments`, `IEditorProps`, `GetReadinessCheckResourceStatusCommandInput`, `InruptError`, `Src`, `VisualizeEditorCommonProps`, `ViewModel_`, `requests.ListBdsInstancesRequest`, `DocumentValidationsResult`, `Load`, `NullAndEmptyHeadersServerCommandInput`, `LivelinessMode`, `LightType`, `ExternalDMMF.Mappings`, `GoalItemViewModel`, `DebugConsole`, `IAdjacencyBonus`, `PoiGeometry`, `CssBlockAst`, `AnyValue`, `PlaylistModel`, `PureComputed`, `TSTypeParameterInstantiation`, `DeleteDeploymentCommandInput`, `IVectorStyle`, `TeamMember`, `BaseMessage`, `Adb`, `CountParams`, `IGlobalManager`, `NgWidget`, `ListPoliciesCommandInput`, `Roadview`, `IDBIndex`, `ODataQueryArgumentsOptions`, `Tween`, `SetSelectionMenuDelegate`, `IDBValidKey`, `TextMarker`, `DocumentRangeFormattingParams`, `HeaderStreamManipulator`, `TGroupHandle`, `QueryHook`, `WithoutSheetInstance`, `TypeReference`, `GfxInputLayoutDescriptor`, `NormalizedModule`, `CreateRequest`, `IAppContainer`, `HDWallet`, `ToggleGroupProps`, `Uint256`, `PrerenderContext`, `RootBank`, `ReducersMapObject`, `Visit`, `BasicReflectionEvent`, `TimeFormatter`, `QueryJoin`, `Runtime.Port`, `SilxStyle`, `MultiChannelAssociationCCReport`, `SqrlInstance`, `IContainerNode`, `IEmbedConfigurationBase`, `XPCOM.nsIFile`, `TLSSocket`, `ChangeFn`, `Knowledge`, `UserType`, `Reservation`, `IFavoriteColors`, `HTMLScLegendRowElement`, `IComputedFieldOwner`, `PinejsClient`, `CompilerCtx`, `OpenApiRequestBuilder`, `SourceMapGenerator`, `AuthContextType`, `DocumentStore`, `NavigationDescriptor`, `ValidatedPassword`, `Parjser`, `NodeSSH`, `AlterTableAddColumnBuilder`, `RoomModel`, `AutocompleteItem`, `AccessorConfig`, `CachePage`, `TFunction`, `SerialOptions`, `DecorationOptions`, `Session`, `RepositoryStatistics`, `ReadonlyNFA`, `Let`, `ParsedResults`, `common.WaiterConfiguration`, `SingleSpaAngularOptions`, `ResolveModuleIdOptions`, `GoogleProvider`, `vd.VNode`, `QueryKey`, `ITypeUnion`, `DescribeDashboardCommandInput`, `AuthedRequest`, `Advice`, `AnyRawModel`, `ThrottleSettings`, `MIRTypeOption`, `TypeMap`, `EngineResults.EvaluateDataLossOutput`, `AccountingService`, `AthenaExecutionResult`, `StepInfo`, `DeploymentResult`, `PatternLike`, `d.OutputTargetDocsCustom`, `inferHandlerInput`, `DeleteLifecyclePolicyCommandInput`, `OrderedRotationAngles`, `IToolbarAction`, `MetadataProvider`, `Slab`, `PymStub`, `requests.ListBackupsRequest`, `ITextDiffData`, `WholeHalfUnison`, `StringTypes`, `CommandsSet`, `ParserProduction`, `TypedEvent`, `ArrayCollection`, `Collectible`, `DaffNewsletterSubmission`, `IApprovalPolicy`, `_GlobalJSONStorage`, `UINavigationBar`, `BatchCreateAttendeeCommandInput`, `SVErrorLevel`, `CSSObject`, `IPuppet`, `DirFileNameSelection`, `RequestMock`, `ContentModel`, `DataViewValueColumn`, `UseRefetchOptions`, `PhaseModel`, `DtlsContext`, `IsTenantAvailableInput`, `DataFetcherOptions`, `TEventHandler`, `NotificationID`, `ReplExpect.AppAndCount`, `LazyService`, `PacketInfo`, `IFilePropertiesObject`, `TypeMetadata`, `GitBlameCommit`, `CoreFeature`, `SerializedData`, `CustomType`, `JQueryMouseEventObject`, `GenerateMappingData`, `QRPolynomial`, `stream.Readable`, `Slot`, `LiveExample`, `Define`, `AttributeKeyAndValue`, `ContractInterface`, `TestSuiteInfo`, `d3Geo.GeoRawProjection`, `CharGroup`, `AppUserCard`, `CopyResponse`, `CredentialsOverwritesClass`, `GeneratorFile`, `IndexerManagementResolverContext`, `IErrorPayload`, `RuleEngine`, `FileMode`, `messages.Background`, `PartnerActions`, `UserFacade`, `DocumentLinkShareState`, `ParameterConfig`, `NodeChanges`, `BenzeneGraphQLArgs`, `RelayServiceConnectionEntity`, `TestPlayer`, `AnalyzeCommentResponse`, `MessageAttachment`, `Permissions`, `IncludeMap`, `InputMode`, `ModuleBlock`, `point`, `TPropertyTypeNames`, `RosApiCommands`, `Fiber`, `ContinuationData`, `HashMapIteratorLocationTracker`, `DialogItem`, `ExpoAppManifest`, `TraitNode`, `NormalCollection`, `GenericRequestHandlerChain`, `VerifyEmailAccountsValidationResult`, `MappedTypeNode`, `ScopedCookieSessionStorage`, `TValue`, `RedBlackNode`, `MountedHttpHandler`, `SourceFileLike`, `EnhancedGitHubNotification`, `Apollo.SubscriptionHookOptions`, `ActivitySettings`, `FlowView`, `PickResult`, `CesiumLayer`, `WebCryptoFunctionService`, `PDFAcroField`, `NavigationAction`, `AfterGroupCallback`, `IHTMLCollection`, `InternalTakomoProjectConfig`, `MIRInvokeDecl`, `requests.ListPdbConversionHistoryEntriesRequest`, `DescribeCertificateAuthorityAuditReportCommandInput`, `express.Router`, `GetSharedData`, `LogFileParsingState`, `ActivityHeight`, `PackTypeDefinition`, `TagResourceRequest`, `TypeGenerics`, `WalletInitializationBuilder`, `IContentSearchRequest`, `CodegenContext`, `BabelConfigOptions`, `DataInterface`, `ObservableValue`, `Trees`, `XMessageBoxAction`, `DependencyStatus`, `UsersOrganizationsService`, `DependencyInfo`, `React.FormEvent`, `GenericOperation`, `AppApp`, `ListQueuesCommandInput`, `LogFormula`, `Appservice`, `UInt8`, `JQuery.TriggeredEvent`, `IdentifierType`, `CreateResponse`, `Facets`, `ViewerNetworkEventStarted`, `FormEventDetail`, `PDFCatalog`, `ItemElement`, `Blueprint`, `requests.ListKeyVersionsRequest`, `TEDirective`, `RouteProps`, `GeometryType`, `GlobStats`, `QueryLeasesRequest`, `HandlerParamMetadata`, `InputEventMouseButton`, `ICommandManager`, `Fn3`, `Line`, `GetByIdAccountsValidationResult`, `MarkerBase`, `Postable`, `UpdateTableCommandInput`, `InsertChange`, `BackendWasm`, `TestSchemaProcessor`, `PiConceptProperty`, `PeriodData`, `Packet`, `CSSParsedDeclaration`, `INamedObjectSchemaProperty`, `AutowiredOptions`, `SerializedNode`, `GPGPUBinary`, `TypedDocumentNode`, `GraphQLQueryGenerator`, `ObjectValueNode`, `IAuthConfig`, `OfficialAccount`, `Segno`, `Embed`, `AddressBookEntry`, `PipetteNameSpecs`, `StructureMap`, `RedspotArguments`, `PopulatedContent`, `CrochetValue`, `AaiDocument`, `DatabaseInstanceHomeMetricsDefinition`, `InjectorClient`, `NgextConfigResolved`, `NavigationButton`, `ListRecommendationFeedbackCommandInput`, `OciError`, `DataGraph`, `GlobalChartState`, `SubsetCheckResult`, `ClusterClient`, `Radians`, `WebviewTag`, `SendEventCommandInput`, `Prize`, `SimpleInputParamsCommandInput`, `WU`, `QuickInfo`, `Geoposition`, `By2`, `ColumnHeaderOptions`, `ProgressModel`, `CaretPosition`, `QueryImpl`, `JsonEnumsCommandInput`, `fakeDevice.Device`, `FoundationType`, `TransactionMeta`, `UserTimeline`, `ServerTransferStateTranslateLoader`, `EmergencyCoordinates`, `GraphCalculator`, `ITreeDataProvider`, `SecurityService`, `Equaler`, `PieceModel`, `TopNavItem`, `IBackendRequestData`, `yubo.WaveOptions`, `IManualTimeInput`, `DecoratorData`, `UiThread`, `UploaderEnvs`, `BaseModule`, `ImmutablePerson`, `BasicAuthResult`, `td.AppLogger`, `ICoreService`, `PlatformRepositoryService`, `RelativeInjectorLocation`, `IStateProps`, `DeclarationBlockConfig`, `Draggable`, `SheetSpec`, `ProtoJson`, `Finality`, `Information`, `XCommentNode`, `requests.DeleteConnectionRequest`, `IFeatureOrganization`, `PropsWithAs`, `A.App`, `OutgoingHttpHeaders`, `WatchSource`, `IDBOpenDBRequest`, `IResizeState`, `RouteFilterRule`, `On`, `MiddlewareFunction`, `FileAsset`, `ServerArgs`, `TimePickerBase`, `AggConfigs`, `CipherCollectionsRequest`, `UserController`, `SocketIO.Socket`, `ModelSummary`, `ng.IAttributes`, `requests.ListBdsMetastoreConfigurationsRequest`, `ERROR_CODES`, `Fixer`, `ShaderAttributes`, `NextLink`, `AutorestExtensionHost`, `MiniSimulation3D`, `DefaultClause`, `RollupStateMachine`, `CISKubeBenchReport`, `MasterKeySecret`, `Pseudo`, `DateTimeData`, `BaseHandlerCommonOptions`, `AzureComponentConfig`, `IGameState`, `Cat`, `SceneGraphComponent`, `Launch`, `DataLabelOptions`, `Katana`, `ThemeObject`, `VariableParserAST`, `AttributionData`, `Pickability`, `webpack.compilation.Compilation`, `HumanAddr`, `OrganizationalUnitConfig`, `BarService`, `FastifyPluginCallback`, `FirebaseTools`, `ListRowProps`, `SignatureHelpParameter`, `Server`, `CreateDeviceDTO`, `GetCertificateCommandInput`, `DappKitRequestMeta`, `ListEventsRequest`, `RecordDef`, `TableInstance`, `DropTargetMonitor`, `DeleteResult`, `FabricWallet`, `Tick`, `Accelerometer`, `IVec3Term`, `IObservable`, `ActionCodeSettings`, `ElectionMetadata`, `MapMouseEvent`, `SearchRequest`, `LocaleRecord`, `MarkdownProps`, `PropTypeConfig`, `LinkingCrossPlatform`, `JPA.JPAResourceData`, `logging.Level`, `ActionParams`, `IExportedValue`, `ArticleModel`, `ResetDBClusterParameterGroupCommandInput`, `ast.EscapeNode`, `Beacon`, `IMapping`, `OperationDescriptor`, `WetMessage`, `Delete`, `ConfigStorage`, `ShapeOptions`, `ts.BooleanLiteral`, `AssetService`, `BleepsSettings`, `SliderComponent`, `FrameData`, `DomainName`, `EditionsList`, `SimplePubSub`, `ErrorContinuation`, `ImportResolver`, `UnicornInfo`, `AlertInstance`, `d.Workbox`, `AddGroupUsersRequest`, `EventRepository`, `NodeCallback`, `FloatingPanel`, `Reduction`, `ResponsiveQueryContextType`, `EdaColumn`, `ToolchainName`, `TSForIn`, `Editors`, `GradientAngularVelocity`, `SingleResponseModel`, `THREE.Texture`, `VideoCapture`, `InheritanceChain`, `All`, `AtomChevronElement`, `UpdateSubnetGroupCommandInput`, `EnumEntry`, `ScreenReaderSummaryStateProps`, `ParserError`, `OnChildElementIdArg`, `ModifyRelationOptions`, `RoutesMeta`, `PackageChangelog`, `OperationPath`, `Easing`, `IHydrateResult`, `ReaderMiddleware`, `FormValues`, `d.CollectionCompilerMeta`, `VpnClientIPsecParameters`, `TiledMapResource`, `ConstantNode`, `requests.ListNetworkSecurityGroupSecurityRulesRequest`, `GenericThemes`, `SearchStrategyProvider`, `XYAndZ`, `PanelPlugin`, `NodeJS.Timer`, `SflibInstrumentMeta`, `IModelDb`, `FeatureSet`, `ErrorRequestHandler`, `Prog`, `ERC721ContractDetailed`, `CategoricalChartState`, `ScrollBehavior`, `GraphQLResponse`, `IAddMemberContext`, `ClientHello`, `YesNoLimitedUnknown`, `CustomQuery`, `These`, `Top`, `ColumnMetricsObject`, `StorageType`, `IUserInfo`, `PreprocessCollector`, `BitcoinAPI`, `GPUBuffer`, `TagResourceInput`, `SymbolTable`, `CtrOr`, `FlexibleConnectedPositionStrategyOrigin`, `TParams`, `IEntityAction`, `UInt64Value`, `BranchNode`, `FilePreviewModel`, `RuleFn`, `Children`, `lf.query.Select`, `IWatchCallback`, `CombatantInfoEvent`, `InferableComponentEnhancer`, `DatabaseEventBus`, `BlobPart`, `ICreateTableOptions`, `ISearchResponse`, `LocalRepositoryService`, `AnyToVoidFnSignature`, `IModalListInDto`, `CollapsableSidebarContainerState`, `CurrencyFormat`, `CardHeaderProps`, `UrlTree`, `RenderBox`, `IMarker`, `Derivative`, `JGOFMove`, `http.IncomingHttpHeaders`, `MatchedMention`, `ReadableAtom`, `SinonStub`, `CoreAPI`, `TopicsService`, `ViewConverter`, `SearchBar`, `ShallowWrapper`, `ESTree.CallExpression`, `DayResults`, `InputModel`, `PageG2Type`, `IOrganizationRecurringExpenseFindInput`, `PivotAggsConfig`, `TreeBranch`, `StepExpr`, `FileSystemProviderWithFileReadWriteCapability`, `CommandLineStringListParameter`, `Core`, `ISagaModule`, `INavNodeFolderTransform`, `CmsEditorFieldTypePlugin`, `TRejector`, `PipelineDescriptor`, `LibSdbTypes.Contract`, `VertexEntry`, `SpatialAudioSeat`, `SqsMetricChange`, `StoryApi`, `ts.Node`, `IIMenuState`, `ScanGameFile`, `BMP24`, `MIPS.Register`, `IOpenSearchDashboardsMigrator`, `OperationsListOptionalParams`, `CdtFrontElement`, `CodeError`, `Await`, `DataKey`, `UberToggleState`, `CancelToken`, `StatsTree`, `Msg`, `CreateChannelResponse`, `DTMock`, `PhotoData.PhotoDataStructure`, `CSVDataImporter`, `FileWatcherEventType`, `http.ServerResponse`, `Linter.Config`, `EntryProps`, `IJob`, `BlockGroup`, `LoginInput`, `CfnIntegration`, `AsyncQueue`, `PlatformConfig`, `TicTacToeAppState`, `ResolvedPos`, `DeleteDBSubnetGroupCommandInput`, `CustomCallAst`, `ProxyNode`, `requests.ListExadataInfrastructuresRequest`, `AsyncQueryable`, `DescribeParametersCommandInput`, `ECA`, `RNN`, `PreCheckerClient`, `AspectRatioType`, `InputEventType`, `ExpressionAstExpression`, `PiClassifier`, `ReportingUser`, `GoogleMeetSegmentationOperationParams`, `IBlockHeader`, `FungiblePostCondition`, `TimelineElement`, `LocalDataProvider`, `BoundFrustum`, `TooltipInitialState`, `TreeEntry`, `OptionFC`, `Events.hidden`, `TexturePalette`, `PopupService`, `FileStorageOption`, `SentinelType`, `SpectatorFactory`, `ExpandResult`, `AnyConstructor`, `TileDoc`, `SinkBehavior`, `HttpClientRequestConfig`, `BookModel`, `CrawlerDomain`, `DeploymentParams`, `Subgraph`, `QueryDetails`, `requests.GetAllDrgAttachmentsRequest`, `GraphQLInputFieldConfigMap`, `PendingQueryItem`, `JConfiguration`, `DistinctValuesRpcRequestOptions`, `EstimateGasOptions`, `ChangeUserLanguageDto`, `ProcessMainAdapter`, `IUrl`, `PutAppInstanceRetentionSettingsCommandInput`, `UserIdDTO`, `puppeteer.ClickOptions`, `Pose2DMap`, `LazyBundleRuntimeData`, `DescribeFlowCommandInput`, `ConnectionInfo`, `Quota`, `IChangeInfoHash`, `IOptionsService`, `TwingNode`, `ExpNumUop`, `FillerHook`, `SimplifiedParameterType`, `mongoListener`, `OpenAPI.HttpOperation`, `TFieldName`, `DOMWidgetView`, `DynamoDBClient`, `EventHub`, `ListingType`, `RaycasterService`, `SSRContext`, `UpdateEntry`, `Importer`, `ForestNode`, `FormRowModel`, `ParticleEmitterWrapper`, `PanelState`, `PlatformInformation`, `LayerVariable`, `FileData`, `AreaService`, `UpdateThemeCommandInput`, `FileWatcherProvider`, `PvsContextDescriptor`, `VersionHistory`, `TelemetryContext`, `TableProps`, `CompoundStatementContext`, `Nonce`, `Fun`, `Markets`, `ComponentTypeTree`, `NonFungibleConditionCode`, `TagCreator`, `requests.ListFindingsRequest`, `IOutput`, `ToastProvider`, `WalletContextState`, `SectionConfig`, `IInteraction`, `AllQueryStringTypesCommandInput`, `TypedArrayConstructor`, `OrganizationModel`, `EntityActionPayload`, `IQueryBus`, `PageSort`, `ApplicationContract`, `CalendarView`, `NeuralNetwork`, `FeatureNode`, `GraphModel`, `ServerCancellationToken`, `ShaderMaterial`, `MainWindow`, `QueryEngineConfig`, `Relay`, `InstructionWithText`, `FormatMetadata`, `BuildifierConfiguration`, `GPUShaderModule`, `J3DModelInstance`, `IPlotState`, `PrivateKeyPEM`, `Keys`, `LoaderResource`, `TransitionSpiral3d`, `MatListOption`, `NotebookCell`, `IntrospectionEngine`, `SessionContext`, `coreRestPipeline.RequestBodyType`, `IVocabularyItem`, `NzSelectItemInterface`, `IRemovalInfo`, `BasePacket`, `ConnectedAccount`, `DescribeDBEngineVersionsCommandInput`, `StripePaymentListener`, `ExtendableBox`, `Exclude`, `JQuery.ClickEvent`, `BlockModel.Resolved`, `JsonSchemaRootAssertion`, `grpc.Request`, `AsyncArray`, `ConnectionSummary`, `CompiledPredicate`, `DateSpan`, `Interior`, `JRPCEngineReturnHandler`, `IsSelectableField`, `StoreTypes`, `TextLiteralContext`, `MetadataCacheResult`, `ExpressionsService`, `OpMapper`, `ConfigRepository`, `ResolverInput`, `XTermMessage`, `IHookStateInitAction`, `T.RenderFunction`, `ActivityRequestData`, `ResolverFactory`, `BezierPoints`, `PerformRenameArgs`, `DescribeClusterCommandInput`, `FieldValidator`, `TrialVisit`, `ITab`, `IVerificationGeneratorDependencies`, `IsDeletedEventPipe`, `AtlasResourceItem`, `MangoGroup`, `EosioContractRow`, `Verifiable`, `NowBuildError`, `FinderPattern`, `DecompositionResult`, `PerformReadArgs`, `RegisterInstanceCommandInput`, `ObjectTypeMetadata`, `AvailableFilter`, `RecursiveShapesCommandInput`, `TwingSource`, `DaffCartFacade`, `TootDetailState`, `IRadioGroupProps`, `Swarm`, `KBService`, `PositionComponent`, `JSONIngestionEvent`, `JsonFormsCore`, `GetPredicateParams`, `ValidateEvent`, `StorableUser`, `Sampler`, `TxCreate2Transfer`, `InputTokenObject`, `OvSettingsModel`, `GX.DistAttnFunction`, `BuildConfig`, `FileNode`, `KeywordErrorDefinition`, `WorkspaceEdit`, `InputOnChangeData`, `NativeScriptPager`, `DeviceDetectorService`, `CustomPropertyDecorator`, `HttpsProxyAgent`, `Arc`, `NodeProps`, `GridProps`, `Approval`, `SpawnOptionsWithoutStdio`, `HashCounter`, `RatioMetric`, `VerificationRule`, `TagEntity`, `NSString`, `UID`, `CompilerSystem`, `ARCommonNode`, `UnderlyingAsset`, `PartialMessageState`, `TheSagaStepfunctionSingleTableStack`, `ValidatorSpec`, `AuditLogger`, `FunctionEntity`, `BreadcrumbProps`, `moq.IMock`, `AppStatusStore`, `InvertedIndex`, `SpriteAssetPub`, `ByteSizeValue`, `BaseChartisan`, `Timesheet`, `PenroseState`, `UserConfiguredActionConnector`, `AuthService`, `ClientTipsData`, `GeoNode`, `NotificationType0`, `DayPickerProps`, `SignerWithAddress`, `D3_SELECTION`, `ClassSelector`, `ReplyMsgType`, `TensorBuffer`, `QueryCallbacksFor`, `AlertContentProps`, `TagResourceResult`, `AutoBounds`, `Conflict`, `TripleObject`, `IdOrSym`, `CLI_OPTS`, `TorrentState`, `WIPLWebpackTestCompiler`, `P2WPKHTransactionBuilder`, `PreviewState`, `ItemInfo`, `HostRule`, `EcsEvent`, `UpdateExpressionDefinitionChain`, `wjson.MetricWidgetAnnotationsJson`, `CopyAsOrgModeOptions`, `RegName`, `React.KeyboardEvent`, `VNodeThunk`, `MatchExpr`, `GenericCall`, `StatusIndicatorProps`, `TLayoutSize`, `GeoPosition`, `createStore.MockStore`, `ActionHandlerRegistry`, `ResolvedType`, `requests.ListTargetDatabasesRequest`, `Drop`, `TableItem`, `EncodedMessage`, `AmqpConnectionManager`, `connection`, `HubstaffService`, `CoreFeatures`, `IonicApp`, `GeneratorContext`, `d.CompilerFileWatcherCallback`, `ListOrganizationAdminAccountsCommandInput`, `OAuthToken`, `CreateGroupRequest`, `Func0`, `OneOrMany`, `P.Parser`, `RadixParticleGroup`, `ToggleComponent`, `Type`, `CredentialRepresentation`, `JSONSchemaAttributes`, `DiscoveryService`, `TargetLanguage`, `HeftConfiguration`, `ABLTempTable`, `BoundsOctreeNode`, `GF`, `CashScriptVisitor`, `DocumentationLink`, `CoverageFlatFragment`, `MeshBuffers`, `UploadTask`, `PlayState`, `SpaceUser`, `DataServiceConfig`, `Signale`, `GraphSignedTransferAppState`, `Types.Config`, `PiContainerDescriptor`, `Minimum`, `CanvasTheme`, `ShowProjectService`, `TopicStatus`, `InputFile`, `TrackedEither`, `ts.SwitchStatement`, `IDBFactory`, `ProgressCallback`, `Weave`, `RelationalOperatorConfig`, `HTTPError`, `IRoute.IParameter`, `Matrix3d`, `AbortedCallback`, `HsConfig`, `IFetchedData`, `BlockAttributes`, `Commitment`, `TlsConfig`, `SidenavMenu`, `AppOptions`, `PluginHost`, `JSONEditorSchema`, `CreateProjectCommandOutput`, `PartyMatchmakerRemove`, `LeaderboardRecord`, `BasePath`, `Flap`, `ModuleResolutionState`, `Graphics.BlendOperation`, `VirtualNode`, `TClass`, `AttributeValueChoiceOption`, `ExpShapeSlice`, `IndexOp`, `ListUserGroupsRequest`, `TimePointIndex`, `Classes`, `Y.Doc`, `Styles`, `AzureFileHandler`, `PluginInstance`, `MarketInfo`, `ClarityAbi`, `CheckboxState`, `TextNode`, `MockPointOptions`, `ChipColor`, `INetworkInfoFeatureDependency`, `WetAppBridge`, `IncomingForm`, `ODataQuery`, `IRuleSpecObj`, `ISkill`, `UnwrapRef`, `FileRecord`, `TemplateParam`, `DaffCategoryFilterEqualToggleRequest`, `fixtures.Fixtures`, `SfdxFalconErrorRenderOptions`, `L.Property`, `UseLiveRegionConfig`, `VariantCurveExtendParameter`, `AppGachaItem`, `InversionFix`, `ModelPlayer`, `IMapState`, `TextElementFilter`, `DaffCategoryFilterRequest`, `MetadataScanner`, `RegSuitCore`, `ast.Name`, `ScalarParamNameContext`, `EventHandler`, `StreamHead`, `IHistory`, `CubieCube`, `TypedArrays`, `ProblemDimension`, `ISettingRegistry`, `MicrosoftDevTestLabLabsResources`, `FormatFlags`, `zowe.IUploadOptions`, `WorkRequestSummary`, `BasicAcceptedElems`, `CreateDomainResponse`, `IWorkspace`, `TestElementProps`, `ParseParams`, `FibaroVenetianBlindCCGet`, `CaseUserActionsResponse`, `UnitOfMeasurement`, `IRichPropertyValue`, `PublicTransition`, `PluginPositionFn`, `ActionTreeItem`, `CustomerState`, `t.STStyle`, `StackedRNNCellsArgs`, `InputMessage`, `ParsedRepo`, `ListSecurityProfilesCommandInput`, `ServerRequest`, `ListEnvironmentsCommandOutput`, `NameObj`, `IconName`, `CoverageMap`, `SharedFunctionCollection`, `OptionDefinition`, `CpuRegister.Code`, `MessageHashService`, `Blockly.Workspace`, `InjectableMetadata`, `ResourceValue`, `Mesh2D`, `EuiBasicTableColumn`, `IToolbarDialogAddonHandler`, `DescribeResourceCommandInput`, `ThyAbstractOverlayPosition`, `PostprocessSetOptions`, `StackInspector`, `ModuleNameAndType`, `EllipsisNode`, `Protobuf.Type`, `EntityLoaderOptions`, `DocumentWatcher`, `BrowserState`, `float`, `Outputs`, `MapAnchor`, `DescribeAddressesCommandInput`, `LinesChangeEvent`, `Percentage`, `Pause`, `DocumentOnTypeFormattingParams`, `IDBPTransaction`, `InterfaceCombinator`, `SerializedFieldFormat`, `NodeCollection`, `DropdownListItem`, `ProblemLocation`, `LexerContext`, `BlockEntity`, `NotificationPayload`, `LiveAnnouncer`, `Calendar_Contracts.IEventCategory`, `HandlerArgs`, `RelativePattern`, `WriteStream`, `INotesGetByContactState`, `Done`, `CesiumService`, `RTCSessionDescription`, `MethodAbi`, `OptimizeJsResult`, `LocationHelper`, `CtrAnd`, `IQuizQuestion`, `SelectionModelConfig`, `PluginService`, `ISpacesClient`, `ChartComposition`, `QuerySolution`, `FormatterProps`, `RichRemoteProvider`, `CachedItem`, `ContentEditableEvent`, `HostSchema`, `UISchemaElement`, `ESLintNode`, `MDCRipple`, `IInput`, `GfxBindingsDescriptor`, `ExtendedPoint`, `FilterData`, `RpcMessagePort`, `SoloOptions`, `RnnStepFunction`, `DeployBundle`, `AnyBuildOrder`, `GlobalModelState`, `TComponentConfig`, `AggregateColumnModel`, `FormSchema`, `RawSavedDashboardPanel640To720`, `ListManagementAgentsRequest`, `Schemas`, `ParameterNode`, `RenderContainer`, `ISPListItems`, `IActivity`, `types.IDBRow`, `NightwatchBrowser`, `ConfigModule`, `ServiceHealthStatus`, `DataTransferItemList`, `Conv3D`, `InAppBrowserObject`, `IMenuItemInfo`, `CapabilitiesResolver`, `GroupEntity`, `ResolveContext`, `TapoDeviceKey`, `CommonTypes.NotificationTypes.LastKnown`, `ThyGuiderManager`, `RoomService`, `SetupApp`, `WishlistState`, `ExpString`, `ExportCollector`, `SystemHealth`, `BindingForm`, `Ng2SmartTableComponent`, `DictionaryNode`, `GroupItemDef`, `TimerService`, `CopyDBParameterGroupCommandInput`, `DataTable.Row`, `WithUserAuthOptions`, `PaymentService`, `RequestorHelper`, `DeleteSecurityConfigurationCommandInput`, `THREE.Quaternion`, `LocaleOptions`, `IEventSource`, `requests.ListDbSystemShapesRequest`, `ColumnsType`, `SupportedModels`, `GetDirsOrFilesOptions`, `DoomsdayDevice`, `CreateProjectResponse`, `HeaderRepository`, `ArrowCallableNode`, `Regex`, `CoverageRunner`, `DeleteDBParameterGroupCommandInput`, `L1Args`, `ConfigurableCreateInfo`, `RepoCommitPathRange`, `UpdateClusterCommandInput`, `INodePackageJson`, `ReviewItem`, `MongoPagination`, `IPatchRecorder`, `DryadPlayer`, `ProtractorExpectedConditions`, `CommentDto`, `MeetingEvent`, `GroupButton`, `TNodeType`, `ImageConfig`, `PropertyValueRendererContext`, `ScreenshotOptions`, `requests.ListMigrationsRequest`, `AnimationOptions`, `UserService`, `SimpleClass`, `AnimationMixer`, `LiveAtlasWorldDefinition`, `StableTokenInstance`, `BlueprintInfo`, `BitSet`, `DocumentContext`, `VectorStage`, `PartialStepState`, `NotificationCCAPI`, `position`, `JwtService`, `BitWriter`, `GeneratedIdentifierFlags`, `LayerWizard`, `HttpResult`, `xLuceneFieldType`, `S3PersistenceAdapter`, `SlugifyConfig`, `ScryptedNativeId`, `StixObject`, `Ending`, `FeatureDefinition`, `FakeConfiguration`, `SoftwareSourceId`, `ICompletionItem`, `FieldFilterRowData`, `MediaExtended`, `RouteState`, `IWatchExpressionFn`, `Core.Color`, `UnitProps`, `ElementSelector`, `web3ReactInterface`, `AsyncFunction`, `LimitLeafCounter`, `int`, `Vidi`, `CmbInstance`, `CPU6502`, `ScannedElementReference`, `GoToOperation`, `AccountsModel`, `protos.common.CollectionConfigPackage`, `AN`, `CollectorState`, `RouteRecordRaw`, `ValidationQueueItem`, `Cypress.Chainable`, `ExternalSource`, `CoinTransfer`, `Nodes.ASTNode`, `ListPermissionsCommandInput`, `IAttributeData`, `IConnectionParams`, `Prisma.SortOrder`, `VirtualNetworkWaiter`, `CatalogEntry`, `ArrayNode`, `HSD_JObjRoot_Instance`, `SpecificWindowEventListener`, `RepaymentRouterContract`, `cg.Key`, `SizeWithAspect`, `Branch`, `ConversionFunction`, `IDroppableItem`, `HJPlayerConfig`, `GLSL`, `BaseContractMethod`, `FilterExcludingWhere`, `IndicatorObject`, `AsyncResource`, `UiSettingsDefaultsClient`, `InternalCoreStart`, `LinkDownload`, `Adapters`, `ReadyValue`, `AuthStorage`, `WorkboxService`, `TestKernelBackend`, `io.WeightsManifestConfig`, `CmsGroupPlugin`, `NamedTensorsMap`, `AboutComponent`, `HSD_JObj_Instance`, `WorkbenchPageObject`, `Range2d`, `SimulatedPortfolio`, `CaseStyle`, `ArtifactVersion`, `ReplayTick`, `PaymentInformation`, `Lanes`, `ExtendedBlock`, `WildlingCard`, `RuntimePlugin`, `ServerClass`, `ElementRect`, `ConditionalDeviceConfig`, `IXPath`, `Noise`, `ComponentFramework.Dictionary`, `MetaTagModel`, `DenseLayerArgs`, `CdkOption`, `LayerName`, `LegendLocationSettingsProps`, `TemplateLiteralType`, `TimelineKeyframe`, `MathjaxAdaptor`, `PopupState`, `ValueIterator`, `IDecodePackage`, `SignaturePubkeyPair`, `LinkedNodeList`, `DocViewRenderProps`, `OrderedIterable`, `EdgeType`, `WidgetProps`, `ErrorCodeDefinition`, `IContainerProps`, `FetchVideosActions`, `ITaskFolder`, `Apdex`, `window.ShellWindow`, `THREE.Group`, `InPacketBase`, `FailureEventData`, `DealCriteria`, `QueryNameContext`, `QueryOne`, `TypeDescriptor`, `IZosmfTsoResponse`, `JasmineBeforeAfterFn`, `ICacheItem`, `TileTextElements`, `FlashcardFieldName`, `AccountGoogle`, `CustomArea`, `OperationOptions`, `BrowseResult`, `NotificationPressAction`, `TColumnRowPair`, `d.Config`, `Modifiable`, `GeneratedCodeInfo_Annotation`, `RenderArgsDeserialized`, `_Explainer`, `OrganizationPolicy`, `IngameGameState`, `SphereColliderShape`, `IChapter`, `TraceStep`, `DragItem`, `IFBXConnections`, `GitRevisionReference`, `GroupUserEditResponse`, `ConfigLoaderResult`, `FieldError`, `DefaultSDP`, `IVarAD`, `tinyapp.PageOptions`, `BrowserFftSpeechCommandRecognizer`, `TAuthUserInfo`, `CodeMirrorAdapter`, `IFruit`, `ContextEntry`, `ITreeItem`, `MerchantUserEntity`, `EventFragment`, `NodeTracerProvider`, `OpOrData`, `Fix`, `PaneInvalidation`, `SpaceBonus.STEEL`, `StickyDirection`, `ICXOffer`, `PercentLength`, `DescribeChannelModeratorCommandInput`, `CopyDBClusterParameterGroupCommandInput`, `ListTablesCommandInput`, `SteamDeviceReport`, `TransferOptions`, `FabricIdentity`, `TextAreaCommandOrchestrator`, `Integer64`, `SafeBlockService`, `Trigger`, `IViewportInfo`, `MailOptions`, `BiquadFilter`, `ControllerMeta`, `Instance`, `ProjectExport`, `_CollectorCallback2D`, `ReflectionCategory`, `ISiteScriptAction`, `ConditionExpressionDefinitionFunction`, `WorkingService`, `FlatConvectorModel`, `HomeService`, `UnitFormatOptions`, `MappingEvent`, `RouteObject`, `VectorOptions`, `SandboxType`, `VpnConnection`, `SignedStateWithHash`, `AsyncComponent`, `PageScrollInstance`, `TxBroadcastResult`, `HierarchicalFilter`, `MetricTypes`, `SignupDTO`, `ng.IAugmentedJQuery`, `ApiQueryOptions`, `tcp.ConnectionInfo`, `CurriedFunction2`, `NodeKind`, `EngineConfig`, `PreventAny`, `Condition`, `tf.TensorBuffer`, `SetupFn`, `OrganizationTeamsService`, `StructuredTypeSchema`, `FormattingContext`, `TInstruction`, `ArrayPaginationService`, `BindingDef`, `PsbtInputData`, `PopoverContextOptions`, `MDCTopAppBarBaseFoundation`, `PoolCache`, `MonzoPotResponse`, `HttpClient`, `ColumnsContextProps`, `DescribeReplicationConfigurationTemplatesCommandInput`, `OrganizationMembershipProps`, `ABLVariable`, `Granularity`, `TermsIndexPatternColumn`, `SessionStorageCookieOptions`, `Format`, `ContractVerificationInput`, `ScrollHooks`, `Database`, `ProductResult`, `Dayjs`, `NcPage`, `ArgumentCheck`, `theia.CancellationToken`, `Lines`, `PriorityListGroup`, `CloudDirectorConfig`, `dayjs.ConfigType`, `ScmRepository`, `ODataApi`, `Bias`, `IpcPacket`, `IExportData`, `HasId`, `flatbuffers.Builder`, `BungieGroupMember`, `ListTagsResponse`, `UpToDateStatus`, `CpuRegister`, `WriteStorageObjectsRequest`, `TwingEnvironment`, `RushCommandLineParser`, `A`, `StyleProps`, `SeedAndMnemonic`, `LabelValues`, `OnCancelFunc`, `ErrorHandlingResult`, `ECSComponentInterface`, `UpdateOpts`, `FindCharacterMotion`, `GeneratorError`, `ThyTransferItem`, `requests.ListDataSafePrivateEndpointsRequest`, `IMenuItemConfig`, `requests.ListCloudVmClustersRequest`, `Stroke`, `GameFeatureObject`, `GXMaterialHelperGfx`, `ReadModelStoreImpl`, `ManagedFocusTrap`, `BuildStyleUpdate`, `VirtualGroup`, `IAggFuncParams`, `CreateMockOptions`, `ChartHookReturnType`, `LockMode`, `FeedQueryVariables`, `TsickleIssue1009`, `IRequest.Options`, `ModelField`, `AggParamType`, `GetSpaceEnvironmentParams`, `MemberEntity`, `ActionConnector`, `UiStateStorage`, `ListField.Value`, `DQLSyntaxErrorData`, `SaladTheme`, `TokenService`, `MessageViewProps`, `PotentialApiResult`, `IQueueRow`, `providers.BaseProvider`, `TestInfo`, `CompilerJsDocTagInfo`, `ManifestEditor`, `App.services.IPrivateBrowsingService`, `KubernetesObject`, `IResourceEntity`, `CrochetTrait`, `ZipkinSpan`, `DeleteRuleGroupCommandInput`, `ErrorObservable`, `ContractName`, `TelemetryEvent`, `PointData`, `IOSProjectConfig`, `JourneyStage`, `ResponseDataAccessor`, `FunctionEnvelope`, `IEncoder`, `IPatchData`, `AudienceOverviewWidgetOptions`, `T.MachineEvent`, `NavigateToItem`, `SecurityTokenAdapter`, `Paged`, `MangoQuery`, `BuildDecoratorCommand`, `AthleteModel`, `JsonOutput`, `RequiredParams`, `MalFunc`, `EventList`, `NotebookCellData`, `ts.CompletionEntry`, `MethodWriter`, `OutModeDirection`, `PageDoc`, `FoldingContext`, `WifDecodeResult`, `EventFetcher`, `NetworkError`, `NativeTexture`, `HighPrecisionLineMaterial`, `ImageFormat`, `PddlConfiguration`, `RouteMap`, `Interception`, `LoginDto`, `ConnectorProps`, `IMenuContext`, `PostCombatGameState`, `WidgetsRegister`, `ChainState`, `IInviteAcceptInput`, `SimpleTypeFunctionParameter`, `IConfigData`, `GovernObservableGovernor`, `CornerMap`, `FoundOrNot`, `FramesType`, `IObserverLocator`, `DisabledTimeFn`, `ListOfferingsCommandInput`, `MenuState`, `MDCShapeCategory`, `KeyringTrace`, `UnionType`, `ListServicesCommandInput`, `PadId`, `Bignum`, `S3Object`, `SObjectDefinition`, `InterfaceNamespaceTest`, `NuxtApp`, `SchemaMetadata`, `FunnelCorrelation`, `CacheService`, `ItBlock`, `DataSourceTileList`, `CtrLte`, `Breadcrumbs`, `BifrostRemoteUser`, `PhysicsComponent`, `StackTrace`, `GeneratorConfig`, `Comments`, `Eof`, `EventReporter`, `ButtonBaseProps`, `EntitySelectors`, `PromoCarouselOptions`, `LocationDescriptorObject`, `DOMStringMap`, `OpenOrders`, `AppCurrency`, `FunctionCallNode`, `TableEvent`, `PlasmicComponentLoader`, `GetDeliverabilityDashboardOptionsCommandInput`, `three.Geometry`, `ASTPath`, `AnyImportOrRequireStatement`, `PlayerChoice`, `ConfigurationCCReport`, `FileStatusResult`, `InputChart`, `Username`, `XmlDocument`, `DatasourceConfig`, `LinkLabelsViewModelSpec`, `AuditoryDescription`, `DAL.DEVICE_ID_SYSTEM_LEVEL_DETECTOR`, `ColorPickerItem`, `LoginResponse`, `BlobsModel`, `Interface2`, `CounterService`, `LocationMarkModel`, `AWSContext`, `CreateCatDto`, `GraphcisElement`, `cc.AudioClip`, `NodejsFunction`, `LoggerSink`, `EmbeddedRegion`, `ProgressUpdate`, `EncryptedMessageWithNonce`, `StatePathsMap`, `DeploymentTemplateDoc`, `AssignmentExpressionNode`, `WaiterResult`, `IStaticMetadata`, `CacheMap`, `T12`, `turkInformation`, `SegmentBase`, `UnsubscribeCommandInput`, `ParseStream`, `SchemaUnions`, `ClozeRange`, `IStoredTransaction`, `CardModel`, `CopyLongTermRetentionBackupParameters`, `LogLevelType`, `Tspan`, `EventsService`, `ShurikenParticleSystem`, `WebviewPanel`, `LineUp`, `Electron.MessageBoxReturnValue`, `ESLPanel`, `HleFile`, `PuzzleGeometry`, `ISODate`, `PeriodicWave`, `StepGenerator`, `Lint.IOptions`, `requests.ListAvailablePackagesForManagedInstanceRequest`, `MessagesPageStateModel`, `Referenceables`, `FetchHandle`, `ColorDynamicStylePropertyDescriptor`, `UICollectionViewLayoutAttributes`, `PatternEnumProperty`, `EuiSwitchEvent`, `IScope`, `Hover`, `THREE.Material`, `IRadio`, `AnyResponse`, `RunGroupProgress`, `PathObject`, `RedirectPolicy`, `Platforms`, `QueryArgDefinition`, `CreateQueueCommandInput`, `PartyMatchmakerTicket`, `Frequency`, `FileType`, `DecodedOffset`, `view.View`, `OrdenationType`, `MaterialLayer`, `ScreenOptions`, `IRenderableColumn`, `ProjectQuery`, `puppeteer.ScreenshotOptions`, `Animated`, `IFunctionAppWizardContext`, `AbstractElement`, `SaveEntitiesCancel`, `RenderServiceMock`, `AssetDetails`, `ClientContext`, `StakingBuilder`, `GameMap`, `AcceptPaymentRequest`, `Schema`, `DictionaryExpandEntryNode`, `IOrg`, `TreeNodeInterface`, `BSTProcess`, `UnitTypes`, `GotResponse`, `RealFileSystem`, `IListenerDescription`, `CaptureOptions`, `ChromeBadge`, `LazyBundlesRuntimeData`, `HighlighterOptions`, `CompositionEvent`, `IBetaState`, `ChannelMetadataObject`, `TextureCubeMap`, `ts.TranspileOptions`, `Sku`, `TokenIndexedCoinTransferMap`, `IO`, `RecordSourceProxy`, `ListTagsForResourcesCommandInput`, `Sprite`, `EyeProps`, `RtmpOutput`, `WriteBuffer`, `HSD_TETev`, `RawValue`, `vscode.CancellationToken`, `AppUpdater`, `IGatewayMemberXmpp`, `TFLiteWebModelRunnerTensorInfo`, `MarkerData`, `ValueMap`, `IApiSourceResult`, `IRichTextObjectItem`, `RoomBridgeStoreEntry`, `PluralRules`, `FocusOptions`, `TaskRunnerCallback`, `AuthenticateGameCenterRequest`, `SVObject`, `BaseAdapter`, `UpdateAccountSettingsCommandInput`, `PutBucketLifecycleConfigurationCommandInput`, `RequestId`, `IWidget`, `IBrowser`, `VirtualKeyboard`, `TransformResult`, `ActionBinding`, `BaseLayer`, `MeetingAdapter`, `IJsonSchema`, `HammerInputExt`, `ExecutionPathProps`, `LinterConfig`, `CombatZerg`, `PromisifiedStorage`, `GetLaunchConfigurationCommandInput`, `TestScriptErrorMapper`, `PolyfaceData`, `StyleResources`, `IControllerAttributeProvider`, `ESLImage`, `Evaluate`, `RollupChunkResult`, `IStashEntry`, `FileSystemState`, `TopicsData`, `SdkError`, `AssignmentPattern`, `OrderWithContract`, `SqrlExecutionState`, `Game`, `google.maps.Map`, `MemberDescriptor`, `AnswerType`, `CanvasImageSource`, `PackageInstructionsBlock`, `ReduxStoreState`, `BrokerConfig`, `ConnectionConfig`, `IFindWhereQuery`, `AutorestNormalizedConfiguration`, `AccountManager`, `AssessmentData`, `CacheEntryListener`, `UIPreparationStorage`, `Case`, `ZRC2Token`, `Sector`, `ByteBuffer`, `IModelBaseHandler`, `TheWitnessGlobals`, `LayerArgs`, `SquireType`, `RequestState`, `UpdateWebACLCommandInput`, `TypedMessage`, `IntrospectionField`, `Http3PMeenanNode`, `NzThItemInterface`, `ActivityAudience`, `PreReqView`, `PageInstance`, `EnsuredMountedHTMLElement`, `AtomState`, `StravaActivityModel`, `IServiceParams`, `INameAtom`, `ExplorerView`, `SEdge`, `VSTS`, `ReconnectingWebSocket`, `TreeNodeComponent`, `android.view.View`, `SpeechSynthesisVoice`, `ClientEngineType`, `TargomoClient`, `ClassMethod`, `SessionPromise`, `StaffTuning`, `DaffCategoryFilterRequestRangeNumericFactory`, `FilterGroup`, `ActivityPubActor`, `DocumentView`, `DisconnectionEvent`, `IRestClientResponse`, `BackgroundProps`, `TypeObject`, `EyeglassOptions`, `d.ComponentRuntimeMetaCompact`, `Example`, `QuerySuggestionGetFnArgs`, `ParamInfo`, `FieldFormat`, `PutImageCommandInput`, `TimeBucketsInterval`, `FsWatchResults`, `StatusView`, `KVPair`, `AnimationTransform3D`, `TestEvent`, `PersistedData`, `CreateNote`, `DescribeDatasetCommandOutput`, `AxisDependency`, `ExpectStatic`, `sdk.AudioConfig`, `Node.Traversal`, `MatchJoin_MetadataEntry`, `Tree`, `IDesk`, `Merchant`, `JWKStore`, `B7`, `RoleRepository`, `TextOpComponent`, `UnitFactors`, `requests.ListEventsRequest`, `RequestOptions`, `ReplicationConfiguration`, `SavedObjectComparator`, `V1Prometheusrule`, `ConnectionID`, `CreateJobRequest`, `EdgeNode`, `StatesOptionsKey`, `Site`, `J3DFrameCtrl`, `ServiceQuotaExceededException`, `ResourcesFile`, `MochaDone`, `CreateRangeChartParams`, `DisabledDateFn`, `TViewNode`, `Chunk`, `MetadataService`, `AccountRipplePaymentsConfig`, `ConstructorFuncWithSchema`, `DeploymentParametersDoc`, `ResolvedElementMove`, `Repertoire`, `IntersectionC`, `CommandResponse`, `AggregateResponse`, `IWorkflowExecutionDataProcess`, `SqrlRuleSlot`, `PushpinUrl`, `BooleanFilter`, `_Props`, `IfNotExistsContext`, `ForgeModInput`, `CraftTextRun`, `ReactVisTypeOptions`, `TorrentInfo.MediaTags`, `FeatureEdges`, `GitData`, `AuthRequired`, `MousePosition`, `AwsRegion`, `FaastModule`, `backend_util.Activation`, `ListDomainsResponse`, `IMyDpOptions`, `NgSourceFile`, `WalletType`, `IFormField`, `PouchDB`, `ConfigType`, `FileWatcher`, `AggResponseBucket`, `LineCollection`, `RendererType2`, `InputRegisterMaster`, `WebGLResourceRepository`, `Spark`, `IVssRestClientOptions`, `Add`, `BaseInternalProps`, `DescribePendingMaintenanceActionsCommandInput`, `ExtensionProvider`, `StylesConfig`, `FileSystemWatcher`, `C1`, `App.windows.window.IMenu`, `ExtensionPriority`, `InjectCtx`, `ChartsState`, `MediaSlotInfo`, `AdonisRcFile`, `RegistryClient`, `ast.CallNode`, `TypedTransaction`, `ApimService`, `FormattedTransactionType`, `TranspileModuleResults`, `AbstractSession`, `SyntaxNode`, `ReviewerRepository`, `LocationCalculator`, `InsertQueryNode`, `StoredState`, `BoardTheme`, `BFS_Config`, `ScopeFn`, `AST.Expression`, `SeedFile`, `C4`, `G2`, `GasParameters`, `BaseClass`, `VuexModuleOptions`, `apid.CreateNewRecordedOption`, `MdcSnackbarContainer`, `TileFeatureData`, `FlatScancode`, `VFileMessage`, `IIndex`, `SelectionChange`, `angular.IRootScopeService`, `NodeFetchHttpClient`, `Fp`, `providers.TransactionRequest`, `FunctionDeclaration`, `ReactiveChartDispatchProps`, `BlockhashAndFeeCalculator`, `LhcDataService`, `CommonTerminalEnum`, `PolarData`, `MockDocument`, `DetectorConfiguration`, `C8`, `X12QueryEngine`, `SimpleUnaryImpl`, `AssignableDisplayObjectProperties`, `PluginsStatusService`, `CollectionReturnValue`, `PortalService`, `ICommonCodeEditor`, `CommandFlag`, `AttributeIds`, `ModalFlavor`, `IMetricAlarmDimension`, `IResourceItems`, `pw.Frame`, `AggParam`, `ReactLike`, `RefactoringsByFilePath`, `IDataIO`, `MailService`, `MockFixture`, `Installation`, `BytesLike`, `MonzoBalanceResponse`, `ListPipelinesCommandInput`, `DiscoverSidebarProps`, `Series`, `CompositionContext`, `Canvas`, `Spinnies`, `ZoneChangeWhisperModel`, `d.PixelMatchInput`, `MemAttribute`, `AirUnpacker`, `PersistItem`, `AsExpression`, `FilePathPosition`, `PrimitiveValueExpression`, `ListTagsCommandInput`, `BackgroundBlurVideoFrameProcessorObserver`, `JSESheet`, `requests.ListWaasPoliciesRequest`, `IHeaders`, `Int32Value`, `HistoryRecord`, `HealthStatus`, `StackFn`, `ResultState`, `LoadingIndicatorProps`, `FetchHttpClient`, `CalendarEventsCache`, `ServiceClass`, `WebXRSystem`, `ScrollDispatcher`, `NodeVo`, `IChannel`, `DeleteBotVersionCommandInput`, `PutLoggingConfigurationCommandInput`, `ClClient`, `StringPublicKey`, `ModalController`, `Shader`, `TableColumns`, `Sub`, `IActionArgs`, `ResourceService`, `playwright.Page`, `ICDN`, `LocalizedError`, `GraphQLNonNull`, `ResourceAlreadyExistsException`, `OrderedAsyncIterableBaseX`, `Core.Position`, `ComponentLookupSpec`, `EntityTree`, `AuthStore`, `Join`, `napa.zone.Zone`, `XUL.tabBrowser`, `dataStructures.BufferMap`, `PriorityCollectionEntry`, `IUploadOptions`, `WidgetDescription`, `DateTimeNode`, `OffscreenCanvasRenderingContext2D`, `DogRepresentation`, `IWriter`, `ExpandGroupingPanelCellFn`, `CreateOpts`, `soundEffectInterface`, `MdxTexture`, `HelpRequest`, `NgbModalRef`, `CardImage`, `TopUpProvider.RAMP`, `ChildDatabase`, `QueryOpt`, `Param`, `DevicesStore`, `TooManyRequestsException`, `TaskObserver`, `requests.ListDedicatedVmHostInstancesRequest`, `ScalesCache`, `AddRoleToDBClusterCommandInput`, `RequesterAuthorizerWithAirnode`, `MatchRecord`, `AlbumType`, `MessageRequester`, `BuildHandler`, `requests.ListIdpGroupMappingsRequest`, `RollupBlockSubmitter`, `NumberTuple`, `ISession`, `BrowserView`, `KhouryProfCourse`, `GridDimensions`, `UsedNames`, `DescribeUserRequest`, `DescribeTagsRequest`, `UserEmail`, `StrikePrices`, `Models.GameState`, `STDataSourceResult`, `VirtualMachineScaleSet`, `FlatQueryOrderMap`, `PopoverTargetProps`, `JSDocPropertyTag`, `IPipelineOptions`, `DetachedRouteHandle`, `QueueClient`, `MessageToMain`, `SqlPart`, `Buttons`, `TutorialContext`, `LookupStrategy`, `InventoryItem`, `CallbackError`, `AnimationEasing`, `ServiceProperties`, `CIFilter`, `VoiceFocusAudioWorkletNode`, `LinesIterator`, `ts.TextSpan`, `RadixTree`, `PageRoute`, `EndpointBuilder`, `EnumShape`, `Rep`, `JupyterMessage`, `OrganizationDepartmentService`, `VueI18n`, `bluebird`, `PermissionResolvable`, `ArgumentNode`, `IsZeroBalanceFn`, `InvalidPaginationTokenException`, `ComputeManagementClient`, `MethodDescriptor`, `PIXI.Application`, `ProcessApproachEnum`, `TundraBot`, `AttrMutatorConfig`, `IDateGrouper`, `TE.TaskEither`, `ResponsePromise`, `FeatureCatalogueEntry`, `FileExplorerState`, `Angulartics2`, `StaticCardProperties`, `Partial`, `EffectRenderContext`, `IEditorPosition`, `ImageEditorTool`, `OutboundMessage`, `SceneComponent`, `PerfKeeper`, `RequestPausedEvent`, `AggParams`, `SimpleScalarPropertiesCommandInput`, `CommittedFile`, `KeyInfo`, `DataResolver`, `WebMscore`, `MatchPath`, `SelectOutputDir`, `HTMLFormatConfiguration`, `ServerlessResourceConfig`, `TriangleCandidate`, `Lint.WalkContext`, `StartDependencies`, `ASVariable`, `Fork`, `TestRequest`, `MediatorMapper`, `ITag`, `FileDetails`, `DropoutMasks`, `ColumnFilterDescriptor`, `BN`, `AppExtensionService`, `Argument`, `ClientRepresentation`, `ItemTemplate`, `RelatedViews`, `ProblemData`, `CssBlockError`, `MockAddressBookInstance`, `IncomingRegistry`, `Beneficiary`, `InitialState`, `JsonPayload`, `WorkRequestOperationType`, `CreateRoleDto`, `IEventCategory`, `InterfaceImplementation`, `DeleteContext`, `IInitiativeModel`, `GridSprite`, `AlainConfig`, `CatCommonParams`, `DstatementContext`, `Image`, `FormatGraph`, `FieldParamEditorProps`, `MetricDescriptor`, `DOMTokenList`, `ethers.BigNumber`, `Semver`, `Blog`, `Immutable.List`, `EventMapper`, `pxtc.CompileOptions`, `AbstractProject`, `BreakpointFnParam`, `DaffBestSellersReducerState`, `FileSystemTrap`, `NormalizedField`, `EventIded`, `AccountsStore`, `ToggleButtonProps`, `ICardFactory`, `MaxSizeStringBuilder`, `UninterpretedOption_NamePart`, `RecordOptions`, `GetPointTransformerFn`, `IEnumerator`, `QualifierSpec`, `Dirent`, `JestExt`, `MethodCall`, `VulnerabilityReport`, `DirectoryDiffResults`, `SearchSessionDependencies`, `ExtendedGroupElement`, `GenericTwoValuesAndChildren`, `AndroidPerson`, `AsyncIterableExt`, `HostContext`, `DeployedApplication`, `jest.MockedFunction`, `Services.Configuration`, `TocStepItem`, `ModifyDBClusterSnapshotAttributeCommandInput`, `ResourceStatus`, `Ordering`, `TurnTransport`, `HttpPayloadWithStructureCommandInput`, `DetailedCertificate`, `FleetMetricDefinition`, `ContentChange`, `UIAction`, `NowRequest`, `EC.KeyPair`, `StackParameterInfo`, `Ulimit`, `InitializeHandler`, `CCIndicatorSensor`, `InteractionMode`, `MetaInfoDef`, `TextChar`, `Brush`, `ChangeSetType`, `ZoomDestination`, `HsAddDataVectorService`, `FloatTypedArrayConstructor`, `EngineResults.DiagnoseMigrationHistoryOutput`, `FontFeature`, `LoaderAction`, `QueryOrdering`, `PluginFactory`, `ClientConfiguration`, `CreateViewOptions`, `Repositoryish`, `IPC.IFile`, `IMock`, `ComponentTemplate`, `ChemicalDoseState`, `ExpiryMap`, `RuleSetRule`, `WatermarkedType`, `ErrorHandlingService`, `UnsubscribeFn`, `PartyJoin`, `BytesReader`, `YDomain`, `PyrightFileSystem`, `PredictableStepDefinition`, `ListSendersRequest`, `ChildData`, `BusyService`, `PartialVisState`, `TypeProto`, `TextType.StyleAttributes`, `Tiles`, `TileTexSet`, `GPUTexture`, `FakeChain`, `ResFont`, `SdkFunctionWrapper`, `PolygonCollider`, `ListTagsCommandOutput`, `InspectResult`, `ActionParamsType`, `SegmentItem`, `StreamHandler`, `ITracerBenchTraceResult`, `MkFuncHookState`, `UpdateProjectInput`, `LightChannelControl`, `Resolvers`, `LayersModel`, `SqlTuningAdvisorTaskSummaryReportObjectStatFindingSummary`, `AnyObj`, `ExpressionStepDefinition`, `JsonLdDocumentProcessingResult`, `TestProduct`, `CollisionZone`, `ApplyWorkspaceEditParams`, `ListenOptions`, `AngularFireList`, `TInsertAdjacentPositions`, `IBackgroundImageStyles`, `Desktop`, `OrderItem`, `ARMUrlParser`, `PutIntegrationCommandInput`, `IID3v2header`, `IdleState`, `DateInputObject`, `MetricAggTypeConfig`, `NodeDefinition`, `DrawerInitialState`, `Delegate`, `CommandBuffer`, `ColorScheme`, `RobotApiResponseMeta`, `MP.Version`, `IConnectionProfile`, `ResourcePendingMaintenanceActions`, `StringOrNull`, `ILineDiv`, `IqSelect2Item`, `IContextualMenuProps`, `IVarXYValue`, `requests.ListInternetGatewaysRequest`, `Shift`, `ContentBlockNode`, `vscode.TerminalDimensions`, `TIcu`, `NVM500JSON`, `SpheroMini`, `ITokenRefresher`, `GfxProgramP_GL`, `IViewData`, `NavigationPublicPluginStart`, `SolutionBuilderState`, `HoverResults`, `ClassSchema`, `AuthenticationMethodInfo`, `TreeDir`, `HomePublicPlugin`, `HandlerFunction`, `ShortUrlRecord`, `NormalizedEnvironment`, `SharedCLI`, `ConditionsArray`, `NativePath`, `ElementsTable`, `Source`, `SharedTestDef`, `RestClientOptions`, `OAuthError`, `IEnumerable`, `RemoteController`, `CommentNotification`, `UpdateComponentCommandInput`, `LocalizeParser`, `Highland.Stream`, `RuleFailure`, `PortBinding`, `ISample`, `RtkResourceInfo`, `RuntimeTable`, `Vertex`, `Phaser.Math.Vector2`, `ListModelsRequest`, `Electron.OpenDialogOptions`, `WizardTestComponent`, `QueryService`, `SessionChannel`, `SkipBottomButtonProps`, `m.Vnode`, `IRawHealthStateCount`, `ISetLike`, `HasSelectorNodes`, `VirgilPrivateKey`, `PublicIPAddress`, `DropTargetConnector`, `requests.ListInstanceAgentCommandExecutionsRequest`, `helper.PageOptions`, `VaultBackupType`, `SavedObjectsImportError`, `RenderAPI`, `EditableEllipse`, `ThemeTag`, `GetPrismaClientConfig`, `IWorkerContext`, `CategoryCollectionParseContextStub`, `UseConnectResult`, `ContextContributorFactory`, `SpeculativeTypeTracker`, `EntryProcessor`, `IMessageOptions`, `TreeItemComponent`, `OrderbookResponse`, `EditableRectangle`, `core.ScalarOutSpread`, `OrderService`, `RxFormControl`, `DropIdentifier`, `IDataItem`, `IDialogContext`, `InternalPlotConfigObject`, `DeleteQueueCommandInput`, `UnoGenerator`, `lf.schema.TableBuilder`, `requests.ListLoadBalancerHealthsRequest`, `DSOChangeAnalyzer`, `MutableCategorizedStructProperty`, `DefinitionLocations`, `LoadCache`, `mjComponent`, `Globe`, `TSize`, `BasicGraphOnEdges`, `SerializedDatatable`, `Machine`, `ODataEntitySet`, `PutAccountsRequestMessage`, `requests.ListResolversRequest`, `ReadResult`, `PreferenceSchema`, `RunProps`, `Math2D.UvBox`, `LocalUser`, `LexerInterpreter`, `EscapeableMethod`, `TemplatePart`, `Ornaments`, `TokenIterator`, `IObjectOf`, `HTMLLabelElement`, `TagObject`, `AtlasManager`, `TreeDirItem`, `SingleSampledTexture`, `EzBackend`, `InterfaceInternal`, `ListModelDeploymentsRequest`, `Argv`, `CLM.ScoredAction`, `Promotion`, `AnalyticsService`, `ExternalAttributionSources`, `PolicyType`, `ResolveIdResult`, `Register`, `MerkleIntervalTreeNode`, `ServiceAnomalyTimeseries`, `PhysicalLayout`, `Mdast.Link`, `PodDataPoint`, `IData`, `PiPropertyInstance`, `UiSettingsClient`, `SearchExpressionGroup`, `CreateAggConfigParams`, `N2`, `HighContrastModeDetector`, `builder.IEvent`, `ResultPoint`, `Bind`, `ProgramCounter`, `TransformerPayload`, `TrackingData`, `Bass`, `OutgoingMessage`, `Constructor`, `AdminActions`, `RoleOption`, `NoteItem`, `CompressorOptions`, `LoaderData`, `FacepaintStyleSheetObject`, `DirItem`, `InstancesState`, `StorageAdapter`, `ScalarTypeComposer`, `StandardProps`, `MemoExoticComponent`, `TransformLike`, `RadListView`, `PolymerElement`, `NgWalker`, `SearchInWorkspaceResult`, `ContractProgram`, `NativeStackScreenProps`, `SettingsDataProvider`, `PointerPressAction`, `VRMCurveMapper`, `ParenthesizedExpression`, `CsvFormatterStream`, `BoolTerm`, `CraftBlock`, `EmitterManager`, `PartialConfig`, `RealtimeUsersWidgetData`, `PanelConfig`, `IStyleAttr`, `BlockService`, `JsonResult`, `WindowService`, `React.PropsWithChildren`, `TestOptions`, `DomainDropSet`, `VisualizePluginSetupDependencies`, `ConfirmedTransaction`, `ArrayType1D`, `Internal`, `StateHandler`, `WorkflowActivateMode`, `IFormat`, `WhiteBalance`, `IRouterConfig`, `CompressedEmojiData`, `IFormSection`, `StacksPublicKey`, `SelectionService`, `InputObjectTypeDefinitionNode`, `BasePlayer`, `SqlQuery`, `DataModel.RowRegion`, `GUIDestination`, `ProtocolNotificationType0`, `NoteForActivitySetup`, `SiteLicenses`, `ListEnvironmentTemplatesCommandInput`, `IDataFilterValue`, `WhitelistType`, `FullyQualifiedScope`, `StatusService`, `Graph`, `IMaterial`, `FirebaseListObservable`, `StubProvider`, `IsAssign`, `DescribeAccountCommandInput`, `NinjaItemInfo`, `StatementCST`, `FeaturedSessions`, `PlaywrightTestConfig`, `TaskPriority`, `VersionHistoryDataService`, `UseMutationOptions`, `Preview`, `Expectation`, `PrerenderUrlResults`, `FirewallRule`, `GetPromiseInvocationContext`, `DescribeEventsCommandInput`, `ThyTransferDragEvent`, `UrlDrilldown`, `types.UiState`, `NextPageContext`, `ListProfilingGroupsCommandInput`, `ts.DiagnosticCategory`, `LayerEdge`, `QueryCompleteContext`, `size_t`, `RelationsService`, `CompilerOptionsValue`, `IComplexTypeEx`, `EntityWithGroupType`, `DecryptedUserMessage`, `ListFindingsResponse`, `Square`, `OpenAPISchema`, `OperatorFormat`, `CaptionElementProps`, `OptionalRef`, `IBindingTemplate`, `DateSchema`, `QueryParamConfig`, `Routes`, `C2dRenderTexture`, `StandardSchemeParams`, `RegionData`, `RegisteredActionRunner`, `KeyPathList`, `AssetId`, `KernelParams`, `MediaTrackSettings`, `SceneNodeBuilder`, `TraitMap`, `CommandSetting`, `k`, `RegisteredPlugin`, `LookUp`, `MetronomeBeam`, `SimpleRNN`, `TabbedRangeFilterParams`, `Probe`, `freedom.Social.ClientState`, `AuthDispatch`, `DOMHandlerScope`, `ContractMetadata`, `PointCloudMaterial`, `PlacementTypes`, `schema.Context`, `NotificationBarService`, `AppearanceCharacteristics`, `LoginPayload`, `UpSetProps`, `JsonLocations`, `ListConnectionsCommandInput`, `RLAN`, `ArrowHelper`, `TestFunction`, `ConnectionMessage`, `IAmazonS3Credentials`, `CmdType`, `JobAgent`, `DescribeLoadBalancersCommandInput`, `Preprocessor`, `Path1`, `PatternRecognizer`, `PersistedStatePath`, `DragDropProviderCore`, `FieldValidationResult`, `ProjectInput`, `ChainableElement`, `EditorWidget`, `AddFriendsRequest`, `HttpServer`, `DomainData`, `ActivityDefinition`, `StreamDescription`, `ITextureInfo`, `DocumentManager`, `FieldToMatch`, `GetImportJobCommandInput`, `ExprVisState`, `BlockChainUser`, `HTMLDetailsElement`, `SeriesChanges`, `InternalGroup`, `MockClientFactory`, `WasmResultValues`, `SecurityRequestHandlerContext`, `ItemOptions`, `ApiErrorReporter`, `HashParams`, `IRpoToken`, `TypeKind`, `HistoryNodeEvent`, `TileInfo`, `NbToastrService`, `GltfNode`, `Point`, `ConflictType`, `GestureEventData`, `CreateTokenAccount`, `android.content.Intent`, `EntityColumnDef`, `GetUserData`, `HsDialogItem`, `IAccordionItemContextProps`, `OrganizationSet`, `AzureConfigs`, `GetSymbolAccessibilityDiagnostic`, `OnEvent`, `PriceOracle`, `UntagResourceInput`, `PrismaClient`, `ICountryModel`, `ReaderConfig`, `Group`, `ActionFilter`, `ParametersPositionContext`, `InternalProps`, `CustomOkResponse`, `JsonIdentityInfoOptions`, `Events.postcollision`, `SaveEntities`, `ts.WriteFileCallback`, `MethodDetails`, `CamelElement`, `IModelConnection`, `ControlOptions`, `IPivotItemProps`, `NodesInfo`, `ConnectedWallet`, `IFormInput`, `ParameterInformation`, `ModelRenderer`, `SamlRegisteredService`, `AngularFireFunctions`, `W1`, `GunGraphAdapter`, `program.Command`, `RedPiece`, `DataOption`, `DeleteNamespaceCommandInput`, `GossipMemoryStore`, `ProjectLabelInfo`, `Viewport_t`, `BaseExecutor`, `StackDescriptor`, `ProjectExtentsClipDecoration`, `LicenseSubs`, `CacheKeys`, `FullRequestParams`, `Inhibitor`, `DescribeDBClusterSnapshotAttributesCommandInput`, `BoneDesc`, `Lru`, `PutResourcePolicyRequest`, `ViteDevServer`, `RequireFields`, `d.BundleModule`, `JoinDescriptor`, `BatchCheckLayerAvailabilityCommandInput`, `MockCachedRule`, `ErrorState`, `ShareMap`, `InterfaceDeclarationStructure`, `StateChange`, `TStylingContext`, `Declaration`, `UseSavedQueriesReturn`, `IRootState`, `GraphService`, `IpcRendererEvent`, `TypesStart`, `CombatantState`, `IReader`, `Knuckle`, `DataReader`, `TokenState`, `BsModalRef`, `ConnectionSetting`, `MatOpM`, `ShaderRegisterElement`, `TSObj`, `ICXOrder`, `TouchMouseEvent`, `ODataUri`, `cdk.App`, `ModelTypes`, `UInt32`, `TimePickerState`, `SimpleToastCreator`, `ApolloTestingController`, `AuthProps`, `Bean`, `MockRouter`, `PDFPageEmbedder`, `RegSuitConfiguration`, `CloudWatchDimensionConfiguration`, `IOrganizationSprint`, `DataSnapshot`, `IComponentName`, `IAmazonClassicLoadBalancerUpsertCommand`, `XRSession`, `RestorePoint`, `ISelectionId`, `MetadataProperty`, `StageRuntimeContext`, `GanttSettings`, `SubscriptionTracker`, `UpdateGroupRequest`, `Uri`, `MediaProviderConfig`, `MessageProps`, `WebSettings`, `PropertiesField`, `TreeNode2`, `Truncate`, `ScannerState`, `CreateCrossAppClickHandlerOptions`, `WechatSettingService`, `HeaderComponent`, `requests.ListTsigKeysRequest`, `LayoutDefaultHeaderItemComponent`, `DeleteExpression`, `CommonSelectedNode`, `APIClient`, `IEventFunction`, `GraphIIP`, `TestHost`, `CategoryCollectionParserType`, `TreeviewComponent`, `PlotArea`, `IAppContext`, `SessionConnection`, `SalesLayoutState`, `HttpRequestOptions`, `GlobalVarsService`, `BleepsGenerics`, `NavigatableWidget`, `EntityNameOrEntityNameExpression`, `PerspectiveCamera`, `ChartJSNodeCanvas`, `ServiceNowActionConnector`, `IAuthStrategy`, `WorkerPoolResource`, `HealEvent`, `SupCore.Data.Schema`, `PedalTuning`, `fromAuthActions.Login`, `HsEventBusService`, `SemanticTokensParams`, `SolutionToApiAnalysis`, `AngularPackage`, `ArrayBuffer`, `GfxrGraphBuilder`, `BadRequestException`, `ModuleNameNode`, `PortalType`, `StreamResponse`, `SetContextLink`, `MemoryPages`, `BookmarkChange`, `CreateStackCommandInput`, `FileScan`, `IFiber`, `ICondition`, `CronProcessTable`, `CanaryExecutionRequest`, `TransactionSkeletonType`, `MovingDirection`, `SceneObjHolder`, `ComponentFileItem`, `TestType`, `BitstreamDataService`, `GenerateFn`, `IGitApi`, `HistoryResponse`, `TextPathGeometry`, `MaxPooling1D`, `ExtractDto`, `NumberFormat`, `APIConfig`, `Slugifier`, `protocol.Message`, `DestinationAuthToken`, `CoreContext`, `MappedPosition`, `ODataModelField`, `Ivl`, `TestFunctionImportEdmReturnTypeCollectionParameters`, `AssetPropertyTimestamp`, `AirtableBase`, `AccountImplement`, `Combinator`, `UInt160`, `TypeDetails`, `HeadingProps`, `DataSeriesDatum`, `PathRef`, `ICardEpisode`, `ReadonlyArray`, `core.BTCAccountPath`, `IScreen`, `Survey.Operand`, `Store`, `FIRStorageTaskSnapshot`, `SignOptions`, `ChartWidget`, `IncludedBlock`, `OpType`, `IContext`, `CustomNestedProps`, `PubArt`, `ModuleDefinition`, `PromiseSocket`, `TranslationSettings`, `HttpStatusCodes`, `SavedVisualizationsLoader`, `SFUISchemaItem`, `PassportStatic`, `DeviceService`, `ProductService`, `TextAreaComponent`, `TNodeReturnValue`, `LoggingConfigType`, `MyEvent`, `MetalsTreeViewNode`, `ResolvablePromise`, `EvmContext`, `PaymentInfo`, `InputSettings`, `RollupWarning`, `FkQuadTree`, `TestFolder`, `Filesystem`, `SnackbarKey`, `DescribeEndpointsCommandInput`, `ResourceArguments`, `CaretOptions`, `StaffLayout`, `DecorationFileMap`, `ECharts`, `IConnectionFormState`, `Evt`, `LinkObject`, `UsbDevice`, `IsometricPoint`, `SecurityReport`, `SpeechServiceConfig`, `NotificationTemplateEntity`, `IDrawOption`, `LikeEntity`, `InspectorViewDescription`, `TemplRef`, `ComponentService`, `AccessKey`, `SelectionModel.Selection`, `AVRIOPort`, `yargs.Arguments`, `DataViewCustom`, `ProjectColumn`, `SavedObjectsImportFailure`, `StorageImpl`, `SMTMaskConstruct`, `TryStatement`, `IPlDocObject`, `PhraseFilterValue`, `Prisma.Sql`, `UsersActionType`, `Matrix`, `ITooltipProps`, `PlaybackSettings`, `AnyBody`, `IFeature`, `InternalHandler`, `Servient`, `TemplateSummary`, `NibbleDisk`, `DataItem`, `Progression`, `ExtendedType`, `IQueryBuilderPart`, `oke.ContainerEngineClient`, `SdkSignalFrame`, `DebugProtocol.OutputEvent`, `DebugProtocol.Source`, `ScopedLabel`, `DecoratorConfig`, `ICategory`, `NationalTeam`, `TokenSource`, `Cypress.Response`, `requests.ListSecretVersionsRequest`, `AggTypeFieldFilter`, `FieldToValueMap`, `DelayNode`, `UsageSummary`, `MonitoredItem`, `DeleteImageCommandInput`, `SavedObjectUnsanitizedDoc`, `ScullyRoute`, `CalculateBoundsFn`, `ActivePoint`, `SqlObject`, `SymbolKey`, `AuxChannelData`, `BundleModuleOutput`, `DescribeCodeBindingCommandInput`, `VdmFunctionImport`, `TupleAssignmentContext`, `DocumentDelta`, `CreateTokenCommandInput`, `ClanStateService`, `IAnalysisState`, `NumberDraggerSeg`, `JsonFormsState`, `AsyncLocalStorage`, `StateProvider`, `SolanaNetwork`, `BeatUnitDot`, `SRT0_MatData`, `vscode.ConfigurationChangeEvent`, `d.OptimizeCssInput`, `U`, `VersionStage`, `IBlockchain`, `FolderItem`, `ScrollInfo`, `UniversalRouterSync`, `TT.Tutorial`, `Stream`, `TupletDot`, `TestContracts`, `ReferenceContext`, `IFileTreeItem`, `Field_Ordinal`, `ParticipantSubscriber`, `H264RtpPayload`, `AuthModeChanged`, `CompilerAssetDir`, `ApplicationRepository`, `TextureFetcher`, `DmChannelDTO`, `jasmine.Spy`, `IServerOptions`, `UserFunctionNamespaceDefinition`, `JSON_PayloadInMask`, `PrismaClientRustErrorArgs`, `StartQueryCommandInput`, `IDBAccessQueryParams`, `DiscordBridgeConfig`, `PerformListFilesArgs`, `GfxQueryPoolP_GL`, `GoStoneGroup`, `ResolvedConnection`, `ListConfigurationsCommandInput`, `AndroidChannel`, `SchemaToArbitrary`, `GherkinException`, `AllFile`, `VideoModel`, `child_process.ChildProcess`, `BaseVisTypeOptions`, `VAStepData`, `NotifyPlacement`, `ButtonColor`, `TResult`, `UserFunctionDefinition`, `PairSide`, `TemplateTag`, `ChartSpecPage`, `HttpEvent`, `SubjectDataSetColumn`, `WorkRequestWaiter`, `MetricType`, `GetMasterAccountCommandInput`, `CreateJobCommandInput`, `InferenceInfo`, `UserInput`, `TooltipValue`, `MenuSection`, `ApisTreeItem`, `LocalOptionsMap`, `MockBaseElement`, `RedirectResult`, `Ecies`, `WebAppRuntimeSettings`, `ts.LabeledStatement`, `AlterTableBuilder`, `ZipResource`, `NameType`, `ExpirableKeyV1`, `IBaseView`, `ReactChild`, `eui.Image`, `MarkSizeOptions`, `Fill`, `Mute`, `BlockMap`, `SelectorCore`, `MobileRpcChunks`, `TypingIndicatorReceivedEvent`, `CancellablePromise`, `SerializeErrors`, `marked.Renderer`, `MockCall`, `MnemonicLanguages`, `AbsoluteDirPath`, `ScaleMap`, `UpdateUserResponse`, `IterableChanges`, `ChannelFactoryRegistry`, `Perm`, `V1DaemonSet`, `Calendar_Contracts.IEventSource`, `SymbolAccessibilityDiagnostic`, `SourceControlResourceState`, `JsonDocsSlot`, `WalletError`, `TestStep`, `ElmExpr`, `ShorthandFieldMapObject`, `AnalyticSegment`, `Q.Deferred`, `SourceFileInfo`, `IPropertyValueDescriptor`, `YBasicSeriesSpec`, `WorkItemTypeUI`, `User.Type`, `GuideType`, `ComponentTestingConstructor`, `WordStorage`, `ViewUpdate`, `Toolbox`, `CrochetType`, `BTreeNode`, `DocView`, `OrgInfo`, `GetText`, `ModuleResolutionKind`, `estree.Node`, `EncodeOptions`, `EventAccumulator`, `FileOutput`, `PointCloudHit`, `ConversationState`, `MilestoneActivity`, `Polyface`, `LoggerFormat`, `AuthenticateFacebookInstantGameRequest`, `ValidatedPurchase`, `Persistor`, `FuncMode`, `CachedTileLayer`, `BreadcrumbItemType`, `PathReference`, `WebSocketClient`, `ApplicationStart`, `ShaderParam`, `TestScriptResult`, `FileDefinition`, `IContextMenuItem`, `Beam`, `BranchDataCollection`, `DefaultDataService`, `ResponseError`, `TaskFn`, `InteriorNode`, `TExtra`, `New`, `TernaryNode`, `IPosition`, `SpecializedFunctionTypes`, `LabelDefinitionJSON`, `tmrm.TaskMockRunner`, `ChatItemSet`, `AssignmentCopyStep`, `AppRedux`, `KeyRingStore`, `DataFileType`, `SfdxCommandDefinition`, `CustomDecorator`, `VisualizationChartProps`, `EntriesArray`, `HsdsEntity`, `ModuleDatafeed`, `GraphEdge`, `GetDeprecationsContext`, `ApexTestNode`, `Predicate`, `TemplateHandlers`, `KeyofC`, `HeaderColumnChainRow`, `NextApiRes`, `WalkerDown`, `Z64SkeletonHeader`, `VersionNumbers`, `RoverInitialState`, `DeeplyMocked`, `CdkDragEnter`, `requests.ListConnectHarnessesRequest`, `IEffect`, `LabelValue`, `PSIDataType`, `Sema`, `QueryFormColumn`, `PackageId`, `DSlash`, `YConfig`, `Bytecode`, `EnvValue`, `Dependency`, `BuiltAction`, `IntrospectionEngineOptions`, `NavigatorParams`, `MemoryArray`, `GetUserSettingsCommandInput`, `ConfirmationService`, `PluginEditorProps`, `SegmentRef`, `CandleData`, `RequiredFieldError`, `ApiRoute`, `StyledButtonProps`, `DescribeEventsMessage`, `ItemType`, `ThreadID`, `RevisionValueCache`, `CppCbToNew`, `DeliveryDetails`, `BreakpointObserver`, `QueryFormData`, `IndexedDB`, `InputInfo`, `TicTacToeGameState`, `CollisionContact`, `InternalProvider`, `PluginPageContext`, `Node_Interface`, `ListApplicationsCommandOutput`, `TransactionReceiptTruffle`, `ReplacementRule`, `ParamsOptions`, `EntityUpdate`, `TransferItemOption`, `FastifyError`, `IStorageLayer`, `EmptyInputAndEmptyOutputCommandInput`, `Fanduel`, `InterfaceWithThis`, `DoubleValue`, `OpenApi.Document`, `VectorList`, `d.BuildSourceGraph`, `CancellationStrategy`, `InputPort`, `CommandCreatorError`, `DirectBuy`, `ObjectModel`, `IHawkularAlertRouterManager`, `SimpleNode`, `Heap`, `DaLayoutService`, `DnsValidatedCertificate`, `ILinkProps`, `core.ETHAccountPath`, `KibanaResponse`, `SpecRoleCapabilities`, `IAbortAblePromise`, `LoginAccountsRequestMessage`, `OrganizationMemberType`, `ProgressConfig`, `IBalanceValue`, `MutationObserverInit`, `MeshSprite3D`, `StartPipelineExecutionCommandInput`, `IDistributionDelta`, `JsonFragment`, `ConnectionInformations`, `FortuneOptions`, `BufferId`, `Lambda`, `ComponentClass`, `ODataSingletonResource`, `IValidationResponse`, `Chip`, `TableClient`, `ExportDefaultDeclaration`, `RemoteInfo`, `IMessageValidator`, `FormReturn`, `GenerationStatus`, `GetAppDefinitionParams`, `DiffFile`, `FeatureID`, `ReactComponent`, `Airline`, `MonacoEditorService`, `PouchDBFileSystem`, `NotFound`, `Array4`, `FormlyDesignerConfig`, `RouteValidator`, `MessageError`, `ListPresetsCommandInput`, `QueryWithHelpers`, `Matrix2`, `At`, `CouncilData`, `OnDemandPageScanResult`, `GunGraphData`, `ProductSearchParams`, `core.ITenantManager`, `SubscribableEditionComboboxItemDto`, `TSIf`, `IAbstractControl`, `SerializableMap`, `InternalDatasource`, `CodeMirror.Editor`, `RangeFilterParams`, `IPageData`, `Hook`, `GetDeploymentsCommandInput`, `NelderMeadPointArray`, `webpack.Configuration`, `SpriteData`, `ParsedMessage`, `WriterContext`, `BufferView`, `AllAccessorDeclarations`, `RectAnnotationSpec`, `ProjectorPerformanceLogger`, `TextProperties`, `NodeRef`, `IndexPatternSelectProps`, `BehaviorObservable`, `NgbPanelChangeEvent`, `BlinnPhongMaterial`, `RangeSelectorOptions`, `AbstractDistanceCalculator`, `AlertData`, `ModelProps`, `ICommon`, `QueryPayload`, `LaunchTemplateOverrides`, `CellSelection`, `ConceptConstraint`, `Setdown`, `IShellMessage`, `Composable`, `InstantiableRule`, `MaterialSet`, `ReservedIP`, `CommandEvent`, `Swizzle`, `RefService`, `FileDeclaration`, `_ZonePrivate`, `GeoJSON`, `AreaChartOptions`, `AlertAction`, `SqlTaggedTemplate`, `QuestionModel`, `DappRequest`, `MessagePayload`, `AuthenticationName`, `IJumpPosition`, `ChannelType`, `FieldVisitor`, `NzFormatEmitEvent`, `AttributionInfo`, `ServiceImplementations`, `NSData`, `MEMBER_FLAGS`, `JsonAstNode`, `DeleteSnapshotCommandInput`, `GameBase`, `Pagerank`, `DiagnosticMessage`, `Other`, `TEAttr`, `TSBreak`, `CacheItem`, `HistoryTreeItem`, `IRequestInfo`, `AnalysisResults`, `SavedObjectsMigrationVersion`, `CliqueVote`, `Project.ID`, `DhcpOption`, `ActivatedRouteSnapshot`, `CommandExecution`, `AggConfigSerialized`, `VideoDescription`, `SchemaValidatorFactory`, `DeviceType`, `StateIO`, `IOptimizeOptions`, `TypeScriptEmitter`, `ITransUnit`, `ConfigTypes.CFWorkers`, `BucketMetadataWithThreads`, `ConceptDb`, `ContractState`, `FSFile`, `ProfileStateModel`, `FaunaIndexOptions`, `SimpleReloaderPlugin`, `Notes_Contracts.Note`, `IReduxAction`, `EnvironmentOptions`, `RelationExt`, `ValuePaddingProvider`, `TDiscord.Guild`, `AuthorizeParamsDto`, `BookSavedObjectAttributes`, `XmlStateConsumer`, `UpdateValueExpression`, `DataValidationCxt`, `NoteSnippetEditorRef`, `IApplicationState`, `DbStxLockEvent`, `requests.UpdateProjectRequest`, `SkeletonField`, `CompositeDisposible`, `QueryCommandInput`, `IGDILogger`, `Vector3Keyframe`, `ExchangeOptions`, `$G.IGraph`, `interfaces.BindingInWhenOnSyntax`, `Key2`, `IFormValues`, `IFrameHeader`, `EmailConfirmationValidator`, `JSExcel`, `ts.FileWatcher`, `StructDef`, `ArrayServiceArrToTreeNodeOptions`, `EventArgs`, `PiTypeDefinition`, `Enumerator`, `NodeJS.Process`, `HsAddDataCommonService`, `SfxData`, `CommandArgument`, `ts.Expression`, `HitsCounterProps`, `IconifyIconCustomisations`, `MemberData`, `RTCStatsReport`, `DisLabel`, `FileTextChanges`, `RequestConfig`, `Trait`, `Words`, `GetAccountCommandInput`, `ListingMeta`, `SafeTransaction`, `PathAndContent`, `BranchFlagStm`, `WebElementWrapper`, `ConnectDetails`, `OperationDetails`, `Decoration`, `MessageWithoutId`, `BeforeCaseCallback`, `CLM.TextVariation`, `StoreNode`, `IReducer`, `IsoLayer`, `DinoController`, `DeleteEndpointCommandInput`, `requests.ListPoliciesRequest`, `tf.Tensor1D`, `TemplateFunction`, `TPackage`, `dia.Link`, `ResourceHelper`, `path.ParsedPath`, `TransientState`, `TInjector`, `GetGeneratorOptions`, `DeleteVpcPeeringConnectionCommandInput`, `NetworkContext`, `RBNFNode`, `ImageRequest`, `Version`, `egret.Event`, `JUser`, `GClient`, `CdsControlMessage`, `UST`, `EVMPayload`, `RawGraphData`, `Vector2`, `PlanetInfo`, `ResolverRpCb`, `objectPointer`, `AmongUsSession`, `ColorSwitchCCStartLevelChange`, `sdk.LanguageUnderstandingModel`, `RumConfiguration`, `Rx.Observer`, `Yendor.TickResultEnum`, `IUserDetails`, `ReaderPage`, `Padding`, `AccordionComponent`, `ReplayableAudioNode`, `IModuleMap`, `MessageRepository`, `IUserRequestOptions`, `MIRArgument`, `UsePaginationModelConfig`, `ResponseParams`, `ITransformerHandleStyle`, `IParticipant`, `VersionOperatorContext`, `GraphQLSchemaWithFragmentReplacements`, `TableDataProvider`, `BlokContainerUserSettings`, `EzBackendOpts`, `TEmoji`, `WaitForSelectorOptions`, `fhir.Identifier`, `ActionInterval`, `vile.Issue`, `AppWithCounterState`, `UserInputPlugin`, `ScopeableRequest`, `Sid`, `FixtureContext`, `Matrix4d`, `IRuntimePosition`, `LoadingBarsEffectsRefs`, `ITemplate`, `PollerLike`, `ValueHandler`, `anchor.web3.Connection`, `HarmajaStaticOutput`, `Touched`, `TInput`, `ExtOptions`, `EntityActionParam`, `ShaderParams`, `LogFunction`, `ParameterValueDefinition`, `IArguments`, `SingleASTNode`, `ConvertService`, `GanttDate`, `CommandClient`, `IFactory`, `Timeline`, `TargetRange`, `PkgConflictError`, `SetIconMode`, `BoxCache`, `Relationships`, `IUserDocument`, `MutationFunction`, `MessageHeaders`, `ListTagsRequest`, `StagePanelSection`, `ColorGradient`, `SupabaseClient`, `MDCAlertAction`, `UpdateDependenciesParams`, `RectModel`, `requests.ListAutonomousContainerDatabaseDataguardAssociationsRequest`, `ThroughputSettingsUpdateParameters`, `B13`, `ToastParams`, `SecretVersion`, `NavService`, `TimeScale`, `EventTypeService`, `serialization.ConfigDictValue`, `ListRequest`, `Sphere`, `AggregationMode`, `parse5.ASTNode`, `UserStorage`, `IManifestArmor`, `InfuraProvider`, `Identification`, `DeepLink`, `_DeepPartialObject`, `TooltipPayload`, `SourceConfiguration`, `CSTeamNum`, `ts.AsExpression`, `SVGGraphicsElement`, `ImageState`, `TangentType`, `NcTabs`, `BitGo`, `MatBottomSheet`, `ParameterCategory`, `AliasMapItem`, `IAGServer`, `PublishDiagnosticsParams`, `EventCreatorFn`, `QTMCounterState`, `SuccessfulMatchReport`, `CobIdentifier`, `UserSession`, `ContextTransformFieldType`, `IColumnToolPanel`, `StitchesComponentWithAutoCompleteForReactComponents`, `d.RollupChunkResult`, `IFieldSchema`, `ComponentLocale`, `BooksState`, `AudioPlayerState`, `Public`, `NavControllerBase`, `TransmartStudy`, `IStorage`, `ConversationNode`, `StorageFile`, `OrbitTransformation`, `CalendarRepository`, `AddressHashMode.SerializeP2SH`, `InboundTransport`, `CrawlContext`, `SubscriptionObserver`, `ResStatus`, `RSSI`, `RRNode`, `FindConditions`, `ApprovalPolicy`, `MDCLineRippleFoundation`, `CreateAuthorizerCommandInput`, `EvaluationResult`, `RenderBufferTargetEnum`, `DecryptedSymmetricKey`, `MentorBasic`, `EventArg`, `IUnitStoryChapter`, `ObservableMap`, `DMMF.SchemaEnum`, `FaceNameSwizzler`, `GitHubClient`, `Hour`, `UserChallengeData`, `CryptoFrame`, `VectorType`, `CreateContactCommandInput`, `LuaSymbolInformation`, `Achievement`, `Lazy`, `CreateDeploymentCommandInput`, `Password`, `CaseInsensitiveMap`, `DestinyCacheService`, `PackedBubblePoint`, `TSESLint.RuleModule`, `Ingredient`, `ListSortMembersSyntax`, `ElementResult`, `ObjectButNotFunction`, `IArgs`, `DecodedPixelMapTransaction`, `CoreUsageStatsClient`, `IndexedGeometryMap`, `SpawnASyncReturns`, `FolderService`, `Invoice`, `Pixels`, `ChoicesEntity`, `ListOpsInfo`, `IExpectedIdToken`, `DataCenterResource`, `CategoryMap`, `RPCConnection`, `ResolvedPointer`, `ColorScale`, `PackageSummary`, `EmitContext`, `MarkupElement`, `InterpolateData`, `TranslationFile`, `UploadApiResponse`, `TranslationKeys`, `PatchOperation`, `NgGridItem`, `AtomicMarketNamespace`, `DiagnosticResult`, `CollisionCategorizedKeeper`, `ColorFunc`, `HR`, `AnalyserNode`, `ts.TypeParameterDeclaration`, `IssueLocation`, `LambdaContext`, `ARMRamItem`, `ResponseWithBodyType`, `PanelNotificationsAction`, `Trail`, `RequestedServiceQuotaChange`, `GraphQLInputField`, `PointerAllocationResult`, `PackagePolicy`, `CLM.TrainScorerStep`, `SdkAudioStreamIdInfoFrame`, `MicroAppConfig`, `ApiCall`, `protocol.FileLocationOrRangeRequestArgs`, `PackageJsonWithTsdConfig`, `ModifyDBInstanceCommandInput`, `Junction`, `UiSettingsParams`, `ODataService`, `AddGatewayV1`, `JobValidationMessage`, `AccessTokenResponse`, `AbortChunk`, `ValueOptions`, `RawLogEvent`, `HomeComponent`, `WalletPage`, `CloudTasksClient`, `FieldResultSettingObject`, `HighlightData`, `StorageConfig`, `TxOptions`, `GetZoneRecordsRequest`, `ColumnWorkItemState`, `StringifiedUtil`, `WebTally`, `EmitTextWriterWithSymbolWriter`, `VueFile`, `CreateEndpointCommandInput`, `AirlineEffects`, `OrthographicCamera`, `IArticleField`, `MessageGroup`, `Manipulator`, `UISliceState`, `ExpandedArgument`, `TaskDraftService`, `FilterDataStatusValues`, `CompletionRecord`, `HandledEvent`, `CommonTableExpressionNode`, `Bank`, `CreateDBSubnetGroupCommandInput`, `SearchInputProps`, `SnapshotListenOptions`, `ReconnectDisplay`, `DockerRegistryHelper`, `ParamT`, `ChainJson`, `PnpmShrinkwrapFile`, `IMergeViewDiffChunk`, `StorageManager`, `DiffCopyMessage`, `Datastore.Context`, `CDJStatus.State`, `AddressData`, `SavedToken`, `ServerListEntry`, `ChordType`, `TypeOperatorNode`, `ChartDownload`, `ActionFilterAsync`, `DefaultRollupStateMachine`, `IntlShape`, `ButtonType`, `PreRenderedChunk`, `ExpressionReturnResult`, `DeleteConfigurationSetEventDestinationCommandInput`, `Knex.TableBuilder`, `ScaleLinear`, `ContainerBase`, `BuiltQuery`, `IComm`, `WrappedStep`, `MDCChipAdapter`, `IsNot`, `SecureRandom`, `RaycasterEmitEvent`, `requests.ListBootVolumeBackupsRequest`, `vscode.CancellationTokenSource`, `CodeBlockProps`, `ElementSession`, `AxisLabelFormatter`, `ApplyResult`, `EmulateConfig`, `IPlatformService`, `ts.ParseConfigFileHost`, `SHA384`, `avcSample`, `ReputationOptions`, `preValidationHookHandler`, `fs.Dirent`, `ISceneActor`, `ObjectiveModel`, `GEvent`, `CarouselInternalState`, `LinearSweep`, `ProColumns`, `TextEditorHelperReturnType`, `UserState`, `Moment`, `DeleteFileOptions`, `snowflake`, `MdcIconRegistry`, `IntervalType`, `EzBackendInstance`, `CommandClass`, `SuccessCallbackResult`, `DateTime`, `TestSet`, `Identify`, `OUTPUT_FORMAT`, `TensorData`, `PropertyAst`, `BlurState`, `TabBar`, `AddTagsCommandInput`, `IInventoryArmor`, `DaffCartCouponFactory`, `CmsModelFieldToElasticsearchPlugin`, `EncryptionError`, `Ray3`, `OneListing`, `PreloadData`, `ExecuteStatementCommandInput`, `ServerSecureChannelLayer`, `Salt`, `MapIncident`, `ReportingCore`, `DomainEntity`, `CreatePostInput`, `NSV`, `AtomFamily`, `SnapshotOrInstance`, `VariableDeclarationList`, `CreateFieldResolverInfo`, `SeriesUrl`, `CodeLens`, `Operator.fλ.Stateless`, `CompassCardConfig`, `RelativeTimeFormat`, `IFunctionCall`, `XPCOM.nsXPCComponents_Results`, `InterceptorOptions`, `StorefrontApiModule`, `MatchReport`, `ConfigSource`, `UnpackOptions`, `SimpleObjectRenderer`, `WidgetZoneId`, `SigningRequest`, `Defaults`, `ResponderRecipeResponderRule`, `RadioChangeEvent`, `aws.iam.Role`, `CommandLineBinding`, `DragSourceSpec`, `SelectPlayer`, `TextureDataFloat`, `HttpRes`, `TaskLifecycleEvent`, `TCallback`, `StopWatch`, `ApigatewayMetricChange`, `ODataEntityResource`, `DAL.DEVICE_ID_RADIO`, `ColumnProperty`, `RepoClient`, `DiagnosticBuffer`, `CheckPointObject`, `WesterosCard`, `ClearingHouseUser`, `UnsignedContractDeployOptions`, `comparator`, `QuickPickStep`, `ITimeline`, `Function1`, `IgnoreMatcher`, `ProtocolType`, `TextDocumentPositionParams`, `ArgumentCategory`, `TestProps`, `NewTorrentOptions`, `JPAC`, `OptionsInit`, `RowBox`, `PrinterOptions`, `DirectiveHarvest`, `WorkerMeta`, `Extend`, `RenderDebugInfo`, `CSSResult`, `next.SketchLayer`, `PddlExtensionContext`, `RectGeometry`, `IStorageOperationModel`, `GetDomainStatisticsReportCommandInput`, `SideEntityController`, `HTMLPreviewManager`, `HeatmapSpec`, `UserObjectParam`, `Biquad`, `IOptionsObj`, `SolarWeek`, `SingleProvider`, `TextOptions`, `ValidatorBuilder`, `GestureStateChangeEvent`, `LineSegment`, `DecodedInstruction`, `PointAttribute`, `Logging`, `OverlayPositionBuilder`, `BuildEnv`, `TAG_SIZE`, `EVCb`, `SimpleChanges`, `PayoutNumeratorValue`, `AuthenticationExecutionInfoRepresentation`, `ResourcesWithAttributedChildren`, `QueryAuditorAttributesRequest`, `FollowLinkConfig`, `TernarySearchTree`, `SignDoc`, `BaseTexture`, `RowTransformFunction`, `ObjectFlags`, `DimensionGroup`, `NetworkingState`, `TextElementsRendererOptions`, `MdlOptionComponent`, `SecuritySchemeObject`, `TimechartHeaderProps`, `KeyboardShortcut`, `TweetTextToken`, `WatchableFunctionLogic`, `ReactFragment`, `TypeToMock`, `BespokeServer`, `CustomersGroupState`, `core.ETHSignMessage`, `QueueReceiveMessageResponse`, `AuthReduxState`, `FlipDirection`, `MetricRegistry`, `VNodeProps`, `StateNode`, `ResolvedAtomType`, `Transpiler`, `Preposition`, `DynamoDBDocumentClientResolvedConfig`, `GroupList`, `HTTPResponseBody`, `PoxInfo`, `IDatePickerModifiers`, `VerticalPlacement`, `TaskResolver`, `SoftmaxLayerArgs`, `requests.ListWorkRequestErrorsRequest`, `Feeder`, `OperandType`, `DockerGlobalOptions`, `IApiResponse`, `ContractCallOptions`, `SelectEvent`, `CheckSimple`, `DeleteQueryNode`, `JhiAlertService`, `Phaser`, `_Identifiers`, `BroadcastEvent`, `LegacyResult`, `UsersState`, `UAObject`, `IHWKeyState`, `IVehicle`, `SetElemOverlap`, `ThyUploaderConfig`, `OutputEntry`, `SerializableRecord`, `BatchCreateChannelMembershipCommandInput`, `Rule.RuleFixer`, `ComponentsProps`, `fromSettingsActions.GetSettingModelCollection`, `TruncatablesState`, `TextureCoordinateType`, `TsConfigResolver`, `FragmentDefinitionMap`, `SVGDatum`, `BrickRenderOptions`, `DatabaseParameterSummary`, `MenuAction`, `FunctionAddInfo`, `CreateUserCommandInput`, `InputTree`, `ITransactionProps`, `Alt1`, `ReferenceParams`, `ComponentManager`, `UserActions`, `CompositeName`, `AppiumClient`, `AuthenticateEmailRequest`, `LiteColliderShape`, `LayerSpec`, `PackedTag`, `ParsedFileContent`, `SwaggerMetadata`, `ListResponse`, `ShaderSpec`, `ChangelogEntry`, `MaterialFactory`, `ExternalService`, `FolderView`, `RepoService`, `IListenerRule`, `HallMenus`, `ExpressionKind`, `StatsFieldConfiguration`, `IFeatureOrganizationUpdateInput`, `TAggregateCommit`, `InternalViewRef`, `Specialty`, `AddedKeywordDefinition`, `ApiClientResponse`, `ColumnModelInterface`, `StacksPrivateKey`, `DescribeDBClusterParameterGroupsCommandInput`, `StepperProps`, `SceneActuatorConfigurationCCSet`, `DynamicFormService`, `NotificationEntity`, `ContentTypeService`, `GeneratedFiles`, `ICandidateInterview`, `PerformanceEntry`, `ATOM`, `ResourcesToAttributions`, `IPagingTableState`, `SelectorNode`, `AuthContextProps`, `PrivilegeCollection`, `StateAB`, `TranscriptEvent`, `ReadonlyMat4`, `BasePin`, `ArianeeWalletBuilder`, `TimePanelProps`, `WithPLP`, `OptionalFindOptions`, `IPersonState`, `ButtonVariant`, `ExpressionFunctionDefinition`, `HlsEncryption`, `HiNGConfig`, `UiAtomType`, `TagProps`, `PageMetadata`, `WebCryptoDefaultCryptographicMaterialsManager`, `PipelineStageUnit`, `DeleteDataSourceCommandInput`, `DecodedTile`, `ResourceType`, `QueryParamsAsStringListMapCommandInput`, `uint8`, `GX.IndTexWrap`, `TLndConf`, `BoardSettings`, `RouterStateData`, `CategoryPreferences`, `Hmac`, `UpdateResourceCommandInput`, `DocumentInitialProps`, `TestingConfig`, `Realm.Object`, `MdcElementObserverAdapter`, `FileTreeComponent`, `INodeDetailResolverService`, `ShimFactory`, `Scrobble`, `CSSStyleSheet`, `SyncGroup`, `DebugProtocol.ConfigurationDoneArguments`, `vscode.TestRun`, `StickerExtT`, `PrivateDnsZoneGroup`, `InstallTypes`, `RgbTuple`, `GX.AlphaOp`, `RowOutlet`, `ResolverFn`, `AnimationTrackComponent`, `SlopeWallet`, `ECSSystem`, `EntityStore`, `CanvasFillRule`, `ArgOptions`, `EventPriority`, `UserSubscriptions`, `is_pressedI`, `AngularFirestoreDocument`, `ExtendFieldContext`, `TRawConfig`, `MapItem`, `DeleteFolderCommandInput`, `AsyncReaderWriterLockWriter`, `OnCallback`, `GLTF`, `ShapeType`, `TileLoaderState`, `ConfigPlugin`, `ConfigAction`, `DeckPart`, `ColumnType`, `AbstractServiceOptions`, `EngineRanking`, `SemanticTokensBuilder`, `NavSource`, `BattleDetail`, `ASScope`, `CSSValue`, `LogOptions`, `EmbedObj`, `FunctionTypeBuildNode`, `FetchableField`, `LayoutedNode`, `ServiceBinding`, `PluginImport`, `CdsIcon`, `MessageCallback`, `ReportsService`, `Agents`, `RouterProps`, `IGen`, `ControlItem`, `Flight`, `Dispatch`, `RawRestResponse`, `AbsoluteFilePath`, `CreateVolumeCommandInput`, `RectangleProps`, `NoopExtSupportingReactNative`, `PinType`, `IBufferCell`, `DescribeAccountAttributesCommandInput`, `DeleteNotificationsRequest`, `FileResult`, `BillingInfo`, `SelectModel`, `Footer`, `Triggers`, `AccountDevice_VarsEntry`, `TableMap`, `ValuedConfigurationMetadataProperty`, `EvaluationContext`, `AggsStart`, `MultipleLiteralTypeDeclaration`, `InputBoolean`, `StepProps`, `Mockchain`, `nodes.Node`, `DestroyOptions`, `HitInfo`, `AssemblyData`, `IPayload`, `Control`, `Asset`, `RunEvent`, `ProcessorModule`, `ILegacyScopedClusterClient`, `DDSTextureHolder`, `IFieldFormat`, `IRequestMap`, `IUri`, `NonNullable`, `TranslatorType`, `ProxyRule`, `Mapping`, `Dec`, `SphericalHarmonicsL2`, `StepArgs`, `LabelTable`, `SavingsManager`, `SelectionData`, `IDateStatistics`, `ElementProps`, `ConfigurableFocusTrap`, `DisabledTimeConfig`, `ExpandedEntry`, `MockDialog`, `DependencyResolver`, `IFsItem`, `EncodeOutput`, `ProjectReference`, `CartoonConfig`, `BlockBlobGetBlockListResponse`, `XanimePlayer`, `InteractionWaitingData`, `MutationRequest`, `ErrorFormatter`, `ComponentCtor`, `CrossBridgeAsset`, `TrackMapOptions`, `monaco.Range`, `KeyIcon`, `AndroidTarget`, `IJobConfig`, `ClassNameType`, `AnimationTrack`, `ResponsiveStorage`, `Channel`, `RowMap`, `FunctionImpl`, `RpcResponse`, `ServerWalletAPI`, `ApplicationQuestion`, `ScheduleType`, `StackResultsMatcher`, `JournalShowQueryParams`, `JSDocType`, `OperationGroupDetails`, `MapDispatchProps`, `PotentialPartnersState`, `InjectionToken`, `IServerError`, `ListRecommendationsCommandInput`, `BadGuy`, `IOptions`, `LitecoinjsKeyPair`, `SuiteNode`, `ExpressionAttributeValues`, `InterfaceTypeDefinitionNode`, `AutocompleteSettings`, `SendDataRequest`, `StrokeDrawingContext`, `Where`, `ITrack`, `IOutputOptions`, `Mocha.Suite`, `AppserviceMock`, `LoaderOptions`, `ObjectConsumer`, `Connex.Driver`, `LazyQueryHookOptions`, `GlobbyOptions`, `SVGAttributes`, `PortalProps`, `DragState`, `ModuleInstance`, `TranslateConfig`, `VueDecorator`, `ContextMenuService`, `ee.Emitter`, `JestProcess`, `IContainerRuntimeMetadata`, `ChannelCardType`, `CapabilitiesService`, `SavedObjectsMigrationConfigType`, `SendParams`, `InitCmdContext`, `WebGLVertexArrayObjectOES`, `GetAuthorizersCommandInput`, `IProtoTask`, `QueuingStrategy`, `EmissionsController`, `SuperAgentRequest`, `PackageResult`, `AlertDialog`, `ReferencesIdDictionary`, `IBasePath`, `ErrorCallback`, `Person_Employment`, `ViewPort`, `IMark`, `_IObjectMap`, `XcomponentClass`, `Images`, `StringValueNode`, `AttributeDerivatives`, `Queue`, `HsLanguageService`, `StoreConfiguration`, `Coda`, `AddressDTO`, `ViewBaseDefinition`, `ErrorHandler`, `GeneratorOptions`, `ListMembersCommandInput`, `DataRowItem`, `ProtocolResponse`, `Nuxt`, `LevelsActionTypes`, `NzAutocompleteOptionComponent`, `GetDatabaseCommandInput`, `FetchHandlers`, `URLLoader`, `GetRowLevelKeyFn`, `IEndpoint`, `NodeUnit`, `CheckStatus`, `MountedBScrollHTMLElement`, `TodoAppDriver`, `d.MatchScreenshotOptions`, `_1.Operator`, `Awaited`, `ResolvedTypeReferenceDirective`, `IDate`, `DiscussionEntity`, `TestEnv`, `ListAlertsCommandInput`, `PersonaId`, `CustomParameterGroup`, `XLSX.WorkSheet`, `ImportFacebookFriendsRequest`, `HLTVPageElement`, `Express.Multer.File`, `LambdaExpr`, `EditorContext`, `CollisionBox`, `Cone`, `MsgSignProviderAttributes`, `LinesResult`, `CompoundFixture`, `CategoryModel`, `ITask`, `IModelDecoration`, `ParameterChange`, `ChartScene`, `ColRef`, `FormulaOptions`, `ValueDescPair`, `ProjectsState`, `MatchPrefixResult`, `ROPCService`, `DialData`, `DaffCategoryFilterEqualRequest`, `SelectValue`, `HierarchicalItem`, `RpcRequest`, `ItiririAsync`, `OnConflictNode`, `Stripe.Event`, `PatternValueNode`, `SimpleAnalyzer`, `ActionBarProps`, `TextDrawer`, `HierarchyRectangularNode`, `InputComponent`, `ButtonOptions`, `IBackoffStrategy`, `SelectedIndexChangedEventData`, `SignInState`, `ImmutableBucket`, `ExecutionContract`, `SubscriptionResult`, `RemoteMessage`, `SymbolFormatFlags`, `SelectQuery`, `SolidityVisitor`, `Tools`, `RichEmbed`, `FacetFaceData`, `StaticSiteZipDeploymentARMResource`, `CompilerEventFileUpdate`, `GroupEventType`, `I18nUpdateOpCodes`, `FunctionMethods`, `ANDGate`, `FieldDescriptor`, `Type_Which`, `RepoConfig`, `MatchFunction`, `CalcFun`, `ShurikenParticleRenderer`, `SortCriteria`, `QRCodeSharedData`, `IPullRequestListItem`, `GherkinDocumentHandlers`, `matrix.MatrixArray`, `GfxRenderPass`, `IRGB`, `SanityDocument`, `requests.ListMfaTotpDevicesRequest`, `BasicInfo`, `ClonePanelAction`, `SimpleSignedTransferAppState`, `ScopedMemento`, `KeysRequest`, `StickyVirtualizedListState`, `ProjectStore`, `RangeAsyncIterable`, `IndexedAccessTypeNode`, `pointerState`, `d.ComponentRuntimeHostListener`, `Alternative`, `InputGenerator`, `HitTesters`, `ExtendedWebSocket`, `UseDropdown`, `dRes_control_c`, `PublisherDoc`, `TabContentItem`, `ExtendedVue`, `AttachmentData`, `CodePddlWorkspace`, `ResourceGroup`, `Real_ulong_numberContext`, `ProductFilterDTO`, `PerfState`, `SocketIOClient.Socket`, `TextEncoder`, `MockDataGenerator`, `GenerateConfig`, `HydrateFactoryOptions`, `TypeScriptService`, `Appointment`, `TransactionClientContract`, `UpdateConnectionCommandInput`, `IDict`, `States`, `QueryAccess`, `ParameterType`, `VariableGroupData`, `TreeGridAxis`, `React.Navigator`, `StyleCompiler`, `ListFlowsCommandInput`, `Availability`, `Undo`, `ProjectTilemap`, `TestParams`, `GameObjectInfo`, `DesignerTypeOption`, `ViewableRobot`, `AnnotationEventEmitter`, `StylusNode`, `ICompactPdfTextObj`, `IMatchResult`, `ScrollLogicalPosition`, `DateKey`, `IRoundResult`, `TResolver`, `Int128`, `RuleIteratorWithScope`, `BanGroupUsersRequest`, `NewPackagePolicyInput`, `Reminder`, `CacheNode`, `TrackData`, `Expected`, `GLTF.AccessorComponentType`, `ListRulesResponse`, `PuppetClassInfo`, `OptionsOrGroups`, `IHashProvider`, `ToastOptions`, `DataRecordValue`, `SGSCachedData`, `MappingTreeArray`, `AlexaLambda`, `ConcreteBatch`, `IAnnotation`, `PLSQLCursorInfosVSC`, `AlertComponent`, `EgressSecurityRule`, `VoiceAssistant`, `DeserializerContext`, `common.ClientConfiguration`, `RemoteHandler`, `ParseElement`, `JSONDiff`, `BulkInviteCommand`, `HandlebarsTemplate`, `TaskTiming`, `Deferrable`, `ItemInterface`, `RenderPlugins`, `T14`, `BasicProfile`, `NamedMouseElement`, `LinkTextLocator`, `apid.ManualReserveOption`, `PropertyAssignments`, `Sound`, `CreateMeetingWithAttendeesCommandInput`, `ISolution`, `ShuffleIterator`, `AudioSource`, `JsonAst`, `GameMarks`, `IKeyValue`, `ReflectedValueType`, `NodeDef`, `ForecastSeriesContext`, `CallHierarchyDeclaration`, `Introspector`, `tStartupOrShutdown`, `Sign`, `Highcharts.RangeSelectorButtonsOptions`, `AkimaCurve3d`, `EvaluatorOptions`, `IMediatorConfigurator`, `VirtualRows`, `VideoStreamIdSet`, `DurationEvent`, `DefaultClientMetricReport`, `PlyAdapter`, `PanResponderGestureState`, `ColumnReference`, `PgAttribute`, `MeshInfo`, `SerializeOptions`, `ContactSubscription`, `Demo`, `Review`, `WebGLContextWrapper`, `fabric.Object`, `ComponentTreeNode`, `RoleData`, `TestCaseInfo`, `StringOrNumberOrDate`, `webpack.Compiler`, `ThemeManager`, `EntryId`, `WorkerArgs`, `CodeActionParams`, `TokenAccount`, `ReadableData`, `ElementAspectProps`, `Segment1d`, `VariableModel`, `SigningMethod`, `APIRequest`, `requests.ListBucketsRequest`, `requests.ListCrossConnectGroupsRequest`, `VocabularyOptions`, `TestResultContainer`, `interfaces.Unbind`, `EventKeys`, `Progress.INeonNotification`, `messages.Scenario`, `RequestEvent`, `IGhcMod`, `UIError`, `ThemeExtended`, `Fig.Option`, `ResponseInterface`, `Urbit`, `IFeatureSet`, `ScheduleDoc`, `ThemeModeEnum`, `AthenaRequest`, `DisplayMarker`, `TestDataSource`, `MarkerInfoNode`, `CW20Instance`, `ICosmosTransaction`, `AnchorMode.Any`, `Droppable`, `SerializedObject`, `Behavior`, `LangOptions`, `DiffOptions`, `LightInstance_t`, `FactoryArgs`, `ParsedQRL`, `DirectoryInode`, `OnCleanup`, `Point3dArrayCarrier`, `ColumnDef`, `MDCListIndex`, `Browser.Interface`, `UtxoInfoWithSats`, `PureTransition`, `ProcessRequirement`, `Sigma`, `ListTargetsForPolicyCommandInput`, `PrayerTimes`, `VObject`, `SeekRange`, `RenderFlags`, `GetModelCommandInput`, `MockOtokenInstance`, `BaseTranslatorService`, `ICarsRepository`, `StateInstance`, `TS`, `RuleTransition`, `TracePrinter`, `HealthpointLocationsResult`, `NavigationEdge`, `TileMapLayerPub`, `TSQuerySelectorNode`, `App.webRequest.IRequestProcessor`, `bigint`, `ComparisonOperator`, `SummaryST`, `KeyInDocument`, `GX.TexPalette`, `ListFunctionsCommandInput`, `BaseMultisigData`, `ListCertificatesRequest`, `Http3PriorityFrame`, `BackupJSONFileLatest`, `CreateService`, `DiscordStore`, `WordCloudSettings`, `DAL.KEY_X`, `ECSqlValue`, `FileInode`, `RefundPayerStore`, `MemoOptions`, `AppModule`, `GlobalEnv`, `AssetReference`, `CLM.EntityBase`, `XmlParserNode`, `ConsumedCapacity`, `DescribeSchemaCommandInput`, `IGetProjectsStatistics`, `IValidationContext`, `ProxyReducer`, `mongoVisitor`, `VisibleTreeNodes`, `ClusterCollection`, `SessionsConfigSchema`, `TutorialModuleNoticeComponent`, `FileFilter`, `RouterSource`, `GenericIdModel`, `DynamoDbFileChange`, `DangerInlineResults`, `GreetingService`, `Frakt`, `CredValues`, `StoreAction`, `InjectedConnector`, `CachedNpmInfoClient`, `TypedTensor`, `CoordinateType`, `AdalService`, `GetPerspectiveOptions`, `t_6ca64060`, `Viewer.Viewer`, `ROLES`, `TreeBudgetEvent`, `ResponserFunction`, `MockData`, `LogAnalyticsCategory`, `FS`, `CompBitsValue`, `DropPosition`, `ZxBeeper`, `TaskExecutionSchema`, `VideoStreamOptions`, `ChannelJoin`, `DrawBufferType`, `DiagnosticSeverityOverrides`, `IUrlResolver`, `PadData`, `ShorthandPropertyAssignment`, `PokemonService`, `ValueReflector`, `SubscriptionAlreadyExistFault`, `AuthProviderProps`, `MathsProcessor`, `IterationStatement`, `Reshape`, `ModuleModel`, `MaybeTypeIdentity`, `TaskRun`, `ReifiedType`, `CustomFeatureConfig`, `LoadEventData`, `OverlayContainer`, `addedNodeMutation`, `CliHttpClientOptions`, `MediaStreamsImpl`, `RequestsService`, `KamiConfig`, `DNSAddress`, `UpdaterService`, `BotTags`, `ElementMaker`, `RenderingOptions`, `NotifyService`, `SearchQueryCtx`, `Json.ParseResult`, `InstancePrincipalsAuthenticationDetailsProviderBuilder`, `DOMQuery`, `GluegunToolbox`, `IBoundingBox`, `CacheOptions`, `PageDensity`, `eventType`, `FunctionalLayout`, `PluginValidateFn`, `NewBlock`, `ActorRenderModeEnum`, `DurationLike`, `TLBounds`, `IPositionComponent`, `UpdateUserRequest`, `PS`, `WalkNode`, `DeleteAccountsValidationResult`, `RuntimeIndex`, `LongOptionName`, `angular.IQService`, `CloningRepository`, `CurveCollection`, `IComparatorFunction`, `ParamSpecEntry`, `next.AppLayer`, `RTCConfiguration`, `BitbucketPipelines`, `ResponseComment`, `DemographicCounts`, `CameraState`, `PanelPackage`, `ProductControlSandbox`, `Http3Header`, `ProtocolRequestType`, `DeleteTemplateCommandInput`, `GameObject`, `Md.List`, `d.StyleCompiler`, `KeychainCredential`, `SubnetMapping`, `CreateMediaDto`, `Decibels`, `TransferRequest`, `ImportsAnalyzerResult`, `VdmComplexType`, `OpenSearchDashboardsSocket`, `Img`, `PostService`, `FileRange`, `BinarySwitchCCSet`, `CtrNot`, `ProviderConfig`, `StopDBClusterCommandInput`, `TextEditorViewColumnChangeEvent`, `FrameManager`, `ServerMap`, `GitHubLocation`, `AppStoreReplay`, `TableInterface`, `StatusBarAlignment`, `AlgBuilder`, `AsyncFactory`, `OhbugUser`, `Codeword`, `PDFHeader`, `MediaService`, `TreeNodeInfo`, `NotificationsServiceStub`, `Shadows`, `MythicAction`, `IFeatureFlag`, `EngineOptions`, `TestFile`, `SPNode`, `OBS`, `CeloTokenType`, `UUIDType`, `AddApplicationOutputCommandInput`, `LocalStorage`, `Events`, `parse5.DefaultTreeElement`, `IRemoteTargetJson`, `Indentation`, `SearchActions`, `GaugeSettings`, `SchemaMap`, `IDBOperator`, `SysTask`, `UserLogin`, `ITodo`, `requests.GetProjectRequest`, `AxiosError`, `HookProps`, `IOptionSelectText`, `TranslationState`, `Calendar`, `HTMLHeadElement`, `ObjectPage`, `OutboundTransport`, `ErrorResponse`, `CommBroker`, `CommonIdentity`, `GeometryCollection`, `requests.ListAutonomousVmClustersRequest`, `MerchantEntity`, `SandDance.types.Column`, `EditableTextStyle`, `EventPayload`, `PagedParamsInput`, `WebGLTimingInfo`, `ThemeValueResolver`, `HashChangeEvent`, `InlineConfig`, `types.Message`, `BenchmarkResult`, `ProblemModel`, `DetailsProps`, `ConnectionMetrics`, `IRouteTable`, `DashLowerthirdNameInputElement`, `TaskExitedEvent`, `MDCBaseTextField`, `IStatus`, `TestServerHost`, `CustomRenderer`, `WorkRequestLog`, `Artwork`, `NavigationExtras`, `ts.ConciseBody`, `serialization.ConfigDict`, `ActiveOverlay`, `Episode`, `OperationContext`, `cp.ForkOptions`, `DescribeReportDefinitionsCommandInput`, `Portal`, `RecurringBillPeriod`, `FieldTypeMetadata`, `RendererService`, `IUserModel`, `UpdateEnvironmentCommandInput`, `IHost`, `ts.TypeNode`, `PrivateIdentifierInfo`, `CreateMessageDto`, `SendTable`, `CallMethodRequestLike`, `d.PlatformPath`, `Deep`, `NVMJSONNodeWithInfo`, `IProfileLoaded`, `AzExtParentTreeItem`, `Private.PaintRegion`, `PushRequest`, `WebsocketProvider`, `ConvertIdentifier`, `NormalModule`, `CodeEditorMode`, `LockState`, `CfnExpressionResolver`, `TypeList`, `IPQueueState`, `RegExpMatchArray`, `Surface`, `SystemMessage`, `MetadataORM`, `IMessageRepository`, `PaletteOptions`, `FilterStatusValues`, `IHandleProps`, `IDBEndpoint`, `ACrudService`, `ViewInfo`, `MyComponent`, `LineSide`, `requests.ListWorkspacesRequest`, `StructuredType`, `EmojiService`, `RecommendationCount`, `CallExpressionArgument`, `Generatable`, `CspConfig`, `Features`, `TimeHistoryContract`, `FaceletCubeT`, `CipherResponse`, `IInputHandler`, `AppClientConfig`, `SwitchFunctorEventListener`, `IEqualityComparer`, `IterableActivity`, `TransportSession`, `ExpressionResult`, `WebSiteManagementModels.SiteConfig`, `Documentation`, `d.ComponentCompilerListener`, `IdMap`, `ToolItemDef`, `React.Route`, `ExpectedNode`, `ExpressionFunctionParameter`, `P9`, `Script`, `MockEventListener`, `VideoTexture`, `MagicString`, `LexoInteger`, `ClientRenderOptions`, `EPickerCols`, `cdk.StackProps`, `StoreConstructor`, `ReactClientOptionsWithDefaults`, `WebProvider`, `DataStateClass`, `CLR0`, `Graphql`, `SegmentEvent`, `IGameUnit`, `TableImpl`, `WebGLShaderPrecisionFormat`, `AuthHeaders`, `UpdateGatewayInformationCommandInput`, `CreateApplicationRequest`, `TaskProvider`, `DataProps`, `RestPositionsResponse`, `DeviceMetadata`, `HsDrawService`, `Vec3`, `BuildMiddleware`, `IDocumentManager`, `AppContextType`, `IChip`, `Mirror`, `RouteNode`, `AccountFacebook`, `WebpackConfiguration`, `Monad2C`, `HeroAction`, `UploadxService`, `TouchData`, `FormControlConfig`, `SlicedExecution`, `IBlockchainsState`, `StrictEventEmitter`, `PartitionBackupInfo`, `TextRangeCollection`, `BranchSummary`, `ITaskData`, `ProgramInfo`, `Registers`, `DOMPoint`, `CodeActionCommand`, `IMidwayBaseApplication`, `IMidwayBootstrapOptions`, `OHLCPoint`, `LogInfo`, `IStringDictionary`, `ArtifactItemStore`, `BufferData`, `OnEffectFunction`, `Rental`, `GfxAttachmentState`, `AjaxResponse`, `DeployResult`, `PublicAccessBlockConfiguration`, `LeanDocument`, `IOperatorIdentifier`, `InterfaceWithValues`, `NodeJS.WritableStream`, `NodeSet`, `MDCShapeScheme`, `StatusContext`, `Tax`, `GlobalsSearch`, `Post`, `Keyword`, `IEquipment`, `IQueryState`, `MDCLineRippleAdapter`, `AdminGameEntity`, `CustomSeriesRenderItemAPI`, `IOidcOptions`, `Simplify`, `IColumnRelationMetadata`, `EntityCollectionReducer`, `Vue`, `SwitcherState`, `SubjectInfo`, `SubscriptionClass`, `IMiddlewareGenerator`, `QCBacktest`, `cc.Prefab`, `ReadOptions`, `ICharAtlasConfig`, `GpuInformation`, `TagsFilter`, `IKeyQuery`, `CsvGenerator`, `Empty`, `ComponentInterface`, `UserView`, `ReactTestRenderer`, `GetDatabasesCommandInput`, `CurrencyToValue`, `GLclampf3`, `ExtractedCodeBlock`, `CanvasSpace`, `TNSCanvas`, `BroadcasterService`, `RobotApiRequestOptions`, `FrameStats`, `ValProp`, `CreateDirectoryCommandInput`, `GLRenderingDevice`, `FlowListener`, `RedisModuleOptions`, `FragmentedHandshake`, `ProcessEvent`, `GeoPolygonFilter`, `ZeroPadding2DLayerArgs`, `TestScriptOptions`, `Pkcs12ReadResult`, `ProductState`, `SpeakerWithTags`, `AnnotatedFunctionInput`, `PointItem`, `sdk.RecognitionEventArgs`, `StandardTask`, `AbsolutePath`, `IDataViewOptions`, `WebGLRenderbuffer`, `PDFDocument`, `Phaser.Geom.Point`, `InvestDateSnapshot`, `ContentReader`, `UiMetricService`, `QueryOutput`, `P6`, `EthereumNetwork`, `RopeBase`, `MongoRepository`, `GaussianDropoutArgs`, `Reconciliation`, `requests.ListInstancePoolInstancesRequest`, `GetUsageStatisticsCommandInput`, `VertexLayout`, `SubscriptionEnvelope`, `GherkinDocumentWalker`, `IRun`, `ApiPromise`, `BehaviorNode`, `CompletedLocalIpcOptions`, `CompositeBatch`, `TextEditAction`, `SearchFacetOperatorType`, `CompileTarget`, `ListenCallback`, `Assertions`, `TRPCError`, `StepDefineExposedState`, `VariableNames`, `BaseType`, `Declarator`, `ModdedBattleScriptsData`, `JQueryEventObject`, `ScreenshotService`, `ObjectKeyMap`, `NodeJS.Timeout`, `CommittersDetails`, `TemplateCompiler`, `CronConfig`, `IOctreeObject`, `GADRequest`, `RecursiveStruct`, `KubeConfiguration`, `EncryptionContext`, `ParsedCommandLine`, `CapnpVersion`, `SingleSigSpendingConditionOpts`, `InternalServiceErrorException`, `RouteOptions`, `TestPlan`, `Fragment`, `IFileSystemCreateLinkOptions`, `DatabaseFeatureOptions`, `ToolbarDropdownButtonProps`, `QueryResponse`, `FileHandler`, `OffsetRange`, `VirtualMachineRunCommandUpdate`, `DescribeInstanceAttributeCommandInput`, `HistoryInstructionInfo`, `TutorialDirectoryNoticeComponent`, `ComponentHolder`, `IStepInfo`, `ɵAngularFireSchedulers`, `TSFunDef`, `ThyAbstractOverlayRef`, `InputMap`, `CanvasFontWeights`, `CheckerType`, `DbCommand`, `CombatGameState`, `IViewRegionsVisitor`, `EthersBigNumber`, `UpgradeConfigsParams`, `messages.SourceMediaType`, `TileAttrs`, `BckCtrlData`, `AppAction`, `Anchor`, `GameId`, `SiteService`, `BaseArtifactProvider`, `TabularRows`, `PromiseRejectedResult`, `UserCreateInput`, `IViewbox`, `AuthenticationResult`, `SimpleGit`, `Traversable`, `esbuild.OnLoadArgs`, `WsClient`, `ImageAssetService`, `DmarcState`, `LegacyDateFormat`, `NamedArgTypeBuildNode`, `PropertyDataChangeEvent`, `MethodsOrOptions`, `DeployedBasset`, `ts.ExpressionStatement`, `SdkSubscribeAckFrame`, `ActivitySourceDataModel`, `GetResourcePolicyCommandInput`, `IResolvedUrl`, `xmlModule.ParserEvent`, `IFileSystem`, `SimpleWallet`, `IPathsObject`, `StockState`, `ScreenSize`, `FormControlName`, `SimNet`, `ChartRef`, `requests.ListNetworkSecurityGroupVnicsRequest`, `ResolvedId`, `NetworkInterfaceInfo`, `TextOffset`, `CookieAttributes`, `IPCMessage`, `SceneView`, `FastifyAdapter`, `http.Server`, `TempFlags`, `GadgetPropertyService`, `Painter`, `SplitField`, `JIterator`, `WorkerMessage`, `MigrationContext`, `FreeCamera`, `TaskConfig`, `Telegraf`, `SKU`, `WalletGroupTreeItem`, `IItemTree`, `OCSpan`, `Apollo.MutationHookOptions`, `Eyes`, `K.IdentifierKind`, `MockDirective`, `MockProvider`, `TJS.Definition`, `IModalState`, `DeleteDBClusterCommandInput`, `TableRowPosition`, `IQuiz`, `requests.ListOdaInstancesRequest`, `IAppOption`, `PkGetter`, `ConnectedProps`, `monaco.Position`, `U8Node`, `IndicatorProps`, `ExecutionPlanImpl`, `StepBinary`, `PluginType`, `QuickAlgoLibrary`, `BackstageItem`, `MonthYearDate`, `VideoFrameProcessorPipelineObserver`, `SubmitProfile`, `ExtraDataModel`, `PBRMaterial`, `RequestInfoUtilities`, `IFlowItemComponent`, `LogTracker`, `OverrideCommandOptions`, `AttributeTableData`, `IDynamicPortfolioColumnConfig`, `PossiblyAsyncIterable`, `XListNode`, `ColumnIndexMap`, `QueryResults`, `Ec2MetricChange`, `InstanceWrapper`, `StackLine`, `RtorrentTorrent`, `DirectiveBinding`, `DescribeFleetAttributesCommandInput`, `Fixed18`, `PositionType`, `Blending`, `IRenderContext`, `AllowedParameterValue`, `IBlockData`, `OAuth2Client`, `OperationObject`, `SVGUseElement`, `CreateSubscriptionRequest`, `SystemErrorRetryPolicy`, `NoteSequence`, `Traced`, `CompatibleDate`, `TypeUtil`, `ICustomer`, `MarkerRange`, `UsersAction`, `Journal`, `TestService`, `PerformanceStatistics`, `DeleteDBInstanceCommandInput`, `Union2`, `ProjectsStore`, `InstantiationNode`, `CssToEsmImportData`, `SFDefaults`, `AppContainer`, `MulticallRequest`, `IMatchableOrder`, `PartitionConfig`, `Svg`, `UIApplication`, `ResolverRule`, `GlTfId`, `Transcript`, `BumpInfo`, `TaskSchedule`, `EnumDescriptorProto`, `S2DataConfig`, `React.ComponentPropsWithoutRef`, `GfxRenderInstList`, `MutableVideoPreferences`, `DescribeSecurityProfileCommandInput`, `Logo`, `Telemetry.TelemetryEvent`, `MeetingCompositePage`, `ListAction`, `ChannelTokenContract`, `Expansion`, `DirectionMode`, `LQueries`, `AuthCredentials`, `GenerateResponse`, `IChamber`, `IdentifierContext`, `PreviousSpeaker`, `SessionType`, `TerraformStack`, `NSURL`, `SpecList`, `CandleStick`, `StageSwitchCtrl`, `QlogWrapper`, `ApplicationTokenCredentials`, `AppointmentId`, `EpicSignature`, `TypeOf`, `IDocument`, `App.services.IHttpChannelService`, `TokenConfig`, `tslint.RuleFailure`, `FileSystemHelper`, `SettingsRootState`, `MdcTabScrollerAlignment`, `DirectoryUpdate`, `CustomAtom`, `CollisionInfo`, `AbstractUserProxy`, `TransformPluginContext`, `TabNavigationBase`, `ScriptTask`, `PointComposition`, `FromSchema`, `IAmazonLoadBalancer`, `Values.ReadyValue`, `IAnimationKey`, `FormControlState`, `NgxFileDropEntry`, `ListAssociatedResourcesCommandInput`, `PlayerState`, `TaskComponentState`, `StaticService`, `AccessTokens`, `PiEditConcept`, `TestComponent`, `PrintLabel`, `NlsBundle`, `ParsedTag`, `IApplicableSchema`, `SchemaEntry`, `CacheFileList`, `UberPBRMaterial`, `TranspileOptions`, `FuzzyLocale`, `ObjectContainerParams`, `NumberAttribute`, `ApolloQueryElement`, `IRelease`, `ServerHello`, `InputElement`, `FormInternal`, `FirebaseFirestore.Query`, `ErrorConstructor`, `ObjectListResult`, `JwtConfigService`, `Execution`, `AssociatedName`, `TRequest`, `ThyAutocompleteRef`, `CommandMetadata`, `ActivatedRoute`, `MultiStats`, `BaseTypes`, `IClientInteraction`, `GLM.IArray`, `GetUserInfoQuery`, `IAsfObjectHeader`, `JSONSchemaStore`, `ListChannelBansCommandInput`, `StepFunctions`, `Algebra.TripleObject`, `Ecs`, `CSSSnippet`, `HoldSettings`, `Ethereum`, `StringLiteralNode`, `PositionGrid`, `MDCRippleFactory`, `Jsonified`, `_app`, `IAuthFormContext`, `QueryObserverResult`, `BlogEntry`, `CompositeCollider`, `TypeVblDecl`, `LSConfigManager`, `AbortSignal`, `GlobalMaxPooling1D`, `FileParseResult`, `ClearCollections`, `FeederData`, `InterfaceWithConstructSignatureOverload`, `OperationCallbackArg`, `PutFileOptions`, `TreeSelectOption`, `ISqlite.SqlType`, `InitializeServiceCommandInput`, `FurParam`, `Either`, `Macro`, `ListAnswersCommandInput`, `ElementEvent`, `StaticSiteUserProvidedFunctionAppARMResource`, `Bug`, `MarkInterface`, `ThyDragOverEvent`, `UhkDeviceProduct`, `ApiController`, `RawSourceMap`, `DriftConfig`, `TradeFetchAnalyzeEntry`, `CategorizedClassDoc`, `ThyPopoverContainerComponent`, `RequestResponder`, `VersionVector`, `Eq`, `NodeDocument`, `LocalStorageAppender`, `ListMenu`, `messages.Duration`, `DanmakuDrawer`, `GraphQLObjectType`, `SourceOffset`, `ContainerDefinition`, `PrismaClientConstructor`, `TVShow`, `LicensingPlugin`, `StoredOrder`, `IBlockOverview`, `InMemoryEditor`, `ChartProps`, `UserRecord`, `CustomUser`, `ParseState`, `debug.Debugger`, `OpenSearchdslExpressionFunctionDefinition`, `ListRegistriesCommandInput`, `Types.CodeGenerator.CustomGenerator`, `FirstMate.Grammar`, `MockCSSStyleSheet`, `IValidationOptions`, `SeriesDataType`, `IContentVisitor`, `IGlobal`, `IStateGlobal`, `Workshop`, `TKey1`, `BuilderCanvasData`, `MessageService`, `ESLCarouselSlide`, `Refable`, `Simulation3D`, `FolderUpload`, `TransportRequestOptionsWithOutMeta`, `TableSchemaDescriptor`, `ElementQueryModifier`, `PDFDocumentProxy`, `TypeFlags`, `NetworkVersion`, `BackendConfig`, `ODataResource`, `SHA3`, `CRS`, `FeatureDescriptor`, `TeamDocument`, `GLTFFileLoader`, `BufferVisitor`, `AccessTokenRequest`, `ProxyRulesSubscription`, `ValidatePurchaseResponse`, `CommandItemDef`, `UpdateAction`, `CloudFormationClient`, `LifecycleState`, `RowInfo`, `SvgToFontOptions`, `MIRVirtualMethodKey`, `EmitterContext`, `IUiAction`, `IDeployment`, `PagingOptions`, `IDBTransaction`, `DataViewField`, `FeatureStabilityRule`, `DocumentedType`, `TransactionDescription`, `AMM`, `RenderQueue`, `ProofService`, `SummaryArticle`, `TopicsMap`, `AccountWithAll`, `REPL`, `SwiperProps`, `XmlSerializerOptions`, `ICacheConfig`, `TranslationUnit`, `WrappedEntity`, `ModelType`, `Markup`, `ServerType`, `PermissionTree`, `StreamEmbed`, `AlertServicesMock`, `DevicePixelRatioObserver`, `TooltipValueFormatter`, `SQSEvent`, `IKeyboardEvent`, `ServiceWorkerGlobalScope`, `TDiscord.TextChannel`, `Sudo`, `ComponentInternalInstance`, `SelectOptionComponent`, `TiledTMXResource`, `ParameterObject`, `GenesisConfig`, `ActiveErrorMessage`, `OnPostAuthHandler`, `ForgotPassword`, `PopupProps`, `RuntimeMappings`, `ForwardRefRenderFunction`, `ITimeOff`, `ArrayOperation`, `GetFunctionCommandInput`, `GetBucketPolicyCommandInput`, `DomainEventSubscriber`, `InputLink`, `DataColumnDef`, `SceneGraphNodeInternal`, `Position3DObject`, `ProgramInput`, `PayableTx`, `Entrypoint`, `DependencyItem`, `UserAccount`, `Basset`, `SubtleButton`, `DeserializeAggConfigParams`, `HTMLDOMElement`, `Highcharts.AnnotationsOptions`, `ResolvedUrl`, `RequestInfo`, `AbstractParser`, `KeyboardListenerAPI`, `PageData`, `PredictablePickleTestStep`, `GLbitfield`, `MatchersObject`, `multiPropDiff`, `MediaQuery`, `NormalizedScalarsMap`, `TlcCode`, `ComponentCompilerState`, `requests.ListSecurityAssessmentsRequest`, `TagsObject`, `SEGroup`, `Bits`, `ScreenElement`, `InsightLogicProps`, `INameDomainObject`, `ObjectBinding`, `KeyState`, `PublicShare`, `provider`, `DefinitionInfoAndBoundSpan`, `Rational`, `WorkflowHooks`, `NumberDataType`, `ExportNamedDeclaration`, `BreakpointKey`, `VpcSecurityGroupMembership`, `ConsensusContext`, `ISceneDataArray`, `ExpressionFunctionOpenSearchDashboards`, `IAppEnvVar`, `DateOrDateRangeType`, `StyledComponentWithRef`, `VirtualDevice`, `MinecraftVersion`, `CommandType`, `StyleUtils`, `OnSuccess`, `PartyName`, `FooState`, `FsApi`, `Modification`, `ICData`, `ChangeNode`, `IPoint`, `UseSocketResponse`, `DomainEventClass`, `MessageEmitter`, `HTMLTitleElement`, `requests.ListSoftwareSourcesRequest`, `MFARequest`, `DrawingId`, `polymer.Base`, `EvmAccount`, `SocketIO`, `cheerio.Element`, `FirestoreForm`, `ChartUsage`, `CollectionFn`, `fromReviewerStatisticsActions.GetReviewerStatisticsResponse`, `RichTextProps`, `AxisType`, `FrameContainer`, `FaasKitHandler`, `CloseEvent`, `FiniteEnumerableOrArrayLike`, `Package.ResolvedFile`, `MessageSignature`, `MessagingService`, `MinecraftVersionBaseInfo`, `TestResult`, `IPCMessagePackage`, `HotObservable`, `server.Position`, `DictionaryFileType`, `MonitorModel`, `MutationConfig`, `Mocker`, `ArgumentsHost`, `ProcessedTransaction`, `ViewerConfiguration`, `AssertStatic`, `ParsedArgv`, `FavoriteTreeItem`, `ConnectionNode`, `CreateEnvironmentCommandInput`, `SubscriptionOption`, `AnnotationTooltipState`, `ResourceObject`, `SwitchCase`, `InlineFieldDescriptor`, `ActiveSelection`, `ResolvedDependency`, `DisplayNode`, `ApplicationTargetGroup`, `RequestFn`, `DemoFunction`, `Formats`, `LogHook`, `HttpApi`, `QueryAllParams`, `requests.ListZonesRequest`, `CommandLineConfiguration`, `CreateUserRequest`, `Bidirectional`, `GeoUnitDefinition`, `VehicleInfo`, `InstalledClock`, `ConstantJsExpr`, `CLR0_ColorData`, `DecimalArg`, `VgAPI`, `NodeFactory`, `LogMessage`, `ReferenceDescription`, `LogParse`, `DescribeEventSubscriptionsMessage`, `PickRequired`, `Events.exitviewport`, `SafeAreaProps`, `RendererType`, `RawSavedDashboardPanelTo60`, `TypeaheadState`, `SelectorType`, `IConnectionFactory`, `RedactChannelMessageCommandInput`, `ChangelogJson`, `TimelineTotalStats`, `UserDataService`, `SvgTag`, `PluginRevertAction`, `RequestListener`, `Glyph`, `ScannedFeature`, `GfxPass`, `CoreState`, `Proc`, `UpdateExceptionListItemSchema`, `CreateJobTemplateCommandInput`, `RuleMeta`, `MediaQueries`, `Term`, `_HttpClient`, `tf.fused.Activation`, `RuntimeContext`, `DetectedLanguage`, `DaffCategoryFactory`, `Delaunay`, `Matches`, `ICommandHandler`, `MaybeDate`, `IndexUUID`, `requests.ListChannelsRequest`, `TickViewModel`, `SelectorDatastoreService`, `CanvasIcon`, `PublicIdentifier`, `Moniker`, `ComboBoxMenuItemGroup`, `LanguageServiceDefaults`, `ResolverProvider`, `DependencyPins`, `LogAnalyticsSourceFunction`, `CurrentAccountService`, `BreadcrumbContextOptions`, `IPartitions`, `FormCookbookSample`, `IMenuItemProps`, `ExportMap`, `CartEntity`, `Simple`, `StringOptions`, `requests.ListClustersRequest`, `ComplexType`, `CohortType`, `StateUpdater`, `GitOutput`, `DocType`, `AggsState`, `JGOFNumericPlayerColor`, `WirePayload`, `SignedMultiSigContractCallOptions`, `IConsumer`, `DataRange`, `tensorflow.IFunctionDef`, `ResolveFn`, `NamedExports`, `Pane`, `LESSParser`, `WiiSportsRenderer`, `PhysicalKey`, `HSD_TEInput`, `IRect`, `IDimension`, `DirtyStyle`, `ArrayType2D`, `HeritageClause`, `NativeFunction`, `SSOLoginOptions`, `PortalPoller`, `PDFBool`, `IExistenceDescriptor`, `FsItem`, `MutableRef`, `UseQueryResponse`, `PricePretty`, `ConversationV3`, `DebtItemInterface`, `NestedContentField`, `PostMessageOptions`, `FbForm`, `IRouteItem`, `LogEvent`, `BigNumberFive`, `AbstractObject3D`, `commander.Command`, `AsyncSourceIterator`, `VStackProps`, `HorizontalAnchor`, `ExchangePriceQuery`, `FtrConfigProviderContext`, `IntervalOptions`, `OAuthUserConfig`, `IXulElementSpec`, `PopoverPlacement`, `RootCompiler`, `SemanticTokenData`, `NameMap`, `MapPlayer`, `SVType`, `StylableSymbol`, `IRenderable`, `LayoutPaneCtrl`, `HttpPayloadTraitsCommandInput`, `WebSocketProvider`, `SaveGame`, `UpdateSchemaCommandInput`, `ListEndpointsCommandInput`, `QueryTree`, `IManifestBindArtifact`, `AuditService`, `GraphQLModulesModuleContext`, `PrimType`, `PubPointer`, `ConfigPath`, `NgrxAutoEntityService`, `HdPrivateNodeValid`, `ObjectPattern`, `CompositeCollection`, `GlobalJSONContainerStorage`, `AssetResolver`, `TooltipType`, `Forward`, `RepositoryFactory`, `ServerErrorInfo`, `CertificateManager`, `requests.ListIPSecConnectionsRequest`, `SlideComponent`, `RenderStatus`, `Git.GitVersionDescriptor`, `NwtExtension`, `CompressionOptions`, `TagMapper`, `HTMLObjectElement`, `ModuleThis`, `EndRecordingRequest`, `ImportOrExportSpecifier`, `BitStream`, `AuthInterface`, `MockHashable`, `NumberEdge`, `DeclarationStatement`, `ReuseTabService`, `TCase`, `MagentoCart`, `styleFn`, `BlobServiceClient`, `TypeDefinitionParams`, `ITemplatizedCard`, `TimeResolvable`, `LinearLayout`, `net.Server`, `DataLoaderOptions`, `TLMessage`, `FakeMetricsCollector`, `Music`, `ThyGuiderRef`, `MoveCommand`, `FilterContext`, `CompletionItemProvider`, `ResourceTimelineViewWrapper`, `backend_util.TypedArray`, `PersistentCache`, `CraftTextBlock`, `IShapeBase`, `ObjectShape`, `FeedFilter`, `MacAddressInfo`, `ElementStylesModifier`, `ResponseHeader`, `requests.ListGrantsRequest`, `FocusableElement`, `ValueMapper`, `ITimeOffCreateInput`, `ApiEnumMember`, `FeatureContext`, `InputNodeExpr`, `CustomerAddress`, `LayerArrays`, `Cancellable`, `TsoaRoute.Models`, `ListDatasetImportJobsCommandInput`, `Exact`, `ListDatasetsResponse`, `ListJobsCommandInput`, `IntrospectionQuery`, `PrefixUnaryExpression`, `EquivMap`, `ASTTransformer`, `BottomSheetParams`, `ViewRegionInfoV2`, `WFDictionaryFieldValueItem`, `PerspectiveDataLoader`, `IOptionsFullResponse`, `CartService`, `TmdbTvDetails`, `messages.TestStep`, `FishSprite`, `FunctionAnnotationNode`, `DataViewBaseState`, `IOpenApiImportObject`, `DappInfo`, `requests.ListClusterNetworksRequest`, `IMediatorMapping`, `Delay`, `NotebookFrameActions`, `ChipsItem`, `ResultEquipped`, `WriteGetter`, `MockNgZone`, `MonthAndYear`, `KeyListener`, `ReferenceInfo`, `DatabaseTable`, `ControllerInstance`, `PostList`, `TestCollection`, `CompilerEventFileAdd`, `ThemeProps`, `LoggerParameters`, `ToolkitInfo`, `t.Comment`, `PushNotificationData`, `MapLayerSource`, `SyncPeriod`, `Set`, `PropertyModel`, `NetworkProfile`, `VectorTileDataSource`, `CompiledResult`, `SelectAction`, `BaseStruct`, `JsonFormsAngularService`, `FontNames`, `WebGLContext`, `P`, `RootOperationNode`, `LoginTicket`, `ReboostPlugin`, `ActivationLayerArgs`, `MarkBuilder`, `HTTPClient`, `KeyMapping`, `IncomingWebhook`, `UnionMember`, `ConfigFile`, `WritableStreamBuffer`, `ApiTypes.Groups.MessagesById`, `IHttpResponse`, `StyleResourcesFileFormat`, `DeleteAssetCommandInput`, `AuthProvider`, `MyCustomObservable`, `Activity`, `SlaveTimeline`, `GenericLayout`, `InterfaceAliasExport`, `Car`, `PrerenderUrlRequest`, `QueryRequest`, `GitUri`, `RegEntity`, `GetSettingSuccessCallbackResult`, `SavedObjectsResolveImportErrorsOptions`, `QComponent`, `Field_Slot`, `DeleteClusterCommandInput`, `Parser`, `ColumnRow`, `typescript.CompilerOptions`, `AppDefinitionProps`, `ParameterTypeModel`, `W2`, `TransformComponent`, `AsyncCallback`, `HydrusFile`, `BoundSideType`, `Info`, `DescribeMLModelsCommandInput`, `SyscallManager`, `RenderingDevice`, `WorkflowStepOutputModel`, `GX.IndTexScale`, `CeramicSigner`, `SdkClientMetricFrame`, `Tray`, `GlobalEventHandlers`, `SearchFilter`, `SigninOrSignupResponse`, `IConfigurationSnippet`, `IndexMap`, `ExternalLoginProviderInfoModel`, `DeleteFileSystemCommandInput`, `XIdType`, `NucleusApp`, `NativeImage`, `IVanessaEditor`, `MessageThreadStyles`, `SFARenderLists`, `DisplayListRegisters`, `SelExpr`, `GitDSL`, `MultisigBitcoinPaymentsConfig`, `AtomShellType`, `RoutableTileNode`, `OrbitControls`, `ComponentProps`, `f64`, `AppJob`, `WellState`, `WrapperProps`, `Sketch`, `ApplicationLoadBalancedFargateService`, `Shader3D`, `CustomSetting`, `ONodeSet`, `UpdateQueryBuilder`, `SearchFiltersState`, `ReaderObservableEither`, `UseTimefilterProps`, `TermType`, `DeleteChannelCommandInput`, `DSVEditor.ModelChangedArgs`, `TableName`, `PostgresConnectionOptions`, `Collider`, `NotRuleContext`, `Delaunator`, `Survey.Question`, `NewLineToken`, `Watch`, `LinkLabelVM`, `LoginCommand`, `BlockState`, `MeterChange`, `PathType`, `TokenFilter`, `GalleryApplicationVersion`, `ZRText`, `CompositeOperator`, `UIFileHelper`, `CmsModel`, `PropertyMatcher`, `ICategoryBins`, `CompletionList`, `ISummaryTreeWithStats`, `ResourceHandlerRequest`, `NormalDot`, `PluginEvents`, `ExportType`, `LanguageCode`, `WatcherMap`, `StartFlowCommandInput`, `BodyDatum`, `Deque`, `MonitoringMessage`, `PseudoElementSelector`, `ExecuteShellCommandFunction`, `AutoTranslateSummaryReport`, `ExportAssignment`, `requests.CreateJobRequest`, `UploadItem`, `ScriptContainer`, `ViewMeta`, `TokenParams`, `SpringValue`, `JPAExtraShapeBlock`, `OpenAPIV3.ParameterObject`, `Storybook`, `INumberDictionary`, `MeasureMethod`, `EnumOption`, `ResetPasswordAccountsValidationResult`, `PermissionsData`, `SwitchNodeParams`, `SentryRequestType`, `browser.runtime.MessageSender`, `CustomToolbarItem`, `Angulartics2Matomo`, `SimpleSavedObject`, `XStyled`, `AutofillScript`, `AttachmentService`, `ColorRegistry`, `Nodes.NameIdentifierNode`, `ICurrentWeather`, `UtxoInfo`, `Setting`, `Style`, `ListBranchesCommandInput`, `ICountryGroup`, `Range3dProps`, `ConstructorType`, `AccountProps`, `Adapt.AdaptElement`, `ElementGeometryCacheOperationRequestProps`, `DeleteUserResponse`, `FastRTCPeer`, `DaoTokenWrapper`, `TreeSet`, `Common.ISuite`, `EmployeeStatisticsService`, `AcceptedNameType`, `nodes.Declaration`, `PropertyMetadata`, `ReacordTester`, `ParsedDid`, `PublishJob`, `ConfigBuilder`, `AnyNgElement`, `CreateReactClientOptions`, `OrderByClause`, `IRuleOption`, `internalGauge`, `ParamNameContext`, `EntityMapperService`, `CS`, `purgeCommandCriteria`, `APProcessorOptions`, `SExpressionTemplateFn`, `TrackingOptions`, `LoopMode`, `Nothing`, `Scroller`, `StyledVNode`, `ShardFailure`, `IChunkOffsetBox`, `IVisitor`, `DrawCommand`, `DataConnection`, `StatusCode`, `EncryptionMaterial`, `Breadcrumb`, `StaticProvider`, `UseLazyQueryOptions`, `UnaryOperator`, `CreatedOrder`, `_Record`, `PadplusMessagePayload`, `OnItemExecutedFunc`, `AddRepositoryPayload`, `messages.TestStepResult`, `ServiceEndpointPolicy`, `IAureliaProject`, `tr.events.Name`, `IGenericTag`, `requests.ListSourcesRequest`, `RawSavedDashboardPanel730ToLatest`, `StepSelection`, `CLM.ActionBase`, `OnConflictUpdateBuilder`, `WorkspaceMap`, `IEmployeeAppointmentCreateInput`, `ActionSheet`, `VisualizeUrlGeneratorState`, `RequestSelectorState`, `IDebugger`, `GetObjectRequest`, `TriggerData`, `IScriptCode`, `PackageTypeReport`, `GraphExportedPort`, `FluentIterable`, `WritableDraft`, `Animated.EndCallback`, `Article`, `CompatConfig`, `NameSpaceInterface.Interface`, `IProviderInfo`, `FIRDocumentReference`, `RedBlackTreeNode`, `GetByEmailAccountsRequestMessage`, `Datasources`, `ArenaSceneExtraProps`, `S3URI`, `i18n.Message`, `GUID`, `ProtectionRule`, `CopyTask`, `UpdateProjectCommand`, `MDCTextField`, `ChainIndexingAPI`, `SerializationOption`, `HsLayerUtilsService`, `StringEncoding`, `TypeVariable`, `TelegrafContext`, `ThreeSceneService`, `express.NextFunction`, `StrokeOptions`, `mm.INativeTagDict`, `OptionConfig`, `MapLike`, `SConnectableElement`, `QueryEnum`, `IReaderRootState`, `BaseResource`, `HttpCall`, `GameType`, `PaymentIntent`, `ListGrantsRequest`, `UseCaseLike`, `ComponentRuntimeMetaCompact`, `FactPath`, `MenuEvents`, `MerchantService`, `AttachmentResponse`, `SpotifyService`, `solG1`, `LiveListItem`, `AnnotationActionTypes`, `CancellationErrorCode`, `requests.ListOAuthClientCredentialsRequest`, `ServiceAccount`, `EmbeddableStateWithType`, `IdentityArgs`, `ProductVariant`, `CustomBlock`, `NotWrappable`, `MDCAlertControllerImpl`, `Nes`, `AuthorizedRequest`, `Resetter`, `TicketMod`, `BindingWhenOnSyntax`, `NativePlatformDefinition`, `ChatEvent`, `IConnectedNodes`, `AuthClientInterface`, `DebugProtocol.Variable`, `ConvertFn`, `ASSET_CHAIN`, `VisParams`, `IShaderMaterialOptions`, `VuexModuleConstructor`, `ILanguage`, `ISampleToChunkBox`, `ScrollByY`, `Bluebird`, `Enable`, `NSIndexPath`, `EntryNode`, `SignatureHelpItems`, `IRenderParameters`, `CONNECTION_STATUS`, `NonNullableSize`, `FocusedCellCoordinates`, `Challenge`, `MarkdownTableRow`, `SeriesComposition`, `CourseUser`, `EuiTheme`, `IncomingRequest`, `CanvasType`, `OasParameter`, `ValueAttributeObserver`, `NextPageWithLayout`, `UpdateProjectCommandOutput`, `Metrics`, `EntityResolver`, `IPackageDescriptor`, `ToggleableActionParams`, `ITiledObject`, `nsIFile`, `SParentElement`, `WeapResource`, `WidgetFactory`, `AgAxisLabelFormatterParams`, `SettingsRow`, `Caller`, `UpdatedLazyBuildCtx`, `Events.postframe`, `DataModel.Metadata`, `MODEL`, `EventEmitter2`, `ITemplates`, `SqlOutputContentProvider`, `SocketIOGraphQLClient`, `SignedMessageWithOnePassphrase`, `ITkeyError`, `SessionToken`, `SemanticTokensLegend`, `tabItem`, `row`, `TextStyleProps`, `WebSocket.CloseEvent`, `IterationState`, `SpannedString`, `IBoxPlotData`, `BlockWithChildren`, `BuiltIns`, `BreakOrContinueStatement`, `WrapEnum`, `VBox`, `FilesystemDirectoryNode`, `RowParser`, `MoonBoard`, `PeerContext`, `D3Interpolator`, `NavParams`, `UIMillStorage`, `PBBox`, `ValidationConstraints`, `FcModel`, `GraphQLService`, `MkReplaceFuncStore`, `AcceptResult`, `Tilemap`, `IEventHandlerData`, `LogGroup`, `IFabricWallet`, `https.Server`, `PartitionKeyParams`, `PartialCanvasThemePalette`, `Hotspot`, `IncrementalParser.SyntaxCursor`, `FlattenLayerArgs`, `Calendar_Contracts.CalendarEvent`, `AwilixContainer`, `ClassWeightMap`, `Date`, `DecimalAdjustOptions`, `EdgeLabels`, `Insertion`, `JSDocSignature`, `ContentDescriptorRequestOptions`, `PluginApi`, `AppInstance`, `KeyData`, `KvMap`, `ResourceItemXML`, `Deletion`, `DispatchPropsOfControl`, `SizeObject`, `LocalizableString`, `Z`, `TreeViewItem`, `PDFName`, `TAttrs`, `Ret`, `QueryPaymentsRequest`, `DateTimeService`, `CallbackHandler`, `PvsioEvaluatorCommand`, `FormlyFieldConfig`, `ISettingsIndexer`, `Consola`, `SearchFilterConfig`, `IRenderService`, `MessageTypes`, `GraphQLHOC`, `t.Context`, `DocTableLegacyProps`, `SavedObjectsImportRetry`, `IReducerMap`, `IStructuredLicense`, `DeleteProfile`, `Counter2`, `ISqlCommandParameters`, `CallableConfig`, `StoriesDefaultExport`, `ThemePalette`, `DeleteStreamCommandInput`, `SecretData`, `DropdownService`, `TypeCondition`, `ITodosState`, `DeliveryTarget`, `InsightModel`, `IReduxStore`, `RefCallback`, `MagnetarInstance`, `PermissionsResource`, `TsOptionEngineContext`, `IModelTransformer`, `Rect`, `GetBotChannelAssociationsCommandInput`, `RulesByType`, `PopoverContextValue`, `GfxVertexAttributeDescriptor`, `RequiredStringSchema`, `RTMClient`, `ValidatorOptions`, `CreateParameterGroupCommandInput`, `ArrowCallableParameter`, `Range3d`, `ts.TypeAssertion`, `DetectionResultRowIndicatorColumn`, `ModalProps`, `ResourceDefinition`, `BinarySearchTreeNode`, `DateWrapperFormatOptions`, `Clients`, `SpotSession`, `ModuleConfig`, `CustomCameraControls`, `QueryOptions`, `Move`, `SpawnOptions`, `AllureConfig`, `PannerNode`, `OpenSearchDashboardsDatatableRow`, `UIBezierPath`, `ApiNotificationSender`, `TypedUseSelectorHook`, `ManagementApp`, `MenuListProps`, `ContentSource`, `PeerCertificate`, `ImageGLRenderer`, `SortParam`, `DescribeReservedInstancesCommandInput`, `CredentialManager`, `UpdateWebhookCommandInput`, `Pocket`, `AttributeMap`, `MagickInputFile`, `Dialogue.Config`, `Highcharts.JSONType`, `ProjectTemplate`, `ListColumnSetting`, `MeetingHistoryState`, `SliderCheckPoint`, `ControllerProps`, `CrowbarFont`, `StudioVersion`, `LogInRequest`, `IBasicProtocolMessage`, `IGetExpenseInput`, `NoncondexpressionContext`, `RecordFormat`, `IProtonAccount`, `ExpressionFunctionOpenSearchDashboardsContext`, `ParseTreePattern`, `NgElementConstructor`, `MatSliderChange`, `RemoteSourceProvider`, `Insert`, `CreateConnectionRequest`, `ProjectActions`, `RandomSource`, `ITimeLog`, `PropName`, `Validation`, `ActionParamException`, `CoreTypes.PercentLengthType`, `UrlWithParsedQuery`, `HTMLScLoadingSpinnerElement`, `IBase`, `TermRows`, `ToneAudioNode`, `BlobInfo`, `SubMenuProps`, `AnimatableElement`, `DialogProps`, `requests.ListAppCatalogListingsRequest`, `MockReaction`, `CachedUpdate`, `GfxSamplerDescriptor`, `NeovimClient`, `AccessorDeclaration`, `RBNFSet`, `IContextView`, `IndicatorAggregateArithmetic`, `ReflectiveInjector`, `ProxyInstance`, `FireCMSContext`, `IEntries`, `IndexedColumn`, `ClientOptions`, `CloudServiceResponse`, `FasterqQueueModel`, `PrEntity`, `ModelTemplate`, `UpworkService`, `ServiceExitStatus`, `d.ComponentCompilerData`, `SendView`, `SidePanelRanking`, `Mutex`, `PropsWithUse`, `d.InMemoryFileSystem`, `ts.server.Project`, `PgNotifyContext`, `AddonActions`, `AAAARecord`, `EmitAndSemanticDiagnosticsBuilderProgram`, `flatbuffers.ByteBuffer`, `HTMLMediaElement`, `StripeAddress`, `PromisedAnswer`, `XYZProps`, `DiContainer`, `VectorView`, `PropertyTreeNodeHTMLElement`, `vscode.TextEdit`, `CommentData`, `K8sManagement`, `NETWORK_NAME`, `PermutationSegment`, `TSender`, `GenericDefaultSecond`, `types.TextDocumentIdentifier`, `HelpList`, `MDBModalRef`, `NumericB`, `PatternAsNode`, `tracing.ReadableSpan`, `RawShaderMaterialParameters`, `Classifier`, `MockedResponseData`, `AuthController`, `FIRAuthDataResult`, `EngineArgs.PlanMigrationInput`, `MagentoAggregation`, `TestExporter`, `AcronymStyleOptions`, `BackgroundState`, `QueuedEventGroup`, `FlushConfig`, `TavernsI18nType`, `CreateError`, `OrientedBox3`, `MethodArgsRegistry`, `ConfigValues`, `NodeEvent`, `BucketAggParam`, `CollisionSolver`, `DimensionDetails`, `NextCurrentlyOpened`, `FtrProviderContext`, `Netlify`, `CreateInstanceProfileCommandInput`, `CompiledExecutable`, `TaskArguments`, `FilterMode`, `CredentialResponseCoordinator`, `requests.ListFastConnectProviderVirtualCircuitBandwidthShapesRequest`, `GraphinProps`, `TargetTrackingConfiguration`, `PackageData`, `DaffLoginInfo`, `SwingRopePoint`, `SFAMaterial`, `G1`, `NodeStatus`, `FeaturePipelineState`, `TransferItemFlatNode`, `ReferencedSymbolDefinitionInfo`, `RpcConnection`, `BigBitFieldResolvable`, `IServiceProvider`, `EventActionHandler`, `ListBase`, `HashTag`, `esbuild.OnResolveResult`, `VideoConverterFactory`, `CreateServiceCommandInput`, `BrandC`, `Order`, `CRDTArray`, `MicrosoftSynapseWorkspacesSqlPoolsResources`, `TeleportService`, `MockBroadcastService`, `DirectiveDefinition`, `IServer`, `RMCommandInfo`, `IMidwayApplication`, `ServiceTreeItem`, `PanResponderInstance`, `yubo.MainReducer`, `RecentlyClosedEditor`, `BasePlugin`, `ScriptableContext`, `DomainCategory`, `ControlFlowEnd`, `SVAddr`, `TimelineNonEcsData`, `DocReference`, `NormalizedNodeType`, `ICandidateFeedback`, `SyncDB`, `MockStoreEnhanced`, `CollectionFactory`, `PipelineValue`, `AssertLocationV2`, `TFLiteModel`, `ProjectInformationStub`, `ManifestInstance`, `AdBreak`, `ToolManagerService`, `UtilitiesService`, `WebhookRequest`, `TypeAliasDeclarationStructure`, `DetectedCompiler`, `TsChart`, `RBNFDecimalFormatter`, `TileObject`, `LogService`, `ChannelStoreEntry`, `Level2`, `CommitDetails`, `IDeferredPromise`, `PresentationPreview`, `ProjectFn2`, `TFS_Core_Contracts.TeamContext`, `TelemetryPluginStart`, `QueryHistoryNode`, `ColumnApi`, `AttestationModel`, `Unwatch`, `ObservableEither`, `EventData`, `ValueOf`, `BatteryCCReport`, `UrlPattern`, `KnownMediaType`, `FailedRequestType`, `ComboEventPayload`, `BuildHandlerArguments`, `Should`, `ThingType`, `CodeSnippet`, `ILeaguePrices`, `PlatformPath`, `IPipeline`, `messages.Step`, `RedisService`, `KonstColor`, `RouteQuoteTradeContext`, `SecretsManager`, `DragRefConfig`, `VideoFormat`, `IterableFactory`, `HandlerFn`, `ImageAndTrailImage`, `ProviderObservedParams`, `AnyWire`, `ExtractorMessage`, `ScaleOptions`, `FindRoute`, `MinecraftFolder`, `LchaColor`, `IViewPortItem`, `DeleteProfileCommandInput`, `MDCActivityIndicator`, `IFibraNgRedux`, `TransactionFactory`, `paper.PathItem`, `ShadowCastingLight`, `FieldValue`, `DotenvParseOutput`, `JSONRPCResponse`, `WheelDeltaMode`, `ex.PostDrawEvent`, `IInternalParticipant`, `CDP.Client`, `FlatTree`, `ConfigValueChangeAction`, `SAO`, `Card`, `DealService`, `$N.IBaseNode`, `CellEditor.CellConfig`, `Foam`, `ITrackDescription`, `types.AzExtLocation`, `CpuState`, `ConcreteLaunchOptions`, `Oid`, `MatchOptions`, `AttachedPipettesByMount`, `BabelDescriptor`, `DeleteResourcePolicyCommandOutput`, `ListComprehensionNode`, `ng.IRootScopeService`, `IMapSourceProvidersConfig`, `ResolveModuleIdResults`, `IBifrostAccount`, `StringToNumberSyntax`, `TextAlignment`, `Dialogic.IdentityOptions`, `PartialCliOptions`, `ModelNode`, `ArianeeTokenId`, `MapSimulation3D`, `ActionButton`, `ConfigActionTypes`, `SetStatus`, `UserExtendedInfo`, `TestPhysicalObject`, `TestAssertionStatus`, `RopInfo`, `MeshPhongMaterial`, `capnp.Pointer`, `HdErc20PaymentsConfig`, `SendCommandCommandInput`, `FeatureFilter`, `ITemplateId`, `FinalTask`, `ActionHandler`, `TestDataService`, `RestoreResults`, `EqualityDeciderInput`, `Phaser.GameObjects.GameObject`, `DocumentDataExt`, `NavProps`, `XPCOM.nsISupports`, `ITenant`, `CancelJobCommandInput`, `CreateDatabaseResponse`, `DnsResponse`, `RuntimeEngine`, `Overrides`, `TSelector`, `FabricEnvironment`, `StatefulSet`, `QueryKeySelector`, `Searcher`, `SimpleRenderer`, `TSpy`, `IAccessor`, `BarcodeFormat`, `GL`, `ReaderObservable`, `TestMarker`, `MonacoEditorModel`, `IFlexProps`, `IIdentity`, `ColorRGBA`, `ILayoutContextProps`, `CreateWorkflowCommandInput`, `ClassDeclaration`, `Asm`, `ListVaultReplicasRequest`, `KEXFailType`, `TrackedImportSymbol`, `MockValidatorsContract`, `TemplateEngine`, `RdsMetricChange`, `ChangeSetItem`, `PluginObj`, `Chai.AssertionStatic`, `ESCalendarInterval`, `ScreenType`, `ByteStr`, `Cue`, `StatsChunk`, `OptimizeCssOutput`, `CallbackMethod`, `CreateRegionPureReturnValue`, `requests.ListInstanceDevicesRequest`, `NeedleResponse`, `CreateVpcLinkCommandInput`, `TraceData`, `DatasourceSuggestion`, `IOptimized`, `DeepReadonlyObject`, `RequestInterface`, `SessionRefreshRequest_VarsEntry`, `ast.LookupNode`, `Konva.Stage`, `Liquidator`, `InMemoryPubSub`, `Compressors`, `PiLogger`, `TSClient`, `ContextualIdentity`, `ObjectCacheEntry`, `EventFieldInfo`, `ast.RunNode`, `QueryEngineRequestHeaders`, `NotificationHandler0`, `DateFormatOptions`, `StructureTower`, `EggAppInfo`, `CustomDocumentStoreEntry`, `MenuSurface`, `FileSystemEntry`, `ex.Engine`, `MDCNotchedOutlineAdapter`, `AbstractLogger`, `ThyDragDropEvent`, `MidiNote`, `ScenarioService`, `TaroText`, `IconsName`, `ListStacksRequest`, `PickerController`, `App.windows.IWindowModuleMap`, `CohortState`, `Cypress.PluginConfig`, `SubtitlesFileWithTrack`, `RoarrGlobalState`, `CalculatedBlock`, `TProvider`, `CreatePortalCommandInput`, `typeOfRow`, `PutEmailIdentityFeedbackAttributesCommandInput`, `ArtColumn`, `SubtitlesTrack`, `MdcChipAction`, `AsyncCPUBackend`, `ProviderMessage`, `Ver`, `deployData`, `IOneArgFunction`, `ApolloClient`, `LocalizedCountry`, `InternalTransition`, `FontProps`, `ILiteral`, `IVector2`, `DirectiveNode`, `SearchContext`, `d.LoggerTimeSpan`, `HsStylerService`, `OpPathTree`, `Phrase`, `RSPOutput`, `IValue`, `DeleteRouteCommandInput`, `EventName`, `vscode.DiagnosticCollection`, `ScreenshotCache`, `Expect`, `RequestPresigningArguments`, `MotionState`, `DetectEntitiesCommandInput`, `FirebaseAuth`, `MindNodeModel`, `SpaceStyleProps`, `DescribeTaskCommandInput`, `RegexDialect`, `PartialEntityCollection`, `ProviderWithScope`, `IHttpRequestOptions`, `CommonWrapper`, `MultipleDeclaration`, `EntityBuilder`, `ScanSegment`, `Skeleton`, `SignerPayloadJSON`, `BezierCurveBase`, `GenericDraweeHierarchyBuilder`, `ResourcePack`, `BridgeDeploy`, `Runner.Utils`, `CommandCreator`, `GetOperationRequest`, `CreateProcessOption`, `DashboardListingPage`, `AzureCustomVisionProvider`, `vscode.Range`, `DaffCartShippingRateFactory`, `Composite`, `AllowedModifyField`, `NestFastifyApplication`, `WFSerialization`, `EmbeddedOptions`, `TestReadable`, `Distortion`, `StatsGetterConfig`, `AppIdentity`, `ts.ArrayLiteralExpression`, `SkygearError`, `ActivityStreamsModel`, `PanGestureHandlerStateChangeEvent`, `RewriteRequestCase`, `ExpressRouteCrossConnection`, `EmbeddingLayerArgs`, `PrismaClientInitializationError`, `AppController`, `AccountType`, `PostCollector`, `SEOProps`, `MSIVmTokenCredentials`, `IItemRenderData`, `NexusInterfaceTypeDef`, `CmsEditorContentModel`, `Rx.Notification`, `DailyApiRequest`, `Palette`, `Texlist`, `EffectOptions`, `ILayout`, `PluginHooks`, `Raffle`, `CustomDomain`, `ViewerModel`, `ARAddOptions`, `ReplayEntity`, `DashboardType`, `ng.IHttpPromiseCallbackArg`, `B1`, `LabelAccessor`, `HitTestResult`, `GetApplicationResponse`, `HoldingUpdatedArg`, `OtCommand`, `ErrorLocation`, `ast.NodeList`, `ScalarActivity`, `HandlerStateChangeEvent`, `IndexedGeometry`, `SequenceKey`, `ConditionOperatorName`, `PBXFile`, `DefaultRootState`, `ProxyObject`, `NamespaceExportDeclaration`, `CBlock`, `d.RenderNode`, `TabNavigationState`, `TemplateConfig`, `GaxiosPromise`, `AxeResultConverterOptions`, `CollateContext`, `UserScriptGenerator`, `Listing_2`, `OutputConfig`, `ChatBoxStateModel`, `JobType`, `OrderStatus`, `GenericAPIResponse`, `HotkeysService`, `Dexie`, `FieldPlugin`, `http.ServerRequest`, `ExtensionService`, `HSD_TObj_Instance`, `DestinationSearchResult`, `InsightsResult`, `RequestService`, `HistoryService`, `HttpRequester`, `DescribeConnectorProfilesCommandInput`, `Session.ISession`, `TallyType`, `G2TimelineData`, `BackgroundTrack`, `Neuron`, `AsyncCommandResult`, `InputCurrencyOutput`, `ApolloPersistOptions`, `HTMLDocument`, `CreateLoadBalancerCommandInput`, `IntervalContext`, `PublishArgs`, `AxisAlignedBox3d`, `ChatThreadClient`, `XMLElementUtil`, `UpdateTemplateCommandInput`, `IJobPreset`, `JSONSchema4`, `DirectoryNode`, `LobbyHouse`, `TrackedStorage`, `PeriodModel`, `PieLayerState`, `superagent.Response`, `Force`, `RgbVisConfig`, `MapSet`, `SearchParams`, `T0`, `StreamWithSend`, `SettingValue`, `ListRenderItemInfo`, `PlansCategories`, `GrammarToken`, `FetchService`, `DeviceState`, `ReactQueryConfig`, `ProxyRequest`, `DeleteTokenCommandInput`, `MatFormField`, `PathProps`, `CombatEncounter`, `ParseTreeResult`, `WebSqlTx`, `SubmissionDetailEntity`, `PopoverOptions`, `BorderRadius`, `DockerApi`, `ComponentDoc`, `UntagResourceCommand`, `TreeNodeItem`, `ConcurrentWorkerSet`, `ICreateResult`, `BinOp`, `CPS`, `XmlMapsXmlNameCommandInput`, `VRMHumanoid`, `VNode`, `ResolvedFunctionType`, `FastFormFieldComponent`, `XSDXMLNode`, `DeclarationReference`, `HttpResponse`, `OutputFlags`, `FunctionServices`, `EventsFnOptions`, `apid.GetRuleOption`, `BuildLevel`, `ContextState`, `IOpenAPI`, `cytoscape.SingularElementArgument`, `ProductProps`, `Import.Options`, `GanttViewOptions`, `ExampleFlatNode`, `GitHubActions`, `ReleaseTag`, `GuildConfig`, `AnkiConnectRequest`, `Vocabulary`, `B15`, `CommandParams`, `ListApplicationsCommand`, `LocalWallet`, `InterfaceWithDictionary`, `DegreeType`, `StoreSetter`, `GestureResponderEvent`, `EbsBlockDevice`, `ScoreStrategy`, `OptionEquipped`, `WaveShaperNode`, `XRWebGLLayer`, `ImportDeclaration`, `ShellExecResult`, `PermissionLevel`, `CaseOrDefaultClause`, `AsBodiless`, `Webhook`, `StateDictionary`, `SequenceComponent`, `MyModule`, `SettingsFile`, `AdminState`, `VNodeArrayChildren`, `MultiSigHashMode`, `IFilter`, `MessageModel`, `OpenAPI.Schema`, `ClassList`, `NamespaceOperatorDecl`, `WechatQRCodeEntity`, `SVBool`, `WebsocketInsider`, `LiveEventMessage`, `ProseNodeType`, `BoundEventAst`, `SendPropDefinition`, `NodeConfig`, `UseMap`, `CustomVariant`, `Discord.Guild`, `LogAnalyticsSourceMetric`, `LocationAccessor`, `TypeScriptSubstitutionFlags`, `HalLink`, `DeviceSummary`, `FunctionToActionsMap`, `ListTemplatesCommandInput`, `PiElementReference`, `IRequestResponse`, `TransitionFn`, `WebpackPluginInstance`, `CacheContainer`, `AggregatedApiCall`, `WebsocketClient`, `SwimlaneActionConnector`, `ParamMetadata`, `CylinderGeometry`, `ScanResultResponse`, `ReviewerReadModel`, `ResetAction`, `CourseService`, `providers.Log`, `RGroup`, `WaitForYellowSourceState`, `MutationHookOptions`, `FilterOf`, `evaluate.Options`, `TagEventType`, `AmdModule`, `LightArea`, `StartExperimentCommandInput`, `MouseButton`, `SubscriptionHolder`, `Tensor3D`, `OpenApiParameter`, `EmotionCache`, `MapSubLayerProps`, `IVimStyle`, `utils.RepositoryManager`, `EdiDocumentConfiguration`, `StripeElements`, `interfaces.Lookup`, `SignedDebtOrder`, `TrialType`, `AccountState`, `ValidatorFunction`, `FunctionData`, `MagickFile`, `SGraph`, `IDateColumn`, `StatusEntry`, `Passenger`, `AudioItem`, `tBootstrapFn`, `LiteralObject`, `code.TextDocument`, `DialogForm`, `InitiateOptions`, `WetLanguage`, `BaseWeb3Client`, `QuerySnapshot`, `SchemaModel`, `Continuation`, `DeploymentExecutor`, `UiRequest`, `d.OptimizeCssOutput`, `ExpressionRendererRegistry`, `NodeCryptoCreateDecipher`, `PivotGroupByConfig`, `OptionsProps`, `GradientStop`, `PortalOutlet`, `Path7`, `XHRoptions`, `TYPE`, `KnownTokenMap`, `SpinnerService`, `CalendarViewEventTemporaryEvent`, `Puzzle`, `SecureStore`, `ImportedNamespace`, `LongNum`, `Score`, `IExecutionContext`, `ButtonState`, `Service`, `BrowserEvent`, `IMappingFieldInfo`, `HelpCenterAuthorService`, `RecordList`, `Konva.Shape`, `WsPresentationService`, `RegexComponent`, `PdfObjectConverter`, `Prompter`, `NavigationBarItem`, `PromptItemViewModel`, `Loc`, `ExpressionsSetup`, `CreateDataSourceCommandInput`, `ListNodePoolsRequest`, `PolicyRates`, `LunarYear`, `FieldDeclaration`, `VideoFile`, `IModulePatcher`, `MockERC20TokenContract`, `LogFn`, `SwitchCallback`, `JsonRpcHandlerFunc`, `TexCoord`, `TemplatingEngine`, `BadgeProps`, `ISiteDesign`, `GeoProjection`, `ThyPopoverRef`, `TrustToken`, `TokensPrices`, `JSX.Element`, `ParameterComputeType`, `StateChannel`, `SpecFun`, `ParseSourceSpan`, `Runner`, `ExpandedAnimator`, `GetChannelMessageCommandInput`, `SharedContents`, `PlanetaryTrack`, `GetBucketLifecycleConfigurationCommandInput`, `FindProjectsDto`, `IntLiteralNode`, `VectorKeyframeTrack`, `KeyProvider`, `IPathMapping`, `ContainersModel`, `OverridableComponent`, `CompoundMeasurement`, `IInternalEvent`, `ScoreHeader`, `GameConfig`, `shell.Shell`, `BabelPlainChain`, `TimestampShape`, `ITenantManager`, `INativeTagDict`, `Deno.ListenOptions`, `Proxy`, `PropConfigCollection`, `d.FsReaddirItem`, `WebView`, `CasePostRequest`, `TestFunctionImportSharedEntityReturnTypeParameters`, `ChatResponse`, `HeaderViewProps`, `AllocationItem`, `ProtocolConformance`, `Int16`, `InspectFormat`, `Viewpoint`, `VoteChoices`, `ITypedResponse`, `thrift.IStructCodec`, `BasePoint`, `ReleaseGoldConfig`, `OnGestureEvent`, `Is`, `ExternalWriter`, `ChainNodeFactory`, `SwappedToken`, `OpenApiDocument`, `NotAuthorizedException`, `THREE.BufferGeometry`, `PubsubMessage`, `Calendar_Contracts.IEventQuery`, `ABLParameter`, `NotifyQueueState`, `TypeAllocator`, `CLIArgumentType`, `CausalRepoBranchSettings`, `ThemableDecorationRenderOptions`, `IUnitModel`, `EvaluatedExprNode`, `ISessionBoundContext`, `IGraph`, `ImmutableObjective`, `ListProjectsRequest`, `FieldModel`, `PutEmailIdentityMailFromAttributesCommandInput`, `Point3F`, `T6`, `GfxVertexBufferDescriptor`, `ZWaveFeature`, `ITrackStateTree`, `ToolbarIconButtonProps`, `EdiSegment`, `TranslationAction`, `ParameterInvalidReason`, `SnapshotOptions`, `BalmEntry`, `FloatOptions`, `IAttachment`, `ExtensionPackage`, `AgreementData`, `DocumentModel`, `WearOsListView`, `VisibilityState`, `MigrateAction`, `MockRepository`, `ContractDBTransaction`, `ListNode`, `GlobalSettings`, `ToolbarTest`, `IMdcSegmentedButtonSegmentElement`, `TickAutomationEvent`, `HostLabelInput`, `DaemonConfig`, `TaskUser`, `ExcaliburGraphicsContextOptions`, `TypedKeyInfo`, `EmailTemplateService`, `NumberType`, `HTMLIFrameElement`, `DaffProduct`, `RouterStateSnapshot`, `Pluggable`, `ListOperationsCommandInput`, `AvailabilityStatus`, `MiddlewareMetadata`, `IRequestContext`, `ReindexService`, `AppEvent`, `ReadLine`, `TextureInputGX`, `SharedElementNode`, `X12Segment`, `WithdrawalMonitorObject`, `TransactionResponse`, `IPrimaryKey`, `ISparqlBindingResult`, `EventbusService`, `HTMLCmpLabelElement`, `schema.Document`, `PrivateThreadAndExtras`, `SubCommand`, `TNSCanvasRenderingContext`, `TransactionUnsigned`, `RealtimeEditMode`, `ImportParts`, `MeetingAdapterStateChangedHandler`, `ProxyServer`, `sast.Node`, `UrlService`, `Gradient`, `CacheData`, `xml.Position`, `ExecEnv`, `AnomalyRecordDoc`, `AggTypesDependencies`, `MirrorDocumentSnapshot`, `StateSnapshot`, `TopLevelDeclarationStatement`, `IRequestOption`, `AaiChannelItem`, `PartiallyEmittedExpression`, `FSService`, `PromiEvent`, `FontFace`, `FieldDefn`, `Graphics.Texture`, `SourceRule`, `TypescriptAst`, `CurrencyValue`, `IDraggableData`, `DDiscord`, `IFunctionCallArgument`, `ec`, `ListChannelMessagesRequest`, `FileSystemReader`, `ColumnInfo`, `long`, `PopulatedTagDoc`, `Entity.Account`, `PartialErrorContinuation`, `BasicCCReport`, `OverflowModel`, `ListManagementAgentInstallKeysRequest`, `AmmContractWrapper`, `SelectMenuInteraction`, `Ycm`, `ProfileService`, `GetCoordinate`, `DoubleMapCallback`, `JsonaValue`, `ConditionalBooleanValue`, `PropertyOptions`, `EventProvider`, `SxToken`, `TranslateContainerConfig`, `LogConfiguration`, `ValueMetadataNumeric`, `DescribeEndpointsResponse`, `ts.ForOfStatement`, `ObjectStorageSourceDetails`, `UAParserInstance`, `TemplateAnalyzer`, `CreateClusterCommandOutput`, `NgForageConfig`, `ServiceRecognizerBase`, `StagePanelManager`, `OptionNode`, `BScrollOptions`, `QuerySettings`, `IExpressionLoaderParams`, `InternalComputedContext`, `RegistrationDTO`, `EventmitHandler`, `DB`, `Precondition`, `AppPage`, `CCValueOptions`, `WriteFileOptions`, `Rand`, `IAvatarBuilder`, `ProtocolConformanceMap`, `DocsService`, `CaseExpr`, `Indent`, `ResolvedFile`, `CallSignatureInfo`, `AppEvent.Stream`, `FrameworkOptions`, `EmitFileNames`, `SavedObjectsClientWrapperFactory`, `LabelNode`, `DataLakePrincipal`, `WorkerServiceProtocol.RequestMessage`, `FnN`, `WrappedAnalyticsEvent`, `ContentShareObserver`, `MixedIdType`, `NodeToVisit`, `CustomerDTO`, `ControlProps`, `SyncResult`, `DeleteTagsCommand`, `ExecutorOptions`, `TSParseResult`, `ResourceInUseException`, `PartialBotsState`, `RootComponentRegistry`, `Canvg`, `EditorRange`, `LowAndHighXY`, `Greeter`, `RedHeaderField`, `FormField`, `ICalAttendee`, `CdkTreeNodeDef`, `ClassVarInfo`, `ProofBranch`, `ProjectionOptions`, `TearrData`, `TTurnAction`, `Postprocessor`, `CSSSource`, `ProgressData`, `DataWithPosition`, `MetaSchema`, `monaco.editor.IEditorMouseEvent`, `JSX.TargetedEvent`, `PragmaValueContext`, `SimpleNotification`, `UserContextType`, `Rect2D`, `ICourseModel`, `FormContext`, `PositionPlacement`, `OmvFeatureModifier`, `MatchRule`, `DefaultEditorAggParamProps`, `TileBoundingBox`, `MemberAccessNode`, `IDType`, `NavigationPublicPluginSetup`, `AuthStrategy`, `GenericAnalyzer.Dictionary`, `CheckIdTaskDto`, `WhitePage`, `FirenvimElement`, `MutationEvent`, `JsonValue`, `ConfigurableConstraint`, `NumericalRange0`, `EquipmentDelay`, `HashedItemStore`, `d.BuildConditionals`, `DidChangeConfigurationParams`, `ListApplicationVersionsCommandInput`, `MarkdownTheme`, `ServerCapabilities`, `SimpleMap`, `FileOpenFlags`, `ApplicationInfo`, `Highcharts.AnnotationPointType`, `PaymentResource`, `ProcessHandler`, `UpdateImportInfo`, `BlinkerDevice`, `X12Parser`, `BannerState`, `CreateViewNode`, `IClassParts`, `NormalizedComponentOptions`, `Timeout`, `CalibrationState`, `ExistsExpression`, `ThyNavLinkDirective`, `ListSchemasResponse`, `DOMStringList`, `GithubRelease`, `AugmentedProvider`, `D2rStash`, `CellStyle`, `ResourceManagementClient`, `ExtractGetters`, `CompletionResults`, `TabName`, `ShallowMerge`, `CreateTargetResponderRecipeDetails`, `FeltReport`, `ClientReadableStream`, `NormalizedFilter`, `ServerDto`, `AddApplicationCloudWatchLoggingOptionCommandInput`, `def.View`, `ControlComponentProps`, `TypedFormGroup`, `BitbucketUserEntity`, `requests.ListAlertRulesRequest`, `ILinkedListNode`, `ClassEntry`, `CardInterface`, `LooseObject`, `IdentityMetadataWrapper`, `GfxQueryPoolType`, `IMyFavouriteItem`, `GfxSwapChain`, `ControllerInterface`, `IXElementResult`, `PermutationListEntryWithTrackingData`, `AST.MustacheStatement`, `BucketAggTypeConfig`, `PathSegment`, `ExchangePositionInput`, `TimeoutTask`, `DropedProps`, `LayerInfo`, `ProtocolRequestType0`, `DynamicEntityService`, `App`, `DAVCalendar`, `ObservableSet`, `CompletionParams`, `TLabelName`, `CreateSchemaCommandInput`, `MatchmakerAdd`, `PiBinaryExpression`, `PassphraseError`, `PriceLineOptions`, `MetadataField`, `IOrganization`, `ts.LiteralType`, `CompactOrCondition`, `HubLinksWebPart`, `Q.Promise`, `ChannelAnnouncementMessage`, `ResultValue`, `PolynomialID`, `PluginsContainer`, `LoggingEvent`, `ScriptKind`, `FetcherOptions`, `Submesh`, `UnitConversionSpec`, `OnChangeType`, `TypedQuery`, `ThresholdedReLULayerArgs`, `RequestMessage`, `ActivityPropertyDescriptor`, `CfnRole`, `UserFunctionSignature`, `A3`, `TActorParent`, `PickScaleConfigWithoutType`, `Writer`, `TreeSitterDocument`, `ColorKey`, `Tutorial`, `MeetingSessionStatusCode`, `BrowseEntrySearchOptions`, `NodeCanvasRenderingContext2D`, `Toolkit`, `Multiaddr`, `IndicatorQueryResp`, `AdapterPool`, `SpawnResult`, `CachedValue`, `IPerfMinMax`, `ExecuteCommandParams`, `MintInfo`, `Aai20SchemaDefinition`, `emailAuthentication.Table`, `VocabularyEntryDetail`, `ListSuppressionsRequest`, `SanitizedAlert`, `ScopedObjectContext`, `SessionStore`, `DeleteVpcLinkCommandInput`, `DesktopCommand`, `Popup`, `LocalizedText`, `Paper`, `EndpointInput`, `VirtualCloudNetwork`, `DatabaseCredentials`, `VirtualContestInfo`, `PropertyDescriptor`, `ICodeEditor`, `ShapeAttrs`, `requests.ListPreauthenticatedRequestsRequest`, `InstallState`, `WorkspaceData`, `ConfigParameterFilter`, `messages.Tag`, `angular.IDeferred`, `TableFactory`, `SceneRenderer`, `IDiscordPuppet`, `LocalizeRouterSettings`, `StripeEntry`, `LedgerDigestUploadsName`, `MutableChange`, `MyView`, `SectionType`, `BreakpointKeys`, `CompileKey`, `JSONInput`, `ChromeNavControl`, `ITKeyApi`, `DrawCall`, `VaultData`, `BinarySwitchCCReport`, `UserRole`, `TestCLI`, `JsonRpc`, `NotificationLevel`, `ModeAwareCache`, `WorkspaceChange`, `React.HTMLAttributes`, `BlankLineConfig`, `GQtyConfig`, `PaginationModel`, `vscode.SymbolInformation`, `TodoComment`, `SVNumeric`, `MIRType`, `DurableOrchestrationClient`, `DeleteDedicatedIpPoolCommandInput`, `InstanceState`, `GraphicsComponent`, `CeloContract`, `SetLanguage`, `FieldFormatMap`, `ElementNode`, `Apple2IO`, `IGLTFLoaderData`, `ListUI`, `IpcMain`, `WalletEventType`, `SimpleExprContext`, `CreateProfileCommandInput`, `CreateAccessPointCommandInput`, `AzurePipelinesYaml`, `HistoryManager`, `ExtenderHandler`, `GetPackageVersionHistoryCommandInput`, `PathToProp`, `HandleEvent`, `MdcSnackbarConfig`, `NewPerspective`, `MenuNode`, `Vec2Like`, `SimpleAllocation`, `DaprManager`, `BarChartDataPoint`, `QueryExecutorFn`, `StateFromFunctionReturningPromise`, `ExpandedNodeId`, `ContextMenuFormProps`, `IGlobalEvent`, `tsc.Type`, `IgApiClient`, `PngEmbedder`, `MultiChannelAssociationCCAPI`, `ZeroXOrder`, `Todo_todo`, `CallbackContext`, `Columns`, `Newable`, `Fruit`, `GltfLoadOption`, `ExecException`, `SpatialDropout1D`, `ExcalideckEditorState`, `NormalizedIdentifierDescriptor`, `UseFetchReturn`, `ISubscribable`, `ConfiguredProject`, `SelectedItem`, `ReverseQueryInterface`, `IProcesses`, `Obstacle`, `SourceAwareResolverContext`, `ThisAddon`, `auth.AuthenticationDetailsProvider`, `TSLintAutofixEdit`, `PanelSocket`, `DiagnosticsLogger`, `IPriceAxisView`, `AggsSetup`, `SetterOrUpdater`, `IntPairMap`, `tf.Tensor2D`, `StandartParams`, `Int64`, `IItemAddResult`, `webpack.Stats`, `State.Transaction`, `def.Vec4`, `PutConfigurationSetSendingOptionsCommandInput`, `EmitterConfig`, `Events.postupdate`, `DefsElementMap`, `Shall`, `ConnectionTransport`, `OperatorFunction`, `ModalHelper`, `FocusZone`, `BuilderProgram`, `RenderingContext`, `DraggedItem`, `Notifire`, `YoutubeRawData`, `EntitySprite`, `TestModel`, `ScriptParametersResolver`, `XUL.chromeWindow`, `UpdateManyParams`, `RuleDefinition`, `P2PNodeInfo`, `CreateDomainCommandInput`, `KeyPairTronPayments`, `IDataType`, `StructuredAssignementPrimitive`, `OptionGroups`, `IDocumentOptions`, `FetchError`, `NodeListOf`, `PaletteConfig`, `UgoiraInfo`, `StoreKey`, `MessageSender`, `HttpResponseMessage`, `TextInputProps`, `OcpuUtilizationInfo`, `Collision`, `StoreDefinition`, `TestElement`, `AlterTableExecutor`, `FolderOrNote`, `IOAuth2Options`, `IFontFaceOptions`, `Current`, `IFormPageState`, `BitwiseExpressionViewModel`, `CustomPaletteState`, `WordcloudPoint`, `ColorSet`, `FileRef`, `DeleteClusterCommandOutput`, `RBNFCollector`, `LabeledStatement`, `DeepMapAsyncResult`, `HeaderInfo`, `FeaturesService`, `NodeDefaultCryptographicMaterialsManager`, `GraphDataset`, `IMethod`, `WorkflowClient`, `JsxSelfClosingElement`, `NetworkRecorder`, `Valve`, `SampleCartProduct`, `BinaryReader`, `ActionTree`, `ConverterLogger`, `ListManagementAgentImagesRequest`, `TextEditorPropertiesMain`, `WaitOptions`, `CentralSceneCCConfigurationSet`, `d.OutputTargetDistLazy`, `InvalidFieldError`, `AnimationClip`, `HTTPServer`, `PrRepoIndexStatistics`, `OrgID`, `interfaces.Container`, `IResult`, `ITrackSequence`, `FormatValue`, `EventChannel`, `MessageSeverity`, `VarInfo`, `CryptoFishContract`, `SqrlFeatureSlot`, `GetEnvironentsForProjectEnvironmentResult`, `LayoutResult`, `DueState`, `DryContext`, `ErrorCacheDelta`, `DeploymentStatus`, `ServiceId`, `RTCDtlsTransport`, `Conferences`, `GeometryCommand`, `EncryptedPassphraseObject`, `EventCategoriesMap`, `GraphType`, `WriteTransaction`, `VisTypeIconProps`, `Xml`, `MutationObserverWatcher`, `GenderRepartitionType`, `LFO`, `ClusterVulnerabilityReport`, `SettingsComponent`, `CopyDBClusterSnapshotCommandInput`, `MenuInfo`, `SavedObjectsRawDoc`, `StreamModelWithChannel`, `NodeStore`, `AlterTableNode`, `ISelector`, `A5`, `ISqlEditorResultTab`, `ResponseInterceptor`, `drive_v3.Drive`, `CertificateOptions`, `IActionItemUUID`, `VieraTV`, `RunConfiguration`, `DsDynamicInputModel`, `ISiteDefinitionDocument`, `PutResourcePolicyResponse`, `RobotsTxtOpts`, `FilePreviewDialogConfig`, `IApplicationContext`, `IDateFilter`, `CacheConfig`, `DiscoverIndexPatternProps`, `ListPoliciesResponse`, `CreateEncryptedSavedObjectsMigrationFn`, `IPackageVersionInfo`, `DisplayObjectTransformationProcess`, `NodeController`, `ProductDetailPage`, `Promised`, `SignedMessageWithTwoPassphrases`, `BidirectionalMergeMode`, `JsonLayout`, `AnyJson`, `DescribeEventsResponse`, `TextDocumentItem`, `ClientMenuOrderIdDTO`, `PageListItemProps`, `React.SVGProps`, `RegionGetter`, `IPickState`, `NodeEventHandler`, `CompilerFileWatcherCallback`, `OnFetchEventFn`, `BuildComparator`, `PrismaClientUnknownRequestError`, `ResultView`, `PropertyDocumentationBlock`, `ParamsOf`, `CTX`, `PopoutComponentEvent`, `ITaskRunnerDelegates`, `FleetConfigType`, `GestureConfigReference`, `SpatialControls`, `Loaded`, `Profiles`, `PostCondition`, `CascadeTestResult`, `TransceiverController`, `JsonRpcRequest`, `fc.Arbitrary`, `AffineTransform`, `BaseIO`, `p5.Graphics`, `Hunk`, `SwankRawEvent`, `TransactionAuthField`, `CoreRouteHandlerContext`, `ResizeObserverMock`, `SwitchEventListener`, `AxisComposition`, `SeekQueryResult`, `IStreamPolygon`, `GeometryHandler`, `OptimizerVariable`, `ShaderSemanticsEnum`, `TsunamiContext`, `AccountSteam_VarsEntry`, `PluginActionContext`, `DetectorEnum`, `MetadataRegistryState`, `DataFetcher`, `IUserGroupOptions`, `UndelegateBuilder`, `SubscriberAndCallbacksFor`, `Bettor`, `RadarColumnSeries`, `sinon.SinonStub`, `ListAssociationsCommandInput`, `React.SVGAttributes`, `FargateService`, `Validity`, `InternalStyle`, `Interfaces.RequestConfig`, `AppStateTypes`, `StartDeps`, `RouteWithValidQuote`, `MonitorSummary`, `CausalRepoClient`, `QueryServiceSetupDependencies`, `IdSet`, `ComboType`, `CasparCGSocketResponse`, `ListrObject`, `ProductRepository`, `ListProps`, `Traversable1`, `Hashable`, `VueWrapper`, `ICompiler`, `TimeOpNode`, `PerfEntry`, `SearchRecord`, `VerifyStream`, `SegmentId`, `AppWindow`, `IBranchListItem`, `Mocha.Done`, `SqlEntityManager`, `ReportIndicator`, `ProviderUserBulkRequest`, `Calculator.Client`, `CreateExperimentCommandInput`, `FluidBox`, `RenderContextBase`, `Video`, `TilemapSeries`, `SubMiddlewareBuilder`, `General`, `SpawnSyncOptions`, `TemplateExpression`, `OpenApi`, `SecurityRequirement`, `LabIcon`, `FlowParameter`, `Tx.Options`, `ReactiveControllerHost`, `StoreLike`, `ANodeExprLValueVar`, `GfxIndexBufferDescriptor`, `ConfigChoice`, `RawSeries`, `Core.Rect`, `HandlerType`, `AggregateValueProp`, `ElementsDefinition`, `IRequire`, `Progresses2Runners`, `NumberFormatOptions`, `IChunkHeader`, `Faction`, `Targets`, `ESTree.ImportDeclaration`, `ContentProps`, `IToolbarItemProps`, `CapacityProviderStrategyItem`, `YTMember`, `AttrValuesStore`, `StyleNode`, `RouteExecutionFromOutput`, `TournamentRecordList`, `Model.Book`, `PvsFile`, `ServiceJSON`, `ImageUrlOptions`, `VerifyCallback`, `PIXI.InteractionEvent`, `ThyAnchorLinkComponent`, `ListStreamsCommandInput`, `EntityStateResponse`, `PaymentData`, `IMap`, `FrescoError`, `CommandFlags`, `BackendSrv`, `MessageEmbed`, `PacketNumber`, `AtomOrString`, `MergeDeclarationMarker`, `IDatArchive`, `IErrData`, `QueryLeaseResponse`, `testing.ApplicationEnv`, `IPaneRenderer`, `ClientFileSearchItem`, `DebouncedFunction`, `Browser.WebIdl`, `Ajv`, `IICUMessage`, `AsyncLogger`, `PopupAlignment`, `Parsers`, `ReturnNode`, `DisplayContext`, `FunctionsMetadata`, `requests.ListRunLogsRequest`, `CameraOptions`, `FeedService`, `PointInTimeFinder`, `Tip`, `DiscoverLegacyProps`, `MockTokenTransferProxyContract`, `ContainerContent`, `FeatureFlags`, `IThread`, `TypeC`, `UninstallEventData`, `SessionDescription`, `PipelineTarget`, `CategoryStub`, `Yendor.BehaviorTree`, `Orientation`, `TokenlonInterface.TxOpts`, `ComponentRendering`, `FocusRingOptions`, `OpConfig`, `IScene`, `WorkingDayOfYearByMonth`, `IConfig`, `SVGO`, `SavedObjectsFindResponse`, `BedrockFile`, `VariableColor`, `DataModel.ColumnRegion`, `DrawParams`, `vscode.Webview`, `CtrExpBool`, `PubSubListener`, `ValidatePurchaseHuaweiRequest`, `KeysSource`, `SceneGroup`, `PureSelectors`, `SendOverrides`, `CompilerFsStats`, `DMMF.SchemaArgInputType`, `ConfigFactory`, `ts.Modifier`, `VisualizationsAppExtension`, `TabComponent`, `Markdown`, `MappedType`, `RequiresRuntimeResult`, `AStarNode`, `GroupedObservable`, `VertexAttributeGenDef`, `Float32BufferAttribute`, `MemberFieldDecl`, `ISettingsContext`, `TextRow`, `TransactionLog`, `ClassTransformOptions`, `HTMLTableColElement`, `JsxText`, `ObjExplorerObjDescriptor`, `ITriggerContructorParams`, `BreakNode`, `jdspec.SMap`, `HeftEvent`, `d.RuntimeRef`, `FailedImport`, `ExecContext`, `PayoutMod`, `AksClusterConfig`, `Matrix4`, `Period`, `RequestParameters`, `Positioned`, `NVMEntryName`, `SvgViewerConfig`, `IABIMethod`, `ISection`, `ParsedDocument`, `HiddenProps`, `CmsEntry`, `TestImage`, `BarTuple`, `GitlabAuthTokenRepository`, `DTO`, `CustomTransformers`, `GameResult`, `ScriptTarget`, `SchemaValidationResult`, `IColumnConfig`, `MockAlexa`, `BridgeableChannel`, `Program`, `IConnectionPageProps`, `IDataFilterResultValue`, `MutationTuple`, `PDFAcroListBox`, `string`, `JQLite`, `TraceContext`, `TimeOptions`, `ClusterConfig`, `AuthenticationInstruction`, `FIRDocumentSnapshot`, `PFS_Config`, `HomeView`, `BuildConfiguration`, `ClassEntity`, `BlockHeader`, `StoreType`, `Recipe`, `InsertContext`, `PQP.Language.Type.TPrimitiveType`, `ScheduledOperationDetails`, `IntegerRangeQuantifier`, `SWRConfiguration`, `SectionOptions`, `StateDeclaration`, `DbSeed`, `MatOptionSelectionChange`, `MiddlewareFn`, `IBaseAddressAsyncThunk`, `PyteaWorkspaceInstance`, `CliGlobalInfo`, `DocumentationResult`, `BaseBigNumber`, `SheetsArray`, `DatabaseIndexingService`, `ServiceInterface`, `DistrictsDefinition`, `ICollectionTrigger`, `TypedRequest`, `IJobFile`, `InjectedMetamaskExtension`, `IVisualizerStyle`, `MappedStates`, `MentionInfo`, `GCFBootstrapper`, `MockContainerRuntimeFactoryForReconnection`, `TreeRepository`, `CryptoKey`, `Hardfork`, `browser`, `IInviteGroupUsersOptions`, `Node.JSON`, `GetStagesCommandInput`, `SfdxFalconRecipeJson`, `BookmarkIdMapping`, `TheBigFanStack`, `PlanarMaskBaseTool`, `CfnApi`, `ICourse`, `MaybeVal`, `CubemapSky`, `IEnemy`, `FileError`, `SetNode`, `ForgeModMcmodInfo`, `ReadableStream`, `Validators`, `MultiKey`, `IReducerContext`, `ScrollbarOptions`, `DatabaseObject`, `ConsoleMessageType`, `CreatePageReq`, `Contacts`, `TransformableInfo`, `ModelInstance`, `ResponseToActionMapper`, `TextPossibilities`, `AnalyzerFileInfo`, `DateTimePatternFieldType`, `Functor`, `SEMVER`, `RefLecture`, `TypedEmitter`, `SnapshotMetadata`, `InputSpec`, `FileSystemManager`, `HandleType`, `VersionResult`, `DOMNode`, `DecodeResult`, `Viewer.SceneGroup`, `MiddlewareCallback`, `IndexData`, `DaffPaypalTokenResponse`, `FlamegraphNode`, `VoidType`, `ParamSpecValue`, `CompiledComponent`, `TileAniSprite`, `AstEntity`, `SetToken`, `OutlineDoOauthStep`, `TsCohortDateRangeComponent`, `MessageBoxReturnValue`, `ObjectExplorerService`, `BlockFragment`, `DecoratorConfiguration`, `React.ForwardRefRenderFunction`, `ForwardRefComponent`, `ElementPosition`, `QueryArray`, `UVTX`, `InternalQueryHandler`, `BuddyWorks`, `APIProvider`, `PieSeries`, `CommandsCache`, `JGadget`, `StartCallOptions`, `InvalidVPCNetworkStateFault`, `BufferGeometry`, `StringifyContext`, `HDOMImplementation`, `RenderTargetTexture`, `HKT`, `RuleCondition`, `NavigationOptions`, `IViewEntity`, `MergedProblem`, `CacheBehavior`, `FBXReaderNode`, `WriteTransactionReply`, `CRDPChannel`, `IAggType`, `EnhancedStore`, `SizeT`, `SchemaRegistry`, `ModelMetadata`, `CSI`, `HashPair`, `ImageView`, `ParsedMail`, `ApplicationSettings`, `FormSubmissionState`, `InsertionEdit`, `LoggerAdapter`, `SpaceId`, `LitecoinBalanceMonitorConfig`, `Coords`, `RoleListContext`, `ChainParam`, `td.Action1`, `PhaseEvent`, `Sourcelike`, `interfaces.IExtensionConfiguration`, `KSolvePuzzleState`, `AppxEngineStep`, `ISwidget`, `RTCRtpHeaderExtensionParameters`, `DescribeScheduledActionsCommandInput`, `IPizzasTable`, `protos.common.MSPPrincipal`, `Skill`, `SortingType`, `browser.management.ExtensionInfo`, `PanGestureHandlerGestureEvent`, `BufferType`, `LSTM`, `ExpressionRenderer`, `DescribeDomainAutoTunesCommandInput`, `CharsetNameContext`, `ISnippet`, `ExpressRequest`, `TypeArray`, `DeleteQueryBuilder`, `UIView`, `SessionInfo`, `ModuleLoader`, `AnimationControls`, `DataUnitUp`, `DocNode`, `FieldInfo`, `SocketClient`, `requests.ListAutoScalingPoliciesRequest`, `TObjectProto`, `RemixConfig`, `CanAssignFlags`, `MDCTextFieldFoundation`, `DebugProtocol.DisconnectArguments`, `PropDecorator`, `IntegerParameterRange`, `DeleteAppInstanceUserCommandInput`, `RedirectOptions`, `DeviceManager`, `TComponent`, `ToolsWorkspaceCommandResponse`, `VanessaDiffEditor`, `Datapoint`, `HistoryLocation`, `GanttItemInternal`, `DescribeConfigurationCommandInput`, `ApplicationType`, `INanoDate`, `CredentialsOptions`, `IListenerOptions`, `VizChartPanel`, `ChlorinatorState`, `CdsNavigationStart`, `PageFlip`, `BMMessage`, `VariantForm`, `NavbarElementProps`, `Method`, `MapInfo`, `TVEpisodeDAO`, `FormatContext`, `CancelFnType`, `PackageType`, `SetupPlugins`, `HierarchyIterable`, `IHawkularAlertQueryResult`, `IRepository`, `APIGatewayProxyEventV2`, `INavLink`, `ThyDialogConfig`, `NormalizedProvider`, `AmmFakeInstance`, `DisassociateMembersCommandInput`, `AuthStateType`, `IActor`, `OidcClientSession`, `StringDecoder`, `EngineOpt`, `IndexSignatureDeclaration`, `ZeroPadding2D`, `IRunData`, `ConnectionRecord`, `ClassWithMethod`, `FrameNodePort`, `PatternUnknownProperty`, `requests.ListWindowsUpdatesRequest`, `TBuffer`, `TexMtxMapMode`, `Intersection`, `DataGrid.Style`, `PlaneData`, `DeploymentExtended`, `B6`, `DomainType`, `BaseProperty`, `ComponentFactoryResolver`, `AuthorizationMetadata`, `Timeline.State`, `DAVResponse`, `SimulcastLayers`, `OneToOneOptions`, `PerformanceResourceTiming`, `VariantAnnotation`, `IIOPubMessage`, `Hertz`, `GitBlameLines`, `Kleisli`, `SignupResponse.AsObject`, `PropertySchema`, `DecodedDeviceType`, `ThyCollapsePanelComponent`, `ListJobRunsRequest`, `GetKeyboardResponseOptions`, `IEmailProvider`, `IntervalTree`, `INumberFieldExpression`, `firebase.firestore.WhereFilterOp`, `Formatters`, `IConnection`, `XrmStatic`, `SelectNode`, `FilteredPropertyData`, `PageCloseOptions`, `ScriptDataStub`, `GPUDevice`, `UnionOrFaux`, `MenuDataAccessor`, `ListJobsRequest`, `RC`, `EmbeddableOutput`, `ScriptSource`, `EnclosureShape`, `DeleteQuery`, `Histogram`, `ComputedGeometries`, `BrowserContext`, `IStream`, `ClassifiedParsedSelectors`, `InfrastructureRocket`, `PureVisState`, `UILayoutViewController`, `WithNodeKeyProps`, `ParquetField`, `ValueCtx`, `ViewportService`, `Motor.StopActionValue`, `RingBuffer`, `pulumi.Output`, `QName`, `INotification`, `WebGL2RenderingContext`, `LatexAst`, `ValidatorResponse`, `BotsState`, `T7`, `SbbDialogConfig`, `instantiation.IConstructorSignature3`, `CredentialCreationOptions`, `IHillWarriorResult`, `RepositorySettingsValidation`, `FunctionDeclarationStructure`, `IThriftField`, `P.Logger`, `ERC721`, `ThemeFromProvider`, `Inputs`, `AudioData`, `evt_sym`, `ScrollAreaContextValue`, `TableStringWriter`, `IMusicRecordGrid`, `WebSocketMessage`, `FolderWithSubFolders`, `PerfGroupEntry`, `Protocol`, `TimelinePath`, `Ring`, `HTMLDataListElement`, `ReflectionObject`, `TSocketPacket`, `GMxmlHttpRequestResponse`, `DescriptorProto_ReservedRange`, `JsonRPC.Request`, `ExternalFile`, `ExceptionListItemSchema`, `FailoverGroup`, `SideBarView`, `ReferenceToken`, `Header`, `UpdateConfigurationResponse`, `DebugThread`, `api`, `AttributeDefinition`, `ValidationRecord`, `ServiceSetup`, `SoftwarePackage`, `formField`, `ValidationError`, `ActionsStage`, `TriggerEventCommand`, `MessageIDLike`, `ToolbarItem`, `TaskPoolRunResult`, `ServerLock`, `AddRepositoryCommand`, `AuthorisationStore`, `ParticipantListParticipant`, `NzCellFixedDirective`, `VoteAccountAsset`, `IntervalTimeline`, `VertexList`, `ShippingState`, `Mesh`, `SavedObjectsStart`, `RangeEntry`, `TilingScheme`, `DOMWrapper`, `LinearFlow`, `PromiseReadable`, `Map`, `NotDeciderInput`, `StyleRendererProtocol`, `PermissionObjectType`, `GeneratorVars`, `CalendarManager`, `StyleBuildInfo`, `JSMService`, `InstantiationContext`, `ParagraphProps`, `YieldExpression`, `HistoryStore`, `StylableResults`, `TypedHash`, `VideoInputType`, `DiscordEvents`, `ContentBlock`, `PublicKeyInfo`, `DestinationConfiguration`, `DiagnosticRuleSet`, `AuthTokenInfo`, `ValidationBuilder`, `GroupUserList`, `ILayoutRestorer`, `ObjectMapper`, `PhrasesBuilder`, `SuiCalendarItem`, `TLIntersection`, `planner.PlannerConfiguration`, `Stat`, `IR.BasicBlock`, `PackedBubbleChart`, `Wrapap`, `Eris.Message`, `LinkedWorkTree`, `Organisation`, `ResourceModel`, `IFluidDataStoreRuntime`, `ExtractRef`, `Vec4Sym`, `AggregateField`, `BottomBarItem`, `ResizeObserverService`, `PlayerPosition`, `DateRangeShortcut`, `ChartEvent`, `RegisteredDelegate`, `NgForage`, `IBlockType`, `KeybindingRegistry`, `QueryLang`, `Lesson`, `LayoutItem`, `ConnectionInformation`, `ImageScrollBar`, `DescribePackagesCommandInput`, `FabSpecExports`, `Spotilocal`, `Node.NodeMessage`, `ProtoFab`, `requests.ListGoodBotsRequest`, `CurlyOptions`, `GaugeVisualizationState`, `PolyBool.Shape`, `QueryParserVisitor`, `TypeAliasInfo`, `MediaView`, `CreateOfficeHour`, `ErrorOptions`, `CommentPattern`, `DedentToken`, `KernelSpec`, `AriaDescriber`, `INormalizedMessage`, `SendResult`, `MediaPlayer`, `TemplateIntegrationOptions`, `TVEpisode`, `JSONSchema7`, `MockToken`, `ContainerOS`, `SyncHandlerSubsetOf`, `MIROp`, `OptionalMaybe`, `LayerNode`, `AuthStateModel`, `IndexResponse`, `WebpageMetadata`, `NoticeEntity`, `SkillService`, `LinkChain`, `BlockFactory`, `CRUDEvents`, `PartBody`, `InterfaceBuilder`, `Multisig`, `ParticlesFlyerView`, `DashboardContainer`, `Sessions`, `TestTag`, `QuickReplyItemProps`, `TheCloudwatchDashboardStack`, `EmitParameters`, `sdk.IntentRecognitionCanceledEventArgs`, `MIRRecordType`, `Anthroponym`, `ITrackCallback`, `OsmWay`, `CloneFunction`, `ControlParams`, `QPixmap`, `ResolvedPackage`, `SPBatch`, `BlockModel`, `UpdateTagDto`, `Screens`, `RequestConditionFunctionTyped`, `Playlist`, `UpdateEmailTemplateCommandInput`, `BaseFilterInput`, `IHttpPostMessageResponse`, `ForEachPosition`, `BoardState`, `ECSEntity`, `RemirrorManager`, `ContractEntry`, `FindCursor`, `InspectionFailure`, `ParseNodeType`, `AxisContext`, `FormItem`, `MenuTargetProps`, `UnixTime`, `CDPTarget`, `VisualConstructorOptions`, `MediaKeyComponent`, `CustomUrlAnomalyRecordDoc`, `GetPrTimelineQuery`, `ConditionalTypeNode`, `monaco.editor.IReadOnlyModel`, `AsyncMachine`, `Vorgang`, `VdmNavigationProperty`, `WorkRequestLogEntry`, `MixItem`, `TagFilter`, `DeleteLoadBalancerCommandInput`, `models.IArtifactProvider`, `JssContextService`, `Frustum`, `LoudMLDatasource`, `Activator`, `IUIEvent`, `RuleSummary`, `MemberRef`, `PlayerPieceLocation`, `BodyOnlyAcceptsNumbers`, `RoleDto`, `OutputTargetDocsReadme`, `d.CompilerModeStyles`, `ComparableValue`, `Classifications`, `MediaProps`, `UseRefetch`, `mongoose.Model`, `ChainConfig`, `ParserType`, `Deno.Process`, `DataValues`, `HomePublicPluginSetup`, `AuxBot3D`, `SerializeOutput`, `UpdateUserProfileCommandInput`, `CallIdRef`, `JWTTokenModel`, `SessionOptions`, `AccountBalancesResult`, `RestRequestMethod`, `ConversationContent`, `CustomPaletteParams`, `ArangojsResponse`, `CrochetPackage`, `CodeVersions`, `BaseAddress`, `TimedVariableValue`, `Dice`, `C2`, `PanelOptions`, `IHTMLElement`, `jest.Mocked`, `vscode.QuickPick`, `HTMLIonLoadingElement`, `ObjectTypeComposerFieldConfigDefinition`, `GitCommit`, `ANK1`, `LineupPlayerPosition`, `AutoforwardState`, `CreateConnectionCommandInput`, `JsonHttp`, `CodeGenModel`, `VideoGalleryStream`, `TSrc`, `IProtoBlock`, `ListDomainsCommandInput`, `GPUImageCopyTexture`, `GenericMessage`, `ReplaceResult`, `OrganizationRepository`, `AccountHasFundsFn`, `SerializedChangeSet`, `DeploymentEntry`, `GameRegistry`, `Transpose`, `DefinitionProvider`, `builder.UniversalBot`, `IconRegistryService`, `PublicKeySection`, `VoiceState`, `JobService`, `localVarRequest.Options`, `ResolveXName`, `BitArray`, `ResourceId`, `INPUT_SIZE`, `ResponderActivityType`, `CliAction`, `SecurityKey`, `Tardigrades`, `FSNetworkRequestConfig`, `InterpolatorFactory`, `BBox_t`, `QueryStatus`, `FSTree`, `LibraryBuilderImpl`, `Texture2D`, `FlexPlacement`, `NodeOptions`, `ITilemap`, `MangaListStatusFields`, `ProofRecord`, `Email`, `DataPositionInterface`, `VertexInfo`, `AccountSteam`, `SinonMock`, `uinteger`, `PackageDiffImpl`, `NarrativeSchema`, `ColliderData`, `SMTPServerSession`, `TextureBlock`, `IfNode`, `ContractClass`, `SourceEditorArgs`, `Future`, `Subscription`, `IFloatV`, `CancelWorkRequestResponse`, `LiveShare`, `ValidationErrorPath`, `YearAggregations`, `ProxyServerSubscription`, `ts.CompletionInfo`, `CurveLocationDetailPair`, `EventLocation`, `Trie`, `HTMLScLegendElement`, `ParsedPlacement`, `typedb.DBMethod`, `ISettingRegistry.ISettings`, `GetListParams`, `IOptimizelyFeature`, `DependencyKey`, `EnvVars`, `App.services.IUriService`, `Subtract`, `UpdateCourseOverrideBody`, `IWallet`, `CodeFixContext`, `BoundPorts`, `GetUserSettingsReadModel`, `Rectangular`, `ReactTestRenderer.ReactTestRenderer`, `OpenFileDialogProps`, `ArrayDiffSegment`, `TestSource`, `StartJobRunCommandInput`, `TypedComponent`, `S3StorageProvider`, `CartState`, `LabaColor`, `SparseGrid`, `SegmentAPISettings`, `LoadParams`, `Length`, `ProxyableLogDataType`, `TestModuleMetadata`, `IGetJobPresetInput`, `Knex.Raw`, `ContextualTestContext`, `Unsubscriber`, `CssAnimationProperty`, `TimeLimitItem`, `SUCUpdateEntry`, `ICategoryInternalNode`, `FlagshipTypes.Config`, `requests.ListCpeDeviceShapesRequest`, `ILineTokens`, `OffchainTx`, `ModuleSymbolTable`, `WeierstrassPoint`, `ImGui.Access`, `Paginator`, `FlowLogInformation`, `ts.IndexSignatureDeclaration`, `DurationMs`, `CompileResult`, `ParameterizedString`, `IGetLanguagesResponse`, `ActionSource`, `MemoryStorageDriver`, `ExploredCohortState`, `theia.Disposable`, `AuthContext`, `Chat`, `RenderLeafProps`, `NodeWithOrigin`, `SignatureVerifier`, `ClassScheme`, `DependencyList`, `ComponentBuilder`, `ts.TypeReferenceNode`, `CommandLineOption`, `JSDocParameterTag`, `I2CWriteCallback`, `ContextContributor`, `DecodedIdToken`, `BatchRequest`, `IRow`, `NetGlobalMiddleware`, `ValueRef`, `ParseConfigHost`, `Priority`, `IParsedError`, `MapService`, `Reffer`, `CommunityDataService`, `GeometricElement2dProps`, `TElement`, `ItemSliding`, `DeployedCodePackage`, `ImportInfo`, `ParamItem`, `EmptyClass`, `USBInterface`, `ClassPeriod`, `GossipFilter`, `TileLayer`, `CyclicDependencyGraph`, `ts.JsxAttribute`, `GitHubAPI`, `d.WatcherCloseResults`, `FormatId`, `InitSegment`, `DateOption`, `TagToken`, `LegacyField`, `JPAChildShapeBlock`, `BinaryWriter`, `monaco.languages.LanguageConfiguration`, `VFC`, `ItemDefinition`, `IFilterProps`, `AsyncState`, `ITopDownGraphNode`, `ImplementedFunctionOptions`, `PiLanguage`, `Model.Page`, `MainHitObject`, `ServeOptions`, `S3Client`, `DateValue`, `ServiceClientCredentials`, `AllOptions`, `OutputTarget`, `MemberForm`, `XYChartSeriesIdentifier`, `Kernel`, `Wah`, `SubgraphPlaceholder`, `TransformerDiagnostics`, `ClaimItem`, `LoginStatusChecker`, `IAddressState`, `IExpectedVerifiableCredential`, `GestureController`, `MassetMachine`, `AccountApple`, `TinymathFunction`, `FailoverDBClusterCommandInput`, `ActionResultComboCtx`, `ScaleCreationContext`, `TimelineTheme`, `NgParsedDecorator`, `IVariable`, `BoolLiteralNode`, `I18nConfig`, `ExpressionRunnerShorthandConfig`, `ICombinedRefCheck`, `ListTournamentRecordsRequest`, `vd.createProperties`, `SeriesCompareFn`, `ListComprehensionForNode`, `RefreshAccessTokenAccountsRequestMessage`, `IOHandlerForTest`, `NodeName`, `BackupFile`, `JobLogOption`, `LogAnalyticsSourceEntityType`, `IMutableVector4`, `FolderDetector`, `NullConfiguration`, `ARAddImageOptions`, `GraphQLScalarTypeConfig`, `TransactionOp`, `RequireNode`, `WorkspaceSymbolParams`, `SPClientTemplates.RenderContext_FieldInForm`, `RenderableOption`, `ResolverResolveParams`, `WebConfig`, `IDomMethods`, `FieldFormatConvertFunction`, `IGroupInfo`, `TMessageContent`, `Aggregation`, `GluegunPrint`, `AuthenticationParameters`, `requests.ListVolumeGroupsRequest`, `Cypress.PluginEvents`, `CodeGenResult`, `SNSInvalidTopicFault`, `LocalVarInfo`, `SObjectConfig`, `QualifiedNameLike`, `ANTLRBackend`, `LambdaRestApi`, `GetFederationTokenCommandInput`, `ConfigConfigSchema`, `KibanaPrivileges`, `AddressBalance`, `IRefCallback`, `ts.ResolvedModule`, `ReadModelQuery`, `FilterDef`, `TPlacementMethodArgs`, `SoftwareKeyProvider`, `IDocumentStorage`, `ConfigAggregator`, `MaskingArgs`, `E2`, `ErrorMessageProps`, `TimeStamp`, `SymbolKind`, `ResourcePolicy`, `DocgeniContext`, `FieldSchema`, `LoopOutParameter`, `BillName`, `ItemWithAnID`, `UnionTypeNode`, `JSZipObject`, `ForwardRefExoticComponent`, `BlockStateRegistry`, `ObjectDictionary`, `HTMLIonActionSheetElement`, `core.BTCGetAccountPaths`, `IDoc`, `SingleConnection`, `TileCoordinate`, `ShareService`, `Worksheet`, `UICollectionViewFlowLinearLayoutImpl`, `IAstMaker`, `PointerInput`, `ZeroBalanceFn`, `ExpressionWithTypeArguments`, `NVMJSON`, `DiscordMessage`, `SwatchBookProps`, `PushSubscription`, `NodeConstructor`, `DeploySuccess`, `FileIdentifier`, `TwingFilter`, `SubmitFeedbackCommandInput`, `ModelPredictArgs`, `ISampler2DTerm`, `ShadeCoverOptions`, `AndroidPermissionResponse`, `PositionRange`, `WatcherFolder`, `AmbientZone`, `CodeAction`, `PlatformEvent`, `Chest`, `LocaleProps`, `Looper`, `AuthType.Standard`, `V2BondDetails`, `NSMutableURLRequest`, `IState`, `SignedState`, `DefaultExecutor`, `MiniNode`, `ast.NodeAttributes`, `IdentityTest`, `DirectionType`, `DraftEntityInstance`, `MenuModel`, `ToString`, `StashResult`, `ImageCanvas`, `utils.BigNumberish`, `PetService`, `ButtonTween24`, `ComputedField`, `IAureliaProjectSetting`, `IStatistics`, `IPath`, `Base`, `Reason`, `FilterMeta`, `ArtifactDelta`, `CCashCow.Payment`, `ServiceLogger`, `DebugBreakpointDecoration`, `ArgumentParser`, `CategorySortType`, `GraphQLTypeResolver`, `IMessageEvent`, `FileModel`, `GitAuthor`, `OtokenFactoryInstance`, `ResolveResponse`, `IOptionFlag`, `DomPath`, `MutationCallback`, `GX.TevColorChan`, `ListDetectorsCommandInput`, `ListProjectsCommandInput`, `FunctionBinding`, `V1PersistentVolume`, `OrganizationState`, `PartialApplicationConfig`, `CurvePrimitive`, `SingleTablePrettyfier`, `Claimants`, `AdonisApplication`, `Cave`, `WikiItem`, `JsonStringifierParserCommonContext`, `SMTPServer`, `ImportResolverFactory`, `AuthContextState`, `PlayMacroAction`, `PaginationNavProps`, `thrift.TField`, `Decision`, `ActionStatusEnum`, `Orphan`, `QueryInterface`, `VocabularyStatus`, `Neutrino`, `WalkNext`, `NgGridItemPosition`, `ErrorChain`, `RowNode`, `MDCBottomNavigationBar`, `Numeric`, `SceneFrame`, `ConfigsService`, `IRequestUserInfo`, `React.ReactElement`, `CreateUserProfileCommandInput`, `DomainService`, `ListWorkRequestsRequest`, `MouseEventHandler`, `GX.TexGenType`, `requests.ListSubscriptionsRequest`, `NamedTupleMember`, `ActionsConfig`, `EdgeMemento`, `Endpoint`, `JsonContact`, `HttpEnv`, `TaskService`, `PokemonType`, `PlatformService`, `IMetricsRegistry`, `Workspaces`, `RlpItem`, `SBDraft2CommandOutputParameterModel`, `MovieOpts`, `GossipPeer`, `OffsetPosition`, `NexusGraphQLSchema`, `GetPublicAccessBlockCommandInput`, `SourceBreakpoint`, `CRG1File`, `ParsedQuery`, `Matrix2d`, `PendingTransaction`, `FormatterOptions`, `FocusedElement`, `ITelemetryLogger`, `IndicatorForInspection`, `PackageManagerPluginImplementation`, `MangaFields`, `AutoOption`, `TNSPath2D`, `SeriesPlotRow`, `WalkerArgs`, `ShaderNode`, `FeatureSymbology.Overrides`, `DbIncrementStrategy`, `ProcessedBundle`, `ProgressToken`, `RouterInstruction`, `TargetType`, `CreateJobDetails`, `GlobOptions`, `RequirementBaseModel`, `AttachmentItem`, `TSInstance`, `NotebookWorkspaceName`, `PlayerIndexedType`, `SubtitlesCardBase`, `RenderSource`, `Genre`, `ITokenMatcher`, `BlendMode`, `ResultData`, `CommandLineOptions`, `FlatTreeControl`, `MessageContent`, `IKey`, `IRandomAccessIterator`, `Erc20Mock`, `GraphQLInterfaceType`, `DeleteLoggingConfigurationCommandInput`, `MediaChange`, `CreateReplayDto`, `HttpContextContract`, `ListCustomPluginsCommandInput`, `JsExpr`, `RnM2Material`, `CoverageCollection`, `SelectionItem`, `IRawBackupPolicy`, `ThyPopoverConfig`, `React.CompositionEvent`, `BookingsModel`, `Foo`, `ReadFileOptions`, `FormatMessage`, `ATNConfigSet`, `CompileRepeatUtil`, `ISearchRequestParams`, `ServerSideProps`, `SizeData`, `PipelineId`, `PkgJson`, `ExpandedTransitionListener`, `ParentComponent`, `NotImplementedYetErrorInfo`, `EtjanstChild`, `ProjectBuildOptions`, `PlainObject`, `N6`, `CreateAttendeeRequestItem`, `SubscriptionClient`, `CustomIntegrationRegistry`, `ThySkeletonComponent`, `I18NextPipe`, `core.Connection`, `LocatorDiff`, `Options`, `CliParam`, `CommandOutputBinding`, `MonitoringOutputConfig`, `IDataFrame`, `PhysicalElement`, `CollapsibleListProps`, `MessageActionRow`, `Merge`, `Catalog`, `DogePaymentsUtilsConfig`, `Messaging`, `vscode.TextEditor`, `ControllerConfig`, `MatchResult`, `BaseContract`, `CalendarManagerService`, `Incident`, `ReuseTabNotify`, `ElementInstance`, `ProcessingPayload`, `CompositeDraftDecorator`, `STIcon`, `ECDb`, `KernelInfo`, `SchematisedDocument`, `ArrayProperty`, `TranslationFacade`, `AnyRect`, `LayoutSettings`, `PointMarkerOptions`, `ReturnTypeFunc`, `RegistryMessage`, `ObjectCacheState`, `MixArgs`, `Highcharts.VMLDOMElement`, `LangChangeEvent`, `ModelSnapshotType`, `AggField`, `FrontMatter`, `Invite`, `EventProcessor`, `sdk.TranslationRecognitionResult`, `FastifyTypeBoxHandlerMethod`, `Intent`, `GregorianDate`, `Track`, `ZoweUSSNode`, `tfc.io.IOHandler`, `VerifyOptions`, `FileIconService`, `ChannelMessageSend`, `StepNode`, `ProvenClaim`, `ContentDirection`, `IChildrenItem`, `OutputTargetEmptiable`, `FormMethods`, `RequestBase`, `PopupMessage`, `Protocol.Input.DragData`, `ParsedSelectorAndRule`, `RegisteredSchema`, `thrift.TType`, `PromiseEmitter`, `StringCodeWriter`, `TransactOptions`, `ProposalTemplateService`, `Peripheral`, `ComponentTester`, `ISetOverlapFunction`, `UpdateFileService`, `IColorEvent`, `MonitoringGroupContext`, `PlanService`, `TaskInstance`, `LocationType`, `KC_PrismData`, `ProjectMode`, `NamedCollection`, `GithubUserRepository`, `CombatStateMachineComponent`, `SettingRepository`, `FlushMode`, `AnimGroupData`, `TreeListComponent`, `TName`, `EosioTransaction`, `TypeSourceId`, `ChangeHandler`, `CookieManager`, `AsyncIterator`, `Rect2`, `LifecycleChannel`, `TextFieldWithSelectionRange`, `ConditionFn`, `SourceDataItem`, `Logger`, `IGetTimeLogConflictInput`, `FormAction`, `SourceTargetFileNames`, `UIBeanHelper`, `LineAnnotationSpec`, `PublishResponse`, `HttpInterceptController`, `SymlinkInode`, `XSelectNode`, `IDependency`, `Preferences`, `MicroframeworkSettings`, `BlinkerResponse`, `ComputedBoundsAction`, `DropTableNode`, `FnAny`, `GetFileOptions`, `Quantity.REQUIRED`, `AggregateSpec`, `restify.Request`, `OpenPGP.key.Key`, `FindOneOrFailOptions`, `MongooseSchema.Types.ObjectId`, `CreateElementRequiredOptions`, `ZodUnion`, `AccordionProps`, `Applicative2`, `GReaderConfigs`, `ValueMetadataBuffer`, `RtcpSourceDescriptionPacket`, `SvelteElement`, `NetType`, `ExtensionState`, `CreateExtensionPlugin`, `pd.E2EPageInternal`, `ClientAuthentication`, `MemoryView`, `panel_connector.MessageHandler`, `AdapterGuesser`, `FormFieldConfig`, `PoolType`, `LoadOptions`, `DatasetMemberEntry`, `TionDeviceBase`, `EnvOptions`, `JsonRPC.Response`, `Subspace`, `SQLTransaction`, `BaseDbField`, `GroupCurrencyCode`, `Requester`, `AccountParser`, `Clock`, `DebugProtocol.StepOutResponse`, `MXFloatingActionButtonLocation`, `Comment`, `ListAvailabilityHistoriesRequest`, `FromYamlTestCaseConfig`, `WSClient`, `Unknown`, `PackagesWithNewVersions`, `DayPickerContextValue`, `Sort`, `DecodedJwt`, `ImportGroup`, `JobState`, `TypePairArray`, `FakeContract`, `WebSocketConnectCallbacks`, `cp.ChildProcess`, `FeatureAst`, `BandHeaderNS.CellProps`, `ErrorStateMatcher`, `CrudGlobalConfig`, `RegisterCr`, `EditorManager`, `PlatformType`, `ProxyRequestResponse`, `LogLayout`, `QueryRef`, `OutputTargetDistLazy`, `ShortTermRetentionPolicyName`, `TargetedEvent`, `MapProps`, `UnknownParticipant`, `PublicMethodsOf`, `AWSAccount`, `EngineAttribute`, `Guild`, `ICliCommandOptions`, `ForNode`, `LabelBullet`, `ArcProps`, `PlaceholderMapper`, `types.ScriptType`, `TelemetryRepository`, `Response.Response`, `ForInitializer`, `ParsedMapper`, `WebsocketRequest`, `HealthCheck`, `TransferHotspotV2`, `KeyMap`, `ExposureMode`, `ServerView`, `IMetricsService`, `Locker`, `ListBotsCommandInput`, `AddPermissionCommandInput`, `PatchOptions`, `HStatus`, `DTONames`, `ThyUploadResponse`, `ISubmitData`, `NpmPackage`, `Ribbon`, `CardContext`, `P2P`, `InternalKey`, `AnalyzerState`, `Types.OutputPreset`, `StaffService`, `AudioBuffer`, `ExpectedTypeResult`, `VisualUpdateOptions`, `AssertionExpression`, `d.OutputTargetDistCollection`, `CustomLoader`, `PortalConfig`, `MdcSwitch`, `CLR0_MatData`, `StatusProps`, `ProofNodeX`, `BrowserDownloads`, `ConnectionInfoResource`, `ListCertificateAuthoritiesCommandInput`, `BigFloat53`, `DoneCallback`, `XliffMerge`, `RandomUniformArgs`, `VectorLayer`, `LoginScript`, `ListrTask`, `CAC`, `vscode.Progress`, `Lint`, `requests.ListVlansRequest`, `t_b79db448`, `SearchQueryUpdate`, `DataBlock`, `TDiscord.Client`, `StylePropConfig`, `IIPCClient`, `ConfigurationCCAPISetOptions`, `PriceAxisViewRendererCommonData`, `CommonDialogService`, `Raw`, `IAddressSpace`, `MarkerProps`, `Refactoring`, `NET`, `KeywordErrorCxt`, `JWTService`, `GfxRenderPipelineDescriptor`, `UpdateError`, `EventNameFnsMap`, `AccountsScheme`, `QuadrantRefHandler`, `NumberToken`, `OutputDataConfig`, `GetOptions`, `Ruleset`, `IndexingStatusResolver`, `ILogOptions`, `ActionOptions`, `NormalisedSearchParams`, `WorkspaceMiddleware`, `BaseRedirectParams`, `IOrganizationBinding`, `MetaClient`, `Exit`, `MintAssetRecord`, `Jump`, `iff.IChunkHeader`, `HypermergeUrl`, `DescribeAppInstanceAdminCommandInput`, `JSONSchemaRef`, `HostWindowService`, `DatasetSummary`, `Recording`, `CreateSampleFindingsCommandInput`, `MeetingParticipants`, `Bytes32`, `MutationElement`, `ClipsState`, `AssembledTopicGraphics`, `ActorType`, `SpaceSize`, `ListThemesCommandInput`, `BodyPixConfig`, `FieldFormatsContentType`, `Payport`, `RenderPage`, `GoldenLayout.ContentItem`, `RawTypeInfo`, `ITelemetryProperties`, `AnyNativeEvent`, `ThreadKey`, `DeleteRequest`, `TEUnaryOp`, `EditableProps`, `EffectContext`, `NzMessageService`, `TimePickerControls`, `Active`, `ITransValueResult`, `DeleteApplicationCommandInput`, `TokenManager`, `apid.RecordedTagId`, `MainAreaWidget`, `TLocaleType`, `ConfigurationsClient`, `ICommonHeader`, `d.OutputTargetDistTypes`, `StoreObjectArg`, `AndroidChannelGroup`, `PointerEventHandler`, `MinHeap`, `Device`, `EmacsEmulator`, `AfterWinnerDeterminationGameState`, `workerParamsDto`, `Milestone`, `CosmeticFilter`, `HeadElement`, `StartStop`, `ConfirmHandler`, `GetDMMFOptions`, `EntityProps`, `UnparsedSource`, `OnChangeValue`, `TestingRunOptions`, `SponsorOptionsOpts`, `ChartElementSizes`, `PeopleEmitter`, `ShortcutType`, `PBXGroup`, `MDCMenuSurfaceAdapter`, `Real_ulonglong_numberContext`, `SocketServer`, `ts.SemanticClassificationFormat`, `Events.predebugdraw`, `DepositTransaction`, `VirtualApplianceSite`, `TLE.Value`, `... 28 more ...`, `ICombiningOp`, `ObjectCacheService`, `MarkMessageAsSeenCommand`, `IPipe`, `FunctionMethodsResults`, `IEtcd`, `ListAppInstanceAdminsCommandInput`, `RendererAPI`, `SendEmailCommandInput`, `WordcloudUtils.PolygonPointObject`, `PacketRegistry`, `DebugProtocol.NextArguments`, `ChunkExtractor`, `RegExpReplacement`, `EmitBlockKind`, `ODataResponse`, `AutoSubscription`, `Caret`, `InvalidDatasourceErrorInfo`, `UpdateGatewayCommandInput`, `TableContext`, `SortedSet`, `ChildReferenceDetail`, `IsMutedChangedListener`, `CachedResource`, `DataService`, `Csp`, `IAmazonInstanceTypeOverride`, `RSAKey`, `TocState`, `sdk.DialogServiceConnector`, `DeployView`, `IIStateProto`, `Keystore`, `CdkColumnDef`, `TodoTaskList`, `ListItem`, `DataArrayTypes`, `HeaderSetter`, `StatResult`, `SnapshotProcessor`, `Threshold`, `FileCompletionItemManager`, `DoublyLinkedListNode`, `HeadlessChromiumDriver`, `IPlayerActionCallback`, `GetParameters`, `R.List`, `MetadataValueFilter`, `MediaRule`, `IZoweTree`, `IUIAggregation`, `ChildProcess`, `chrome.windows.Window`, `TableFinder`, `UserSettingsStorage`, `IExternalDeviceId`, `FilesMatch`, `ValidationErrorItem`, `GroupType`, `IItemTemplate`, `NvLocation`, `ts.ResolvedModuleWithFailedLookupLocations`, `SetupOptions`, `EpicMiddleware`, `JPAEmitterWorkData`, `tf.Tensor`, `AsToken`, `CertaConfig`, `AuthenticationProviderOptions`, `ReportManager`, `SharesService`, `RSAEncryptionParams`, `AppMountParameters`, `EvaluatedTemplateArgument`, `DefaultSequence`, `ICCircuitInfo`, `IFilterArgs`, `ASTResult`, `MockTrueCurrency`, `IPortal`, `GlobalStorageOptionsHandler`, `RoleValidationResult`, `nodeFunc`, `SyncMode`, `IAgent`, `SharingSessionService`, `Abbreviation`, `ListWorkspacesRequest`, `ContractParameter`, `UsePaginatedQueryReducerAction`, `TreeMate`, `SearchOptions`, `SwiftDeclarationBlock`, `ElementAspect`, `BootstrapOptions`, `GetResourceCommandInput`, `CertificateRule`, `DecodedAttribute`, `XPCOM.ContentFrameMessageManager`, `Long`, `IBaseEdge`, `Vector2d`, `ArrayIterator`, `nodeFetch.RequestInit`, `StoryObj`, `IntPairSet`, `SourceMapper`, `ArtifactEngine`, `u64`, `VertexType`, `MonitoredElementInfo`, `IHandlebarsOptions`, `ProductOperations`, `ComparisonOptions`, `StoryArchive`, `TtLCreatorOptions`, `JSONScanner`, `EditorConfiguration`, `models.NetCore`, `GetUsersRequest`, `MDCRadioAdapter`, `IOracleListener`, `EventTrigger`, `BeEvent`, `GeneratorTeamsAppOptions`, `RequestMethodType`, `CppSettings`, `ICreateOrgNotificationResult`, `FabricWalletRegistryEntry`, `ChangeDescription`, `View1`, `D3Selector`, `ScriptVersionCache`, `DeepType`, `StoreData`, `IAssetsProps`, `CriteriaNode`, `FileMetadata`, `FontStyle`, `QueryFilterType`, `Seg`, `PrimitiveNonStringTypeKind`, `TContainer`, `ContentManagementService`, `AlertNavigationRegistry`, `PoiLayer`, `CallError`, `ExpectApi`, `TokenGroup`, `IDriver`, `ODataQueryMock`, `FeedProviderType`, `TodosPresentST`, `RuleSet`, `ProfileResponse`, `CustomAvatarOptions`, `ISubject`, `FastPath`, `IPascalVOCExportProviderOptions`, `ICordovaLaunchRequestArgs`, `ActorRef`, `RemoveBuffEvent`, `CacheWithRedirects`, `DecryptedMessage`, `LoggingServiceConfiguration`, `NgxFeatureToggleRouteGuard`, `RoomReadyStatus`, `TransactionJSON`, `ReplacePanelAction`, `FormGroup`, `RemoteStoreOptions`, `IssueIdentifier`, `MinimalCancelToken`, `JsxTagNameExpression`, `IPrivateKey`, `ScriptElementKind`, `LabStorageService`, `SurveyMongoRepository`, `DescribeUserResponse`, `ComponentCompilerStaticEvent`, `TypeAttributeMapBuilder`, `CommandEventType`, `SubTiledLayer`, `AddressHashMode.SerializeP2PKH`, `BRRES.RRES`, `FileStream`, `EditLog`, `RelationInput`, `FormDependency`, `Filters`, `server.ManualServerConfig`, `WhiteListEthAsset`, `TokenDict`, `FieldDestination`, `IRole`, `CHILD`, `RequestPrepareOptions`, `CreateBundle`, `Chain`, `selectionType`, `ITBConfig`, `RawBackStore`, `DocumentStateContext`, `Entities`, `MagicLinkRequestReasons`, `PageMeta`, `LinkedIdType`, `PlanetApplicationRef`, `ImageHelper`, `DocumentTypeDef`, `ErrorDetail`, `DiscoveredMethodWithMeta`, `Messenger`, `ProgressState`, `RecordRepresentation`, `LanguageModel`, `events.Name`, `ButtonItem`, `DraftEditor`, `Conv2DInfo`, `GDQOmnibarMilestoneTrackerPointElement`, `TestCreditCardPack`, `InjectorModule`, `ComponentCompilerTypeReferences`, `ParseValue`, `UserProfile`, `O2MRelation`, `JimpImage`, `ConfigLogger`, `RefreshToken`, `AngularFireOfflineDatabase`, `UseProps`, `GlobalStringInterface`, `VerifyUuidDto`, `VisualViewport`, `Wei`, `Pod`, `Flo.EditorContext`, `RequestHandlerContext`, `JestTotalResults`, `IRenderLayer`, `TwitchBadge`, `IMapper`, `RepoInfo`, `LoadSettings`, `RequireOrIgnoreSettings`, `ParsedHtmlDocument`, `V1ClusterRoleBinding`, `GeoUnitIndices`, `java.lang.Object`, `DeleteClusterCommand`, `ObjectProps`, `ZoneType`, `SecuredFeature`, `SubmitFnType`, `BlockLike`, `PerformStatArgs`, `Interpolation`, `HSVColor`, `DashboardAppLocatorDefinition`, `RectAnnotationStyle`, `TimeConstraint`, `GunGraphNode`, `EzApp`, `vBlock`, `ColumnDefinitionNode`, `WikiFile`, `GroupUserList_GroupUser`, `GeoCoordinates`, `NxValues`, `echarts.EChartsOption`, `TeamList`, `SavedObject`, `SignedByDBInterface`, `RemoveNotificationChannelCommandInput`, `IStudy`, `xLuceneVariables`, `EntityHydrator`, `NumberValidator`, `UiKit.BlockContext`, `SPADeploy`, `TSelectedItem`, `TagService`, `CustomEvent`, `TSunCardConfig`, `MouseEventToPrevent`, `ShaderType`, `RebootDBInstanceCommandInput`, `IPushable`, `Sequence`, `DeleteSourceServerCommandInput`, `uproxy_core_api.CreateInviteArgs`, `CursorPosition`, `ClassDecorator`, `DrawState`, `DisposableSet`, `CommandPacker`, `RGBValue`, `DataGrid`, `UrbitVisorState`, `TGroupBy`, `Validate`, `FaunaRoleOptions`, `LoadBalancer`, `GraphMode`, `RecordsQuery`, `NavigationScreenProp`, `Milliseconds`, `ValidatedJobConfig`, `AccountAndPubkey`, `IInterpolatedQuery`, `AbiCoder`, `Api`, `MockTask`, `ConvertOptions`, `Remote`, `Origin`, `FilterOptions`, `EnvironmentAliasProps`, `ts.VariableDeclarationList`, `EdmxEnumType`, `PackageExpanded`, `WorkspaceSnaphot`, `ShoppingCartItem`, `PLSQLRoot`, `ParquetWriterOptions`, `FileSpan`, `ProjectData`, `io.IOHandler`, `INgWidgetContainerRawPosition`, `ClassAndStylePlayerBuilder`, `ENDDirective`, `ListRulesCommandInput`, `TreeStateObject`, `sdk.Recognizer`, `Errback`, `CardComponent`, `LiteralContext`, `Messages.BpmnEvents.TerminateEndEventReachedMessage`, `ProjectRiskViewEntry`, `ReporterConfig`, `Client`, `PathUpdater`, `FocusType`, `NestExpressApplication`, `HK`, `ActiveWindow`, `AppInstanceEventType`, `LanguageEffects`, `FetchListOptions`, `CollectionDependencyManifest`, `InitializerMetadata`, `ContainerNode`, `WalletI`, `LocationOffset`, `ChoiceValue`, `WFWorkflowAction`, `requests.ListBastionsRequest`, `TestSuiteInstance`, `IpcService`, `PluginResultData`, `NgModuleDefinition`, `LoaderEvent`, `ReactDataGridColumn`, `NetworkgraphPoint`, `TestScriptError`, `Commit`, `DeviceID`, `IScribe`, `BenchmarkData`, `AnyObjectNode`, `MDCChipActionType`, `MessengerTypes.PsidOrRecipient`, `ResolvedConfiguration`, `Lexer`, `IOptionTypes`, `IVariableDefinition`, `FirebaseDatabaseService`, `KubeConfig`, `Tangent`, `IChainableEvent`, `Events.pointerdragstart`, `EquipmentStatus`, `LeftObstacleSide`, `user`, `postcss.Declaration`, `SocketIO.Server`, `ScaleGroup`, `ChildRuleCondition`, `PolygonProps`, `InitializeStateAction`, `SapphireDbOptions`, `IClusterHealthChunkQueryDescription`, `d.FsItems`, `ClientInstance`, `LSTMCellLayerArgs`, `WaveType`, `FeatureInterface`, `BoundSphere`, `MonitoringConfig`, `ITypeFactory`, `ShippingService`, `TransformConfigUnion`, `Hsva`, `ICommandResult`, `UpdateCategoryDto`, `IGetTimeLimitReportInput`, `apid.ChannelId`, `WriterToString`, `StartMeetingTranscriptionCommandInput`, `IEntryDefinition`, `RemoteSeries`, `PointGeometry`, `ProgressBarService`, `StackPath`, `ColliderShape`, `ParsedDID`, `TagsProps`, `ts.ImportEqualsDeclaration`, `IAdjacencyCost`, `CollaborationWindow`, `DesignerNodeConn`, `OverlayReference`, `IProjectCard`, `ApplicationCloseFrame`, `SourceCodeLocation`, `FunctionCallContext`, `Encoding`, `DndEvent`, `LoaderFunction`, `FoldingRange`, `DropDown`, `Body2DSW`, `IRequestApprovalCreateInput`, `Separator`, `AcLayerComponent`, `WorkflowStepInputModel`, `CosmosdbAccount`, `FilesystemProvider`, `TabEntity`, `DIRECTION`, `IntervalTimelineEvent`, `WaitForEvent`, `PaymentChannelJSON`, `TransactionBuilder`, `IClusterDefinition`, `JsonRpcRequestPayload`, `requests.ListReplicationSourcesRequest`, `TimelineTrackSpecification`, `AggsCommonSetupDependencies`, `SerializedNodeWithId`, `CasesClient`, `Json`, `MatDatepickerIntl`, `Fetch`, `HTMLAudioElement`, `StakingTransactionList`, `ModelArtifacts`, `SerialAPICommandMachineParams`, `DataFrameAnalyticsListRow`, `UpdateChannelParams`, `ShaderVariant`, `AnimatedSprite`, `SvgPoint`, `TcpConnection`, `TransformCallback`, `DatabaseInterface`, `AGG_TYPE`, `BookingState`, `OotOnlineStorage`, `IFreestylerStyles`, `SCClientSocket`, `EntityState`, `ExternalProps`, `mergeFunc`, `MutableTreeModel`, `AnnotationLineProps`, `Allowance`, `SVGFilterElement`, `CrossProductNode`, `DescribeVolumesCommandInput`, `TrieMap`, `SubgraphDeploymentID`, `JoinerCore`, `DialogConfig`, `ParsedCssFile`, `ILease`, `TreemapSeriesNodeItemOption`, `TestDuplex`, `AiService`, `IIonicVersion`, `Models.OrderStatusReport`, `FieldUpdates`, `MUserId`, `AztecCode`, `MatchmakerTicket`, `IBatch`, `RTCPeer`, `FoldCb`, `Measurable`, `LoginPage`, `MoveT`, `ReleaseResource`, `SingleKeyRangeSet`, `CategoriesState`, `AboveBelow`, `MockCloudExecutable`, `ParsedMessagePartPlaceholder`, `ConfigurationContext`, `ParserService`, `YggdrasilAuthAPI`, `ParsedJSXElement`, `IP`, `NgxMdService`, `SettingNavigation`, `MediaDiagnosticChangedEventArgs`, `ExampleProps`, `ResponderHelper`, `InspectTreeResult`, `parseXml.Element`, `InputType.StyleAttributes`, `PlotConfigObject`, `Jwk`, `ESAssetMetadata`, `ELang`, `MapsVM`, `SafeAny`, `StateCreator`, `MultiSelectRenderProps`, `EventFactory`, `GetStaticProps`, `HttpWrapper`, `Scene3D`, `meow.Result`, `ListPingMonitorsRequest`, `Spaces`, `NullConsole`, `SqlStatisticsTimeSeries`, `FlattenedFunnelStep`, `Projects`, `SFAAnimationController`, `ITypedNode`, `IArticle`, `TPagedList`, `LabelValuePair`, `IMiddlewareProvider`, `IDateFnsLocaleValues`, `ObservableQueryValidatorsInner`, `CardAndModule`, `EslingPlugin`, `URI`, `RawShaderMaterial`, `CreateTokens`, `CompositeTraceData`, `WithBigInt`, `FormGroupState`, `GetServiceRoleForAccountCommandInput`, `MetricAggParam`, `AADResource`, `TsChipComponent`, `EchartsTimeseriesChartProps`, `V1PodList`, `AnyConfigurationSchemaType`, `DecimalFormatter`, `UserManagementService`, `cc.RenderTexture`, `RouteComponent`, `ParticipantsRemovedListener`, `NewMsgData`, `PureReducer`, `Handlebars.HelperDelegate`, `Requests`, `GlobalGravityObj`, `Radio`, `MerkleProof`, `MapPolygonSeries`, `IRChart`, `MessengerTypes.SendOption`, `ReadonlyNonEmptyArray`, `WalkerCallback`, `MetaKey`, `ChemControllerState`, `Modules`, `ComponentCompilerData`, `LinesTextDocument`, `AgCartesianChartOptions`, `Candle`, `TasksService`, `OperatorAsyncFunction`, `QueryHookOptions`, `CompilerOperation`, `Follower`, `WebResource`, `SubmissionServiceStub`, `AxisLabelOptions`, `TextAnimationRefs`, `LegacyService`, `EzRules`, `GenericConstructor`, `IEntityMetaOptions`, `BrowserHelper`, `ConfigDeprecation`, `UhkBuffer`, `Events.collisionstart`, `CommentResponse`, `RenderElementProps`, `instantiation.IConstructorSignature7`, `IDownloadOptions`, `API.storage.IPrefBranch`, `TaskParameter`, `CardView`, `ICredential`, `UploadedVideoFileOption`, `ApiCallByIdProps`, `PortingProjects`, `IGraphicOption`, `LogChildItem`, `DeletePermissionPolicyCommandInput`, `FactoryContextDefinition`, `SelectionSet`, `ObjectType`, `EveesMutation`, `IBoot`, `LayoutStyleProps`, `CompilerState`, `TabData`, `CoExpNum`, `NextFn`, `SecurityUtilsPlugin`, `GlobalMaxPooling2D`, `IChangeHandler`, `CurrencyMegaOptions`, `TPageWithLayout`, `PrimitiveFixture`, `Delta`, `MobileCheckPipe`, `TransformerStep`, `IStateTreeNode`, `ParsedResponse`, `FileChangeEvent`, `child.ExecException`, `CategoryPage`, `CalculatedColumn`, `providers.TransactionResponse`, `QueryCacheResult`, `GetAppInstanceRetentionSettingsCommandInput`, `XYArgs`, `GitHubService`, `requests.ListWafTrafficRequest`, `LatLng`, `SceneActuatorConfigurationCCReport`, `ResolveNameByValue`, `ConnectionHealthPolicyConfiguration`, `ModuleManager`, `IAPIFullRepository`, `UserRegisterData`, `BlogPostService`, `Line3`, `CanvasFontFamilies`, `SortedQuery`, `Stringifier`, `WebSocketEventListener`, `MemberAccessFlags`, `Applicative1`, `StageInterview`, `TabbedTable`, `ActionConfig`, `TraderWorker`, `Subscribe`, `ElectronLog`, `ProjectEntity`, `ComponentRegister`, `NoteCollectionService`, `PDFNumber`, `CreateBackupCommandInput`, `DisplayState`, `EventBinderService`, `LevelService`, `UpdateEvent`, `GetIn`, `SplittedPath`, `requests.ListSnapshotsRequest`, `PackageLockPackage`, `typedb.DBType`, `ZoneChangeOrderModel`, `OrbitCoordinates`, `NormalizedFormat`, `MaybeNestedArray`, `d.SitemapXmpResults`, `DataviewSettings`, `BoxObject`, `CanvasRenderer`, `IKeyPair`, `ListAst`, `IJWTPayload`, `NormalizeStyles`, `MaskServer`, `ExampleSourceFile`, `RestoreDBClusterFromSnapshotCommandInput`, `CounterfactualEvent`, `ApiErrorMessage`, `FormatProps`, `GraphPartitioning`, `DatasetManager`, `SwimlaneRecordPayload`, `TxLike`, `EventEmitter.ListenerFn`, `DescribeAlarmsCommandInput`, `AthleteSettingsModel`, `ServiceQuotas`, `DynamoDB.BatchWriteItemInput`, `UseSelectStateOutput`, `JPARandom`, `SQL`, `FlowLabel`, `TileCoords2D`, `InternalErrorException`, `CustomIntegrationsPluginSetup`, `CssClass`, `ITransitionPage`, `IFieldExpression`, `ProviderInfrastructure`, `RequestModel`, `Zeros`, `SyntaxKind`, `NodeModuleWithCompile`, `FzfResultItem`, `ITableAtom`, `OperationContract`, `DelayLoadedTreeNodeItem`, `DataTypesInput.Struct2Struct`, `PullRequestNumber`, `ModuleSpecifierResolutionHost`, `Opcode`, `ViewerRenderInput`, `CompilerEventFsChange`, `ITestAppInterface`, `ProfileModel`, `InvalidateAPIKeyResult`, `Contexts`, `ModelService`, `LegendPath`, `RuntimeTreeItem`, `IndexPatternsServiceDeps`, `IChannelModel`, `ReadonlyObjectKeyMap`, `Dialogue`, `Viewport`, `RegisteredServiceUsernameAttributeProvider`, `LookupKey`, `KeyboardListener`, `PrimitiveType`, `ParameterStructures`, `FormfieldBase`, `ExecutedQuery`, `SprintfArgument`, `ReflectionProbe`, `QueryConfig`, `Zone`, `AzExtTreeItem`, `WebhookClient`, `TwingFunction`, `PatternMappingEntryNode`, `KintoClientBase`, `LinearRegressionResult`, `RedisClientType`, `CaseConnector`, `OperatingSystem.macOS`, `Vec4Term`, `MessageSentListener`, `Mat4`, `RecurringCharge`, `ListTemplateVersionsCommandInput`, `CustomFunction`, `WexBimRegion`, `TimesheetFilterService`, `ActiveQuery`, `NameT`, `BeforeUnloadEvent`, `QueuedEvent`, `VerificationToken`, `FormInstance`, `LogData`, `ImagePicker`, `ts.ExportDeclaration`, `reduxLib.IUseAPIExtra`, `UpdateApplicationDetails`, `ValuesMap`, `IOrganizationProjectsFindInput`, `React.DragEventHandler`, `IVectorSource`, `ForkName`, `PageContainer`, `MdcChip`, `ArgsMap`, `CreditWords`, `IServerSideGetRowsParams`, `CachedBreakpoint`, `d3Transition.Transition`, `SharedFileMetadata`, `AstModule`, `TestingGroup`, `TransitionProps`, `EditorInterface`, `ExecutionActivity`, `Cardinality`, `GroupActorType`, `ModeManager`, `Not`, `IPersonDetails`, `ICertificate`, `FSNetwork`, `DescribeDatasetGroupCommandInput`, `vscode.CompletionItem`, `PatternAtomNode`, `SerializedValue`, `Shim`, `IMessage`, `HammerInstance`, `ViewerPreferences`, `GroupByColumn`, `Path8`, `CacheInstance`, `GqlContext`, `TreeCursor`, `SpreadAssignment`, `MockSdkProvider`, `ElementAnimateConfig`, `InterfaceWithDeclaration`, `IWorld`, `ExecuteOptions`, `IdentityService`, `SoFetchResponse`, `Song`, `TransportResult`, `NoiseSocket`, `IOrderedGroup`, `React.ElementType`, `GeometrySector`, `MiStageState`, `SocketType`, `CreateManyDto`, `THREE.Color`, `DocumentRegistry`, `SubscriptionsClient`, `PortRecordMap`, `StoreContext`, `telemetry.Properties`, `AssetOptions`, `DeployingWallet`, `ProjectSpecBase`, `DFChatArchiveEntry`, `requests.ListAutonomousContainerDatabasesRequest`, `DriverSurface`, `BlockNumberPromise`, `HTMLSlotElement`, `MenuI`, `UpdateContext`, `SBGClient`, `BlockCipher`, `OrderedDictionary`, `d.NodeMap`, `EventInteractionState`, `Computation`, `Angulartics2AppInsights`, `CanaryConfig`, `PackageToPackageAnalysisResult`, `IResizeInfo`, `TemplateStore`, `ICoinProtocol`, `JsonLdDocumentProcessingContext`, `AlgoFn`, `Classify`, `FaastModuleProxy`, `MigrateEngineLogLine`, `TabDataType`, `RegisteredModule`, `CustomGradientFunc`, `FormPage`, `ExpressRouteCircuit`, `Realm`, `TabPane`, `t.Transformed`, `ColumnSummary`, `StageDataHolder`, `GetReviewersStatisticsCollectionPayload`, `SimpleLinkedTransferAppState`, `NamedExportBindings`, `ConnectionType`, `Backbone.ObjectHash`, `Flo.ElementMetadata`, `FileState`, `RequestDetailsState`, `ControlCenterCommand`, `EmbeddableSetupDependencies`, `ValidResource`, `WithEnum`, `DefaultTreeElement`, `CrudRequestOptions`, `VisTypeAliasRegistry`, `EndpointClass`, `keyboardKey`, `WindowOptions`, `CommandLineOptionOfListType`, `BaseEditor`, `DomainEvent`, `DataUp`, `AstLocation`, `CalendarHeatmapData`, `AbstractSqlModel`, `RuntimeConfiguration`, `IChainConfig`, `ServicePort`, `CredentialService`, `ResetButtonProps`, `LoggerInstance`, `ts.LanguageService`, `Delayed`, `SaveOptions`, `ExpressionContext`, `IfStatementContext`, `MarkdownSerializerState`, `MUserAccountId`, `Itinerary`, `BaseFrame`, `IAngularEvent`, `RequiredAsset`, `ClientRequestSucceededEventArgs`, `ServerHelloVerifyRequest`, `MakeRestoreBackup`, `LeakyReLU`, `CCResponsePredicate`, `MaskListProps`, `ObservableUserStore`, `GeneratePipelineArgs`, `WriteTransactionRequest`, `HelpfulIterator`, `ToastController`, `EncryptOptions`, `QuestWithMetadata`, `TagnameValue`, `OrganizationPolicyType`, `UsersDetailPage`, `CopyrightInfo`, `MarkSpecOverride`, `Home`, `WorkItemService`, `UntypedProductSet`, `DecodeInfo`, `Natural`, `IProduct`, `IExperiment`, `TargetResponderRecipe`, `Primary`, `IFluidDataStoreFactory`, `React.ComponentProps`, `ResultWithType`, `ObservableApplicationContextFactory`, `MergeDomainsFn`, `TypedPropertyDescriptor`, `ConfigurationScope`, `SceneBinObj`, `AccountAssetDTO`, `IUserModelData`, `JsonObjectProperty`, `HttpAdapterHost`, `AdaptServer`, `WalletBalance`, `requests.ListModelDeploymentsRequest`, `CustomField`, `SettlementEncoder`, `TileProps`, `loader.LoaderContext`, `AxisSpec`, `AxisLabel`, `CosmosClient`, `MultiPickerOption`, `WidgetOptions`, `Then`, `ModifyEventSubscriptionMessage`, `IORedisInstrumentationConfig`, `SceneManager`, `PearlDiverSearchStates`, `BitmapData`, `Body`, `ReboostInstance`, `MDL0Renderer`, `U8.U8Archive`, `ChatParticipant`, `ActionProps`, `chokidar.FSWatcher`, `TupletNumber`, `UsageCollector`, `android.graphics.Typeface`, `FlexProps`, `BufferUseEnum`, `ClippedPolyfaceBuilders`, `AnchoredOperationModel`, `FeeLevel.Medium`, `QuerySuggestion`, `RepositoryData`, `ConfigChecker`, `MappedSetting`, `pxtc.CallInfo`, `DocParagraph`, `PreferenceScope`, `SnapshotDb`, `BuilderRun`, `NextHandleFunction`, `ParsedLog`, `Num`, `SavedObjectMigrationFn`, `RetryHandler`, `ReduceOptions`, `Layer`, `NavigationState`, `GuildService`, `StepRecoveryObject`, `CardService`, `ActionWithPayload`, `CheckBox`, `ProxyValue`, `PostComment`, `TileState`, `STPPaymentIntent`, `WorldReader`, `FramePublicAPI`, `ValidationEventTypes`, `ICompositionBody`, `GenericList`, `Repo`, `BatchedFunc`, `IDeployedApplicationHealthStateChunk`, `RepositoryEntity`, `JsonDocsComponent`, `tf.GradSaveFunc`, `MosaicPath`, `ChannelLeave`, `AnimatorState`, `HistoryStatus`, `ClassNode`, `NodeParser`, `MdcFormField`, `OrganizationEntity`, `PublishedStoreItem`, `d.CopyTask`, `IBuildStageContext`, `HttpError`, `child.ChildProcess`, `theia.Command`, `ITerminalOptions`, `DragEvent`, `BaseArrayClass`, `ParentSpanPluginArgs`, `ImportNameInfo`, `DeleteBucketPolicyCommandInput`, `ContractWrapper`, `PrettySubstitution`, `ManagedShortTermRetentionPolicyName`, `LevelGlobals`, `GalaxyMapIconStatus`, `EvaluateHandleFn`, `PermutationVector`, `ConfiguredPlugins`, `Declarations`, `NestedMap`, `MultiValue`, `PrismaConfig`, `NetworkId`, `FindArgs`, `AccountCustom_VarsEntry`, `ImageFov`, `StoreNames`, `VaultVersion`, `android.view.MotionEvent`, `ProtocolClient`, `ArrayConfig`, `BuildOutput`, `StateTimelineEvent`, `FormArray`, `NavigatedData`, `StripeShippingMethod`, `UpdateSettingModelPayload`, `Food`, `JSDocTypeLiteral`, `Imported`, `DeleteCertificateResponse`, `IStageConfigProps`, `FieldResultSetting`, `XPCOM.nsIURI`, `HalOptions`, `NoteModel`, `CalcAnimType`, `requests.ListShapesRequest`, `Sha256`, `UpdateJobCommandInput`, `SessionConfig`, `DraggableDirective`, `EdgeDisplayData`, `MergeBlock`, `ExecutionParams`, `Async`, `RequestCallback`, `GithubUser`, `AllowedKeyEntropyBits`, `CallableContext`, `EntityCollectionResolver`, `MaximizePVService`, `ImmutableStyleMap`, `TargetStr`, `SimpleChange`, `TextInsertion`, `DeviceSelection`, `SequenceConfiguration`, `LLRBNode`, `ISPRequestOptions`, `MenuType`, `ng.IScope`, `FeatureAppearance`, `GuidString`, `IScriptInfo`, `MaterialInstance`, `TheBasicMQStack`, `CkbMintRecord`, `LoginSuccess`, `ScriptObject`, `StoredCiphertext`, `EditorMode`, `Zip`, `SwitcherFields`, `PollingInterval`, `ListType`, `User`, `CheckAvailabilityProps`, `LookaroundAssertion`, `JsonTokenizer`, `FileDataSource`, `CallInfo`, `AxisLabelCircular`, `FbFormModelField`, `ComponentProperty`, `GetUpgradeStatusCommandInput`, `ExtendedAdapter`, `TxIn`, `RootStoreState`, `RadioValue`, `InstanceResult`, `STXPostCondition`, `TinymathAST`, `ParsedRange`, `MIRAssembly`, `Aspect`, `AdditionEdit`, `GroupParameters`, `PatternLayout`, `ConcreteComponent`, `IPropertyData`, `UpdateDeviceCommandInput`, `Concatenate`, `Second`, `JSX.HTMLAttributes`, `CustomHTMLElement`, `TPayload`, `DataTypeNoArgs`, `StorageHeader`, `DiagnosticCollection`, `ViewMode`, `ValidityState`, `FontData`, `VanessaTabItem`, `Observed`, `Registerable`, `GfxTextureDimension`, `CredentialOfferTemplate`, `HandlerCallback`, `RendererLike`, `EsDataTypeUnion`, `IStoreData`, `Rounding`, `Configuration`, `UpdatePackageCommandInput`, `WithBoolean`, `TT`, `StandardizedFilePath`, `ProtocolRunner`, `HotkeySetting`, `d.TransformOptions`, `EngineerSchema`, `StoryProps`, `UserLoginData`, `PointerDownOutsideEvent`, `OsdUrlTracker`, `MigrateCommand`, `CommandPayload`, `MenuItemProps`, `MyCompanyConfig`, `MIRFunctionParameter`, `HeaderGroup`, `AthenaRequestConfig`, `GraphQLResolverMap`, `IModalServiceInstance`, `PaymentsErrorCode`, `AuthError`, `CommandArg`, `Slots`, `AddressType`, `JKRCompressionType`, `StartDeploymentCommandInput`, `MainAccessResponse`, `CompositeType`, `BisenetV2CelebAMaskOperatipnParams`, `S3.GetObjectRequest`, `CoralContext`, `d.ListenOptions`, `GraphQLNonInputType`, `IExtensionMessage`, `InterfaceDefinitionBlock`, `ValueParserParams`, `ManagedID`, `RedBlackTreeIterator`, `WindowLike`, `TSESTree.ClassDeclaration`, `ParquetBuffer`, `TableBuilder`, `Ex`, `ITelemetryGenericEvent`, `ConventionalCommit`, `NetworkParams`, `RectF`, `Preparation`, `Apollo.Apollo`, `LanguageServiceExtension`, `ReportingEventLogger`, `MetaFunction`, `IOSNotificationPermissions`, `StructureTypeRaw`, `RewardTransactionList`, `RangeBucketAggDependencies`, `OtherNotation`, `Searchable`, `FormSection`, `MyObserver`, `IsBindingBehavior`, `DebugProtocol.SetVariableArguments`, `Enhancer`, `Transport`, `OrthogonalArgs`, `keyType`, `IUriMap`, `ButtonProps`, `TsExpansionPanelComponent`, `FnO`, `Models.WebHook`, `StartImportCommandInput`, `ReknownClient`, `Pbf`, `ChartLine`, `ConnectionState`, `TemplateTermDecl`, `Accessibility`, `GoalService`, `angular.ITimeoutService`, `IArrayType`, `AccessibilityKeyHandlers`, `MagicSDKWarning`, `SessionDataResource`, `NFT1155V2`, `NumericArray`, `requests.ListWhitelistsRequest`, `phase0.BeaconBlockHeader`, `WebViewMessageEvent`, `tf.Tensor5D`, `CachedType`, `OsmNode`, `CreateTransformer`, `SQLDatabase`, `StatusBarWidgetControl`, `IframeController`, `StoreCollection`, `SeriesMarkerRendererDataItem`, `ITenantSetting`, `BalmError`, `AllPlatforms`, `RailsFile`, `DataColumn`, `SpriteManager`, `CrudTestContext`, `Newline`, `GlobalConfiguration`, `SyslumennAuction`, `IFormatProvider`, `CompleteOption`, `SelectionSetToObject`, `WavyLine`, `ActivableKey`, `AbstractClass`, `Mouse`, `CloseEditor`, `ProgramProvider`, `VECTOR_STYLES`, `VerticalRenderRange`, `KeyIndexImpl`, `Dispatcher`, `E2EElement`, `AdminCacheData`, `MdcDialogRef`, `TypeSpec`, `DataCache`, `BBox`, `TargetConfig`, `vscode.OutputChannel`, `WhileStatement`, `TypeDBClusterOptions`, `AnyExpressionFunctionDefinition`, `BatchChangeSet`, `DockType`, `PushDownOperation`, `CacheVm`, `RepositoryInfo`, `Rgba`, `ISpec`, `IVersionedValueWithEpoch`, `TinaCMS`, `FormFieldErrorComponent`, `ServiceTemplate`, `StageName`, `ScriptParameter`, `TimeSpan`, `PickerOptions`, `YAMLNode`, `google.maps.Polygon`, `IAjaxSuccess`, `kind`, `ComponentPublicInstance`, `ParameterScope`, `Album`, `TestConfiguration`, `ActorContext`, `columnTypes`, `FileSystemFileHandle`, `ListComponent`, `ProgressReporter`, `BarLineChartBase`, `EngineWindow`, `Week`, `Bitmap`, `PokemonIdent`, `MinimongoDb`, `sdk.TranslationRecognitionCanceledEventArgs`, `RichLedgerRequest`, `VanessaGherkinProvider`, `BaseResourceHandlerRequest`, `ClientRemote`, `DaffAddressFactory`, `Parsed`, `StatusMessage`, `OutOfProcessStringReader`, `DragHelperTemplate`, `UriCommandHandler`, `DAL.KEY_5`, `AppStackMajorVersion`, `CategoryList`, `RendererFactory2`, `TradeDirection`, `IModdleElement`, `ExtHandler`, `DescribeNamespaceCommandInput`, `IFoundCursor`, `AutoInstrumentationOptions`, `ComponentCompilerLegacyContext`, `requests.ListDbSystemsRequest`, `FunctionOrConstructorTypeNode`, `PathHeadersMap`, `ComponentCompilerEvent`, `PieChartData`, `StageContentLayoutProps`, `InitializeHandlerOptions`, `CephLandmark`, `RosException`, `ts.NavigationTree`, `ListsSandbox`, `UpdateFileSystemCommandInput`, `RequestedCredentials`, `EventRequest`, `CommandService`, `AnimatorPlayState`, `IgetOpenRequests`, `EventResult`, `MediaRecorder`, `UrlSegment`, `JsDoc`, `TydomDeviceSecuritySystemData`, `Quality`, `ConfigParser`, `ManipulatorCallback`, `StringValueToken`, `TableDefinition`, `ConfirmDialogProps`, `SliceNode`, `ParseScope`, `ExecOpts`, `UniswapFixture`, `CheckFlags`, `ContactId`, `Json.ArrayValue`, `StyleRule`, `NodeRequest`, `TileIndex`, `SupClient.AssetSubscriber`, `StorageError`, `StepType`, `VariableNode`, `ConnectivityInfo`, `MessageFormatter`, `RNCookies`, `MdcTopAppBar`, `ProjectSettings`, `RxTranslation`, `DeleteProjectCommandOutput`, `Wire`, `ValidationVisOptionsProps`, `Enums`, `DelegateTransactionUnsigned`, `ActiveContext`, `FrameworkType`, `DebugConfigurationModel`, `MigrationDefinition`, `ISnapshotTreeWithBlobContents`, `GetInsightsCommandInput`, `KeyFunction`, `BlockTag`, `PermissionOverwriteResolvable`, `TypeMatcher`, `ApiDefService`, `MarginPoolInstance`, `DataViewBase`, `RelativePosition`, `IntentSummary`, `RendererContext`, `WordType`, `GLboolean`, `Serials`, `HintItem`, `requests.ListComputeImageCapabilitySchemasRequest`, `TransitionAnimation`, `BrowserError`, `ThunkArg`, `RepeatVector`, `IParserState`, `GuildMessage`, `GetThunkAPI`, `IPageContainer`, `TinaCloudCollection`, `DynamoDbDataSource`, `MapFn`, `PiEditUnit`, `ArrayType`, `ForkTsCheckerWebpackPluginState`, `ServiceWorker`, `FlattenContext`, `Opts`, `MethodGetRemainingTime`, `messages.SourceReference`, `Completion.Item`, `msRest.OperationURLParameter`, `StatsError`, `RPCMethodDescriptor`, `child_process.SpawnOptions`, `ZWaveLogInfo`, `BaseAuthState`, `FocusTrapFactory`, `WorkArea`, `XRView`, `IpcMainListener`, `ShippingAddress`, `BagOfCurves`, `VariableValueTypes`, `SourceBufferKey`, `FrameControlFactory`, `StubStats`, `ADialog`, `PersistenceProvider`, `ReferencedFields`, `FieldsAndMethodForPositionBeforeCurrentStrategy`, `RoomEntity`, `VectorPosition`, `AppElement`, `DSL`, `UpdateRegexPatternSetCommandInput`, `HTMLFrameElement`, `ICellRenderer`, `JestPlaywrightConfig`, `EditText`, `MatBottomSheetRef`, `APIs`, `StreamReport`, `Column`, `RNSharedElementStyle`, `ListGatewaysCommandInput`, `InspectionTimeRange`, `ObservableQueryBalanceInner`, `IconShapeTuple`, `RawRule`, `RobotApiResponse`, `LoggingConfiguration`, `TaskInfo`, `GX.PostTexGenMatrix`, `NotifyMessageType`, `CommandOption`, `CdsControl`, `HelloService`, `TSReturn`, `SiteInfo`, `CustomSmtpService`, `AggParamsItem`, `RecursiveArray`, `IHook`, `AssociateServiceRoleToAccountCommandInput`, `PayloadHandler`, `SwUrlService`, `RegularPacket`, `Templates`, `NodeJS.ReadWriteStream`, `IGlTFModel`, `JwtAdapter`, `ParseResponse`, `ProjectIdAndToken`, `SExpr`, `PainterElement`, `UseHydrateCacheOptions`, `EntityModel`, `Listener`, `DirectiveArgs`, `GlobalStoreDict`, `MatchPresenceEvent`, `MeshPrimitive`, `NexusObjectTypeDef`, `DeferredNode`, `AdminProps`, `IColumnDesc`, `IResolveDeclarationReferenceResult`, `ITouchEvent`, `ImageMapperProps`, `TRPCResult`, `requests.ListManagementAgentsRequest`, `OrderedStringSet`, `GraphInputs`, `CacheIndex`, `EntryHashB64`, `WatchStopHandle`, `IResizedProps`, `SimpleBBox`, `ODataParameterParser`, `RepositoryChangeEvent`, `RNode`, `BaseMemory`, `IFileSnapshot`, `AlarmAction`, `SelectableObject`, `SceneGfx`, `DynamicFormArrayGroupModel`, `JobDetails`, `u64spill`, `S.State`, `TemplateRef`, `PeerTreeItem`, `TalkOpenChannel`, `ImportDefaultSpecifier`, `Encounter`, `messages.DocString`, `GDQLowerthirdNameplateElement`, `RebaseConflictState`, `RepositoriesStore`, `RollupConfig`, `Mocks`, `ImageDecoder`, `StreamInfo`, `SitemapXmpResults`, `NodeKey`, `IAppStore`, `Signals`, `RouteModules`, `ExpNumSymbol`, `RepoSnapshot`, `SCN0_AmbLight`, `CacheTransaction`, `Suggestions`, `IOrganizationDocument`, `CurrentUserService`, `Geography`, `NotificationAction`, `ModelDeploymentType`, `ServerConnection.ISettings`, `StringLookup`, `GameBits`, `express.Express`, `WaitForScript`, `GetNamespaceResponse`, `ContainerInspectInfo`, `CounterState`, `StateDefinition`, `WebApi`, `DefaultFilterEnum`, `P2SVpnGateway`, `BucketAggType`, `ITimelineModel`, `MeshPhysicalMaterial`, `DatabaseVulnerabilityAssessment`, `EntityT`, `LinkedService`, `Requirement`, `ICSR`, `SoftVis3dShape`, `DiceRollerPlugin`, `SSHConfig`, `number`, `Hapi.ResponseToolkit`, `NgxDateFnsDateAdapter`, `PeekZFrame`, `d.ExternalStyleCompiler`, `SlotFilter`, `ReadContext`, `OAuthConfigType`, `ApplicationWindow`, `ExportSummary`, `TestNodeProvider`, `EntityRepository`, `BottomTabBarProps`, `MediaDevices`, `TextDocumentShowOptions`, `ToolbarProps`, `Base16Theme`, `LocalMicroEnvironment`, `AppBarProps`, `ComponentState`, `ODataQueryOptionsHandler`, `ts.FormatCodeSettings`, `schema.Specification`, `ObjectSelectionListState`, `WalletConnectConnector`, `IUsageMap`, `CutLoop`, `CardData`, `TransposedArray`, `TaskScheduling`, `DecoratedComponentClass`, `CreateModelResponse`, `IParameterValuesSourceProvider`, `E2EScanScenarioDefinition`, `WalletEntry`, `TypeEquality`, `InMemoryOverlayUrlLoader`, `ModuleStoreSettings`, `SFCDeclProps`, `BridgingPeerConnection`, `DeleteRepositoryCommand`, `CipherImportContext`, `ScoreService`, `ColumnId`, `CssItem`, `RestClient`, `StoryFn`, `d.ComponentOptions`, `StatBuff`, `TaskLogger`, `IQueryParamsResult`, `LiskErrorObject`, `google.maps.LatLng`, `Highcharts.DataGroupingApproximationsArray`, `MatchPathAsyncCallback`, `ITargetGroup`, `SandDance.VegaDeckGl.types.LumaBase`, `ScreenContextData`, `WebappClient`, `ImageObject`, `ModifyEventSubscriptionCommandInput`, `IRenderTask`, `CalculationYear`, `UpdateQuery`, `MicrosoftSynapseWorkspacesResources`, `ProposeCredentialMessage`, `UnregisterCallback`, `IModifierKeys`, `Parser.Infallible`, `BTCAccountPath`, `RouteAnimationType`, `CommanderOptionParams`, `TimeOffRequest`, `GameOptions`, `TerminalWidget`, `Submission`, `CSSSelector`, `LaxString`, `TranslationEntry`, `requests.ListBackupDestinationRequest`, `NodeEntry`, `HttpResponseOK`, `DownloadService`, `SpringConfig`, `ThunkDispatch`, `RPCMessage`, `TokenType`, `AlertMessage`, `MediaConfig`, `td.SMap`, `ExpressionModel`, `IAheadBehind`, `LoggerProvider`, `CPU`, `ClassExpression`, `EntityContainer`, `ws`, `DeleteSiteCommandInput`, `DialogComponent`, `ProfileServiceProxy`, `FilesystemNode`, `Couple`, `GeoJSON.Feature`, `CreateProgram`, `TFJSBinding`, `requests.ListExternalPluggableDatabasesRequest`, `RawPermissionOverwriteData`, `VarExpr`, `TableBatchSerialization`, `JsonWebKey`, `LVal`, `AnyArray`, `EventListenerOptions`, `JSXIdentifier`, `ErrorSubscriptionEvent`, `MessageTarget`, `lua_State`, `DesktopCapturerSources`, `ParsedConfirmedTransaction`, `winston.Logger`, `TrackParseInfo`, `DataProperty`, `NumOrString`, `ActivityInterface`, `ast.BinaryNode`, `HierarchyRpcRequestOptions`, `Concat`, `CreatePolicyVersionCommandInput`, `Day`, `CrochetRelation`, `VertexFormat`, `Elements.RichTextElement`, `ContextMenuItem`, `ts.FunctionExpression`, `NotificationSettings`, `Models.Exchange`, `IHistoryFileProperties`, `Notified`, `ExportedDeclarations`, `RenderableElement`, `FullIndexInfo`, `CallbackT`, `UsageStats`, `ExtraSessionInfoOptions`, `EntityConstructor`, `ChildInfo`, `JsonType`, `MgtFileUploadItem`, `Pager`, `NVMEntry`, `TransformStream`, `DistrictsGeoJSON`, `ReflectiveKey`, `Writeable`, `CourseType`, `HydrateStyleElement`, `GetPolicyRequest`, `CkElementContainer`, `TestInterface`, `ITaskSource`, `IStatusFile`, `AuditEvent`, `RecordingOptions`, `core.BTCInputScriptType`, `Events.postdebugdraw`, `SuperClient`, `MongooseModel`, `GradSaveFunc`, `SchemePermissions`, `LibResolver`, `ExploreOptions`, `RPCDescriptor`, `MatBottomSheetConfig`, `MockDialogRef`, `ObjectStorageClient`, `ERC20Mock`, `TwistyPlayerModel`, `Gender`, `SchemaDef`, `Cartesian3`, `SessionGetter`, `WsConnectionState`, `GitFileStatus`, `LineAnnotationStyle`, `CBPeripheral`, `VisualObjectInstanceEnumeration`, `ChartModel`, `ProxyServerType`, `ng.ILocationService`, `ShipBlock`, `DDL2.OutputDict`, `CreateRequestBuilder`, `PathAddress`, `IAvatarProps`, `ChannelData`, `CityPickerColumn`, `DeletedAppRestoreRequest`, `AngularFireAuth`, `LocalStorageService`, `OpenYoloCredentialRequestOptions`, `FilesState`, `BuildrootAction`, `HttpsFunction`, `ICore`, `ScatterSeries`, `ReuseItem`, `React.ChangeEventHandler`, `Cookies`, `ServiceControlPolicyResource`, `GitPullRequestWithStatuses`, `BatchNormalizationLayerArgs`, `IStashTab`, `CryptoFactory`, `PartyMatchmakerAdd_NumericPropertiesEntry`, `IAutoEntityService`, `SQS`, `ObjectMap`, `SliderBase`, `Servers`, `ITestStep`, `RobotHost`, `GlobalCredentials`, `WasmQueryData`, `GetPermissionPolicyCommandInput`, `ErrorSubscriptionFn`, `BotonicEvent`, `ICategoryCollection`, `OpenSearchDashboardsReactContext`, `MoonbeamDatasource`, `ActionTicketParams`, `RE6Module`, `FieldNode`, `HttpMetadata`, `Fig.Spec`, `net.Socket`, `ExpressionRenderError`, `iElementInfo`, `TStyleSheet`, `UpdateAppInstanceUserCommandInput`, `PyrightPublicSymbolReport`, `MetadataArgsStorage`, `RawMetricReport`, `AsyncSink`, `UiActionsService`, `ViewProps`, `ethers.providers.BlockTag`, `TableSearchRequest`, `Inspector`, `LogsConfig`, `ScaleBand`, `UrlFormat`, `ArenaAllocationResult`, `QCfg`, `SlideDefinition`, `ParserMessageStream`, `EditionId`, `TreeState`, `ModalDialogParams`, `WebpackConfig`, `IFilterTarget`, `SeedOnlyInitializerArgs`, `SvgItem`, `HardhatRuntimeEnvironment`, `P2PMessagePacket`, `BodyProps`, `a.Expr`, `LogWriteContext`, `Spine`, `WildcardProperty`, `Quill`, `IAddresses`, `LocalTitle`, `ListJobRunsCommandInput`, `HIRNode`, `BreadcrumbsProps`, `FabRequestResponder`, `Procedure`, `PoolClient`, `DaffCartStorageService`, `IHttpClientResponse`, `TemplateArguments`, `SecurityDataType`, `WebPhoneSIPTransport`, `DeleteRequestBuilder`, `Hunspell`, `PageContext`, `ColorPoint`, `PagesLoaded`, `SideType`, `MessageStateWithData`, `IBankAccount`, `FeedFilterFunction`, `ParsedAccountBase`, `AnimGroup_TexMtx`, `ListDatasetEntriesCommandInput`, `SakuliCoreProperties`, `QState`, `ObjectOf`, `ResizeChecker`, `ConfigParameters`, `K3dClusterNodeInfo`, `EnvironmentResource`, `SelectToolConfig`, `$T`, `d.PrerenderUrlResults`, `AvailableProjectConfig`, `S3`, `LayoutService`, `PlanPriceSpecManager`, `ReputationToken`, `IZoweUSSTreeNode`, `Twit`, `RefList`, `HTTPNetworkInterface`, `PolicyResponse`, `GcListener`, `PvsDefinition`, `nsIURI`, `SignedOrder`, `ConeRightSide`, `NamespaceGetter`, `BlenderPathData`, `NormalizedReadResult`, `PushPathResult`, `ReadModelInterop`, `ELanguageType`, `FullDir`, `GeometryData`, `BlockchainWalletExplorerProvider`, `POCJson`, `NonMaxSuppressionResult`, `GraphQLFieldConfig`, `SessionTypes.RequestEvent`, `SavedObjectAttributes`, `CronExpression`, `forceBridgeRole`, `TestExplorer`, `MiddlewareMap`, `LodopResult`, `MultiValueProps`, `ScmFileChangeNode`, `DominoElement`, `ShareStore`, `FileList`, `ModelDispatcher`, `MockComponent`, `BrowserFields`, `EquipmentService`, `OpenApiApi`, `ControllerClass`, `EdgeGeometry`, `GlitzClient`, `CommonLayoutParams`, `ClientData`, `ErrorAction`, `AdditionalProps`, `PermissionsService`, `Cartographic`, `ContinueResponse`, `GeoLevelInfo`, `ChatErrors`, `PartialLax`, `unitOfTime.Base`, `DescribeAppInstanceUserCommandInput`, `Port`, `TabElement`, `AnimationComponent`, `JoinPredicate`, `IBucketAggConfig`, `StorageIdentifier`, `PackageRelativeUrl`, `PrivateUserView`, `Comparator`, `Gate`, `CartoonOperatipnParams`, `This`, `BucketSegment`, `StripeSetupIntent`, `Types.IResolver`, `LspDocuments`, `RobotApiErrorResponse`, `SymbolicTensor`, `ContinuousParameterRange`, `TwingNodeExpression`, `IssuerPublicKeyList`, `SentInfo`, `t.IfStatement`, `ProjectInterface`, `CommonInterfaces.Plugins.IPlugin`, `RendererOptions`, `AsyncStateNavigator`, `ICurrentArmy`, `Ticket`, `ViewDefinitionProps`, `UnixTerminal`, `ProsodyFilePaths`, `GetRuleGroupCommandInput`, `SetModel`, `GeneratedQuote`, `NodeSDK`, `ToastRequest`, `FetcherField`, `ScaleOrdinal`, `IProjectInfo`, `ColorOverrides`, `IInterpreterRenderHandlers`, `FieldEntity`, `nockFunction`, `ISettingStorageModel`, `FeederPool`, `VirtualScope`, `FileResource`, `JulianDay`, `GitCommittedFile`, `IThrottler`, `reminderInterface`, `Animated.Animated`, `IBazelCommandAdapter`, `GameEvent`, `E`, `Environments`, `Printable`, `CompaniesService`, `NativeSyntheticEvent`, `NavigationNavigator`, `KeccakHash`, `ApplicationTypeGroup`, `MergeableDeclarationSet`, `DeleteAppCommandInput`, `requests.ListInstanceAgentPluginsRequest`, `TxMassMigration`, `NotificationProperty`, `SocketConnection`, `StdFunc`, `Tagging`, `TileMetadataArgs`, `ValidationProblemSeverity`, `IView`, `LoadBalancerListenerContextProviderPlugin`, `SnippetString`, `FilterOperator`, `EdmT`, `DeleteUserCommandInput`, `UseTransactionQueryOptions`, `RangeRequest`, `VersionEdit`, `StyletronComponent`, `BorderRadiusDirectional`, `reduxLib.IState`, `PropItem`, `LambdaServer`, `GenericIndexPatternColumn`, `DescribeFargateProfileCommandInput`, `CanvasTypeHierarchy`, `HTMLVideoElement`, `Fillers`, `W6`, `FundingCycleMetadata`, `IRawLoadMetricReport`, `NetworkName`, `Stereo`, `StreamOptions`, `TagSpec`, `VisitOptions`, `WithExtendsMethod`, `StringBuilder`, `EntContract`, `ScrollerAnimator`, `SObjectDescribe`, `OAuthCredential`, `TagValue`, `Sha512`, `FixedDepositsService`, `NormMap`, `AnalyticsModule`, `ShowConflictsStep`, `Matrix3x3`, `GravityArgs`, `FeatureProps`, `MIRPrimitiveListEntityTypeDecl`, `ModelCompileArgs`, `MongoQueryModel`, `FeeRate`, `Conversation`, `EsAssetReference`, `AllowArray`, `PingPayload`, `Alignment`, `IProc`, `PermissionsCheckOptions`, `CreateHotToastRef`, `TRANSFORM_STEP`, `VariantGeometry`, `LegendOptions`, `IAsyncEqualityComparer`, `RouteValidationResultFactory`, `Node3D`, `ContractsState`, `requests.ListAutonomousDatabasesRequest`, `UserThemeEntity`, `ILectureModel`, `Pattern`, `ColumnConfig`, `RBXScriptConnection`, `HelmRelease`, `interfaces.BindingWhenOnSyntax`, `MatchedFlow`, `GetDomainNameCommandInput`, `HandlerNS.Event`, `HTMLAttribute`, `FacetsState`, `QUnitAssert`, `IFollow`, `LazyCmpLoadedEvent`, `EditValidationResult`, `ScriptingLanguage`, `WriteLock`, `LegacyCallAPIOptions`, `Babel`, `Blip`, `ValueMetadata`, `iTunesMusicMetaProvider`, `PersonEntity`, `MdxListItem`, `RuleFunctionMeta`, `ng.ui.IStateProvider`, `Assembly`, `MessagesService`, `VcsItemConfig`, `TTK1`, `MemberRepository`, `MaxAge`, `ModuleBuilderFileInfo`, `TransactionVersion.Mainnet`, `TModule`, `TypeScriptVersion`, `ExpressionAstFunctionBuilder`, `Spherical`, `restm.IRestResponse`, `RawRuleset`, `PublicApi`, `FileBrowserItem`, `SimulcastUplinkObserver`, `SafeVersion`, `Locale`, `d.HttpRequest`, `GX.CompCnt`, `MediaStreamOptions`, `LspDocument`, `TranslationGroup`, `GraphicContentProps`, `ConsolidatedCertificateRequest`, `ISortOptions`, `LoggingConfig`, `IStrokeHandler`, `Dummy`, `AudioRule`, `VorlonMessage`, `ISocketBase`, `FrontCardsForArticleCount`, `RedisCache`, `d.JsonDocsProp`, `Col`, `SeparatedNamedTypes`, `interfaces.Binding`, `DAL.DEVICE_ID_COMPASS`, `NSDateComponents`, `ChangeListener`, `IStatusButtonStyleProps`, `WebAccount`, `OfAsyncIterable`, `TransactionSegWit`, `TestKafka`, `LeftRegistComponentMapItem`, `ExprListContext`, `UserInfoResource`, `WrappedWebSocket`, `TreeModel`, `TableComponentProps`, `IMusicMeta`, `types.signTx`, `DispatchOptions`, `TabularSource`, `admin.firestore.DocumentSnapshot`, `IGradient`, `PlanSummaryData`, `SYMBOL`, `TEObject`, `VideoModes`, `EFood.Session`, `IConnect`, `SkeletonHeaderProps`, `GraphqlApi`, `FilterTrailersStatusValues`, `SwaggerPathParameter`, `ts.Program`, `Options.Publish`, `ComponentMetaData`, `IDriverInfo`, `OsmRelation`, `JSEDINotation`, `CallCompositeStrings`, `Substitution`, `JsonAPI`, `BotMiddleware`, `CharacterSet`, `ExpressRequestAdapter`, `ObserveForStatus`, `WebSiteManagementModels.Site`, `AttributeParser`, `PluginDefinition`, `NamedFluidDataStoreRegistryEntries`, `CustomSkillBuilder`, `FilmQueryListWrapper`, `PermissionConstraints`, `MatTableDataSource`, `DeleteJobResponse`, `Flags`, `Floating`, `SnapshotAction`, `FilterEvent`, `ITileDecoder`, `ResolvedConfigFileName`, `LightSet`, `GitStatusFile`, `NumberValueSet`, `HipiePipeline`, `PrintStackResult`, `IBuildConfig`, `AttestationsWrapper`, `ma.TaskLibAnswers`, `TreeGridTick`, `EventInterpreter`, `IBoxSizing`, `RendererElement`, `ToastType`, `FutureWalletStore`, `AnyResource`, `CubicBezierAnimationCurve`, `angular.auto.IInjectorService`, `L2Args`, `InvocationContext`, `UserConfigDefaults`, `ArDriveAnonymous`, `WebsiteScanResultProvider`, `HostString`, `TestSandbox`, `MsgPieces`, `GetReviewerStatisticsPayload`, `ExprEvaluatorContext`, `TmdbMovieResult`, `HttpResponseRedirect`, `LeakDetectionSignal`, `FloatingLabel`, `d.FsReaddirOptions`, `PropertyResolveResult`, `MatcherGenerator`, `DashboardProps`, `IFileModel`, `SwipeActionsEventData`, `CommerceTypes.CurrencyValue`, `UpdateDestinationCommandInput`, `ComponentReference`, `AmqpConnection`, `YearCell`, `FirmwareUpgradeIpcResponse`, `IMenuItem`, `ProcessInfo`, `Label`, `TimeoutRacer`, `RumSessionManager`, `StartRecordingRequest`, `MutableSourceCode`, `ListConfigurationSetsCommandInput`, `BaseSkillBuilder`, `IChannelsDatabase`, `DocumentSpan`, `OverlapRect`, `KanbanRecord`, `Name`, `CartesianTickItem`, `PassNode`, `ApplicationService`, `LegacyTxData`, `DataFrameAnalyticsStats`, `GenericNotificationHandler`, `Dependency1`, `SerializedStyles`, `BuildrootUpdateType`, `Icu`, `alt.Player`, `IRegisterNode`, `ClipShape`, `ExecutionOptions`, `Endpoints`, `IBuildTaskPlugin`, `SignShare`, `Path2D`, `Electron.BrowserWindowConstructorOptions`, `BuilderOptions`, `BasicColumn`, `OmitInternalProps`, `NavigatorOptions`, `IsWith`, `IWmPicture`, `PowerAssertRecorder`, `Callbacks`, `HapiHeaders`, `AppStateType`, `SRule`, `ContextMenuProps`, `InstallForgeOptions`, `IUserPP`, `AnalyticsConfig`, `TemplateProviderBase`, `AssociationValue`, `azure.Context`, `Vector4`, `ColorType`, `PaymentResponse`, `ZipLocalFileHeader`, `btVector3Array`, `PatchFunction`, `EventSystemFlags`, `SummaryCalculator`, `IChannelAttributes`, `NotificationsStart`, `ResponsiveProp`, `MenuID`, `SpaceBonus`, `LitElement`, `ProviderPosition`, `ParseAnalysis`, `ObjectFieldNode`, `BotSpace`, `MDL0`, `CreateReplicationConfigurationTemplateCommandInput`, `Captcha`, `CreateIPSetCommandInput`, `SolcOutput`, `CurveChain`, `NotificationPermission`, `TestSink`, `OptionalObject`, `ThemeCoreColors`, `ContextWithFeedback`, `ArrayWrapper`, `InternalSession`, `URLQuery`, `SidebarProps`, `BackgroundFilterSpec`, `DebugProtocol.LaunchResponse`, `LocatorExtended`, `MDCChipCssClasses`, `AttrParamMapper`, `PuppetCacheContactPayload`, `BlockchainExplorerProvider`, `ExpressionsCompilerStub`, `DBOp`, `Tensor6D`, `AttributePub`, `CodeActionsOnSave`, `PerformanceObserverEntryList`, `IError`, `React.UIEvent`, `videoInfo`, `TaskProps`, `BotAction`, `SavedObjectsResolveResponse`, `ObjectSchemaProperty`, `ITodoState`, `SerializableValue`, `IStateCallback`, `CodePointPredicate`, `IotRequestsService`, `InputToken`, `IdentityClient`, `ISnippetInternal`, `JPABaseParticle`, `MediaPlaylist`, `UniqueSelectionDispatcherListener`, `IMainClassOption`, `Watermark`, `IVideoService`, `InMemoryProject`, `RegionLocator`, `DynamoDB.PutItemInput`, `UsersController`, `InsertEvent`, `Metadata_Add_Options`, `SubSymbol`, `ShapePath`, `EventCategory`, `CacheStorageKey`, `ITestScript`, `Creator`, `DocumentChangeAction`, `cg.Color`, `OrderForm`, `ArgumentsCamelCase`, `PanelLayout`, `WebGLComponent`, `tfconv.GraphModel`, `IScreenInstance`, `SerialBuffer`, `Vp8RtpPayload`, `AbstractToolbarProps`, `ProtocolMapperRepresentation`, `HdEthereumPayments`, `SortableEdge`, `DAL.DEVICE_OK`, `CodebuildMetricChange`, `GfxAttachmentP_WebGPU`, `MonoTypeOperatorAsyncFunction`, `ZoneModel`, `PA`, `AttendeeModel`, `SitecorePageProps`, `MiddlewareArray`, `IdentityView`, `SKLayer`, `TransformProps`, `LoggerText`, `OptionEntry`, `FN`, `QueryEngineBatchRequest`, `GrpcConnection`, `OptionService`, `OptionalKind`, `DBDoc`, `BuildConditionals`, `BatchRequestSerializationOptions`, `SavedObjectsRemoveReferencesToOptions`, `XHRResponse`, `ExpressionOperand`, `IBufferView`, `ReCaptchaInstance`, `TSDNPromise.Reject`, `ListingNodeRow`, `OptionsNameMap`, `ClientMetricReport`, `MDCChipActionFocusBehavior`, `DAL.DEVICE_ID_MSC`, `NestedRoutes`, `TestLedgerChannel`, `OAuthClient`, `GetItemFn`, `FileCodeEdits`, `ModuleInstanceState`, `ManifestMetaData`, `FunctionalComponent`, `OperationURLParameter`, `AlternatingCCTreeNode`, `ApolloResponse`, `DateFnsConfigurationService`, `IDiagram`, `ListImagesResponse`, `TestContextData`, `EmitFiles`, `IWebPartContext`, `SuiteThemeColors`, `IAttrValue`, `FlattenedXmlMapWithXmlNameCommandInput`, `ANodeStm`, `ContractReceipt`, `ModeName`, `ResourceDetails`, `ElementAnalysis`, `IProtoNode`, `Factory`, `LayerRecord`, `TLE.StringValue`, `Symbol`, `TfCommand`, `BufferWriter`, `StackNavigationProp`, `XPCOM.nsIChannel`, `DataTexture`, `lsp.Position`, `Cheerio`, `ITransform`, `ThematicDisplayProps`, `RequestForm`, `ListTagsForResourceOutput`, `GroupTypeUI`, `requests.ListRunsRequest`, `ITEM_TYPE`, `IRGBA`, `IModuleMinificationResult`, `ListGroupUsersRequest`, `FacetOption`, `SecondaryIndexLayout`, `VpcTopologyDescription`, `ResourceState`, `RedisCommandArguments`, `L`, `AuthGuard`, `CustomBinding`, `NoelEvent`, `WebpackError`, `CallClient`, `ILoggedProxyService`, `InstanceContainer`, `Ping`, `FileSystemProviderWithOpenReadWriteCloseCapability`, `Arg`, `Model`, `MonacoEditor`, `$p_Declaration`, `ReferenceMonthRange`, `ScaleModel`, `Settings`, `CredOffer`, `requests.ListAutonomousDatabaseDataguardAssociationsRequest`, `TabContainerPanelComponent`, `PageObject`, `Map4d`, `IncrementalNodeArray`, `StoreResource`, `FactionMember`, `TableCellPosition`, `requests.ListDomainsRequest`, `SourceService`, `ParsedSource`, `CollatedWriter`, `FormAzureStorageMounts`, `FreeBalanceState`, `GraphicStyles`, `TestHotObservable`, `ReportId`, `Sash`, `StructuredError`, `HardwareModules`, `EventInput`, `WorkRequest`, `MeshNormalMaterial`, `GX.BlendFactor`, `ListDomainsCommandOutput`, `Money`, `MessageBuilder`, `PrismScope`, `MdcRipple`, `AsyncResult`, `TransformOption`, `CallProviderProps`, `PackageName`, `OriginalDocumentUrl`, `ThyResizeEvent`, `StorageAccount`, `SearchUsageCollector`, `IDatabaseConfigOptions`, `TriumphCollectibleNode`, `TspanWithTextStyle`, `Layout`, `UseCase`, `AssertionLocals`, `Binary`, `Extract`, `grpc.ServiceError`, `SelectableTreeNode`, `YVoice`, `OperationTypes`, `nsIDOMWindowUtils`, `HttpCode`, `CommandLineTool`, `SessionImpl`, `BooleanCB`, `LightingFudgeParams`, `ItemBuilder`, `ICrop`, `Categories`, `models.RegEx`, `SetbackState`, `SymbolType`, `Datatype`, `PursuitRow`, `FileDescriptorProto`, `FSNoteStorage`, `InversifyExpressServer`, `PngPong`, `DeleteUserCommandOutput`, `DateAxis`, `UnaryOpNode`, `ResolveablePayport`, `viewEngine_ViewRef`, `IAccountInfo`, `ESLSelectOption`, `PatchFile`, `CustomImage`, `Resolve`, `TreeWalker`, `ParserInfo`, `QuestionCollection`, `StackActionType`, `NavigableHashNode`, `CloseButtonProps`, `ScriptObjectField`, `IModelRpcProps`, `CreateImportJobCommandInput`, `CountArguments`, `AppStoreModel`, `IApplication`, `CustomContext`, `PreviewSettings`, `Pagination`, `CronOptions`, `Shelf`, `LGraph`, `VcsAccount`, `SuccessAction`, `IFieldMap`, `Id`, `DescribeDatasetCommand`, `PhoneNumber`, `SagaActionTypes`, `AlertService`, `ModList`, `SmartHomeHandler`, `SCNVector3`, `VirtualApplication`, `StorageInterface`, `redis.ClientOpts`, `RemoteParticipant`, `ByteString`, `ParsedTestObject`, `IAdministrationItemRoute`, `ConfigSchema`, `IHotspotIndex`, `TestNodeList`, `RepositoryService`, `HierarchyProvider`, `CodeUnderliner`, `ConstRecord`, `ProposalManifest`, `ExtractGroupValue`, `ActionsRecord`, `DocsTargetSpec`, `OpenerOptions`, `Math.Vector3`, `MediationStateChangedEvent`, `BrowserRequest`, `IDetailsProps`, `web3.Connection`, `ChainID`, `Injectable`, `DecodedLog`, `AllowedLanguage`, `IParagraphMarker`, `DescribeClustersRequest`, `WaitTaskOptions`, `Links`, `NullableSafeElForM`, `PopoverProps`, `Fail`, `SplitDirection`, `VideoDeviceInfo`, `SpyObject`, `SubgraphDataContextType`, `BlobStore`, `TitleService`, `BoneSlot`, `ParsedUtil`, `Lumber`, `SweetAlertOptions`, `ApiOptions`, `PrintExpressionFlags`, `Region`, `WaitTask`, `ProdoPlugin`, `Autocomplete`, `Matcher`, `InputStep`, `BSPRenderer`, `TestApp`, `GeneratedKeyName`, `IResponse`, `AccentIconStyles`, `OptionValue`, `ListClustersCommandInput`, `InputTextNode`, `ChainableHost`, `Replay`, `AnalysisCompleteCallback`, `UpdateOneInputType`, `FormInputs`, `SocketService`, `Margins`, `CreateAccountCommandInput`, `TThis`, `func`, `LocalTag`, `HTMLIonBackdropElement`, `DeleteNetworkProfileCommandInput`, `BrowserFetcher`, `ServerIO`, `InstallationQuery`, `MpegFrameHeader`, `EnabledFeatures`, `requests.ListMaintenanceRunsRequest`, `JSDocNonNullableType`, `PaneProperty`, `WithCSSVar`, `IBytes`, `ParsedOrderEventLog`, `IPriceDataSource`, `TaggedTemplateExpression`, `RenderFlag`, `IconBaseProps`, `CCAPI`, `_IIndex`, `CampaignTimelineChanelsModel`, `ToneAudioBuffer`, `MemberType`, `indexedStore.FetchResult`, `TextureManager`, `Lib`, `ApplicationOpts`, `CategoryTranslation`, `SendResponse`, `MemoryRenderer`, `NotificationAndroid`, `CannonBoxColliderShape`, `ContractBuilder`, `LockedDistricts`, `Segment`, `DiagnosticWithFix`, `Architecture`, `Objkt`, `HTTP_METHODS`, `Injection`, `DefaultEditorSize`, `Highcharts.Popup`, `LegacyRequest`, `HierarchyQuery`, `CollectionProp`, `AuthParams`, `AwsOrganizationReader`, `DaffCategoryFilterRangeNumericFactory`, `OrderByStep`, `_Code`, `LaunchEventData`, `ChangeSet`, `EditableNumberRangeFilter`, `MessageReceivedListener`, `IGameObject`, `TranslationItemBase`, `GroupParameterMethod`, `ColorAxis.Options`, `EmitType`, `EvaluatedChange`, `GasMode`, `SearchSequence`, `RouterCallback`, `ProposalActions`, `StraightCurved`, `org`, `ValidateFunction`, `LegendItemExtraValues`, `TRouter`, `ComponentCompilerListener`, `PromisedComputed`, `AudioStreamFormatImpl`, `Toolbar`, `JsonRpcProxy`, `TAttributes`, `IAzureNamingRules`, `AggConfig`, `SecurityGroupRule`, `ITrackInfo`, `RegistryInstance`, `PageElement`, `EqualContext`, `RepeatForRegion`, `AuthenticateFacebookRequest`, `t.VariableDeclaration`, `UserConfigExport`, `Euler`, `FILTERS.PHRASES`, `RigidBody`, `DialogSubProps`, `Model.LibraryStoreItemState`, `IPropertyWithName`, `LayoutNode`, `ElasticPool`, `ExecController`, `InferableAction`, `TileSet`, `ShContextMenuItemDirective`, `UserSchema`, `GoogleBooksService`, `EdgeImmutPlain`, `DummyNode`, `DateMarker`, `CompilerConfiguration`, `IRenderOptions`, `IAppProps`, `SettingsCallback`, `CreateAliasRequest`, `ErrorArgs`, `AnimationPlayer`, `BasicTemplateAstVisitor`, `AutoconnectState`, `SerializedObjectType`, `ConceptMap`, `PaginationNextKey`, `FolderNode`, `ObsConfiguration`, `ColorAxis`, `NodeLoadMetricInformation`, `CallbackManager`, `QueryBuilderFieldProps`, `TECall`, `Electron.Event`, `FinalInfo`, `Processes`, `ServiceDescriptorProto`, `MapMode`, `RPiComponentType`, `PoolFields`, `IHawkularRootScope`, `GetResponseBody`, `EventCallback`, `Transform2D`, `THREE.PerspectiveCamera`, `PartialResolvedVersion`, `Drone`, `api.ITree`, `LightInfo`, `FocusZoneDefinition`, `PortInfo`, `Bm.ComposeWindow`, `NavOptions`, `ShuftiproInitResult`, `IVectorLayer`, `Hill`, `ParsedDirectiveArgumentAndInputFieldMappings`, `ClipId`, `FallbackProvider`, `HoistState`, `ConnectedPosition`, `DialogflowApp`, `IAssignment`, `RouteEffect`, `TrackId`, `ScanCommandInput`, `requests.ListManagementAgentImagesRequest`, `ParameterSpec`, `DeleteAuthorizerCommandInput`, `IFileInfo`, `B10`, `PropertyChangedEventArgs`, `ReconfigResponseParam`, `ICellInfo`, `TempFile`, `MiddlewareArgs`, `InitConfiguration`, `ColorPresentation`, `CachedKey`, `HTMLIonTabElement`, `SvelteConfig`, `Thumb`, `ISerializedActionCall`, `WithStatement`, `EditorFile`, `ActorComponent`, `OpenChannelMessage`, `BrowserSimulation`, `IOdspResolvedUrl`, `DictionaryType`, `FieldTypes`, `ParseTreeListener`, `LocationObject`, `ast.SyntaxNode`, `RatingStyleProps`, `TestMethod`, `TexMap`, `Uni.Node`, `BaseParser`, `AppHelperService`, `TestController`, `PackageChangelogRenderInfo`, `DropdownItemProps`, `com.nativescript.material.bottomsheet.BottomSheetDialogFragment`, `TouchPulse`, `Survey.Survey`, `CachedPackage`, `CollidableCircle`, `ScrollToColumnFn`, `CornerSite`, `ReactMouseEvent`, `MetricId`, `chrome.runtime.MessageSender`, `IndexingRuleAttributes`, `ExtraInfoTemplateInput`, `Sharp`, `ThyDialogContainerComponent`, `MockRouteDefinition`, `IAnyStateTreeNode`, `ABLTableDefinition`, `RequestSession`, `MangoQuerySelector`, `SelectContext`, `ToLatexOptions`, `Screwdriver`, `TagResourceCommand`, `AnimationResult`, `DescribeStacksCommandInput`, `AuthAccessCallback`, `PluginDevice`, `ICourseDashboard`, `IImageryConfig`, `Adventure`, `MetricsService`, `ModuleOptions`, `IHelpCenter`, `GetUpgradeHistoryCommandInput`, `DevToolsExtension`, `RequestDto`, `HardhatConfig`, `GX.Command`, `SlateNode`, `DocfyService`, `AppInitialProps`, `CirclinePredicateSet`, `TransformListRow`, `GtRow`, `RawContract`, `SnapshotField`, `SignedAndChainedBlockType`, `GfxRenderDynamicUniformBuffer`, `ServeAndBuildChecker`, `RESTClient`, `RowGroup`, `ScopeSymbolInfo`, `MapAdapterUpdateEnv`, `SvelteSnapshotFragment`, `ZAR.ZAR`, `OperatorSpec`, `Road`, `WalkerStateParam`, `NodeMaterialConnectionPoint`, `FormErrorsService`, `ScaleCompression`, `NgModel`, `ValidationAcceptor`, `ContextTypes`, `BaseHeader`, `SyncEngine`, `FIRStorageReference`, `PresentationRpcResponse`, `CancelSignal`, `BinStructItem`, `LegacySocketMessage`, `ExpandedBema`, `S3MetricChange`, `TypeVarMapEntry`, `ISelectHandlerReturn`, `WebApiTeam`, `ISetItem`, `FrameItem`, `BrowsingPage`, `FileContext`, `AuthorizationErrorResponse`, `FormError`, `KeyValueStore`, `ColorStateList`, `TSTypeParameterDeclaration`, `IPair`, `TSBuffer`, `CollectionNode`, `MosaicDirection`, `GitLog`, `DaffCartShippingInformation`, `Rehearsal`, `requests.ListDynamicGroupsRequest`, `AzureParentTreeItem`, `ts.ArrowFunction`, `ServiceContainer`, `LinkType`, `UIComponent`, `PrimitiveSelection`, `Expiration`, `FirestoreSimple`, `ParenthesizedTypeNode`, `RateLimit`, `Icon`, `StackNode`, `MIRConstructableInternalEntityTypeDecl`, `ProductA`, `ServiceInstance`, `TestObservable`, `TemplateWithOptionsFactory`, `DvServiceFactory`, `MathExpression`, `OpenSearchDashboardsResponse`, `HistoriesService`, `NewsItem`, `OutputItem`, `IosBinding`, `ArrayPattern`, `ExportedConfig`, `SvelteIdentifier`, `CandidateResponderRule`, `SPHttpClientResponse`, `ImgType`, `Title`, `ConnectionListener`, `SeriesList`, `HookEnvironment`, `GameChannel`, `TriggerConfig`, `KoaMiddleware`, `core.ETHGetAccountPath`, `GrowableXYZArrayCache`, `Notify`, `AccountSetBase`, `IDataSourcePlugin`, `SortStateAPI`, `PlainObjectOf`, `GeneratorExecutor`, `AbstractField`, `UsePaginatedQuery`, `aws.autoscaling.Policy`, `VertexAttributeInput`, `ListDbSystemsRequest`, `SyncableElement`, `Chalk`, `AttributeListType`, `NonemptyReadonlyArray`, `KernelMessage.IIOPubMessage`, `ShellExecution`, `JSXOpeningElement`, `AbiStateObject`, `sdk.IntentRecognizer`, `IMiddlewareHandler`, `ISpriteAtlas`, `MongoIdDto`, `R2`, `CreatedObject`, `App.windows.window.IClassicMenu`, `IAudioSource`, `UpdateChannelError`, `HyperlinkMatch`, `IntegerList`, `BasketSettings`, `AnimationDefinition`, `ClearableMessageBuffer`, `NodeExtensionSpec`, `JsExport`, `ArrayPropertyValueRenderer`, `GaugeDialogType`, `UnderlyingSource`, `MergeResults`, `ASTCodeCompatibilityReport`, `InvalidSubnet`, `ConchVector3`, `PotentialEdge`, `ExternalCliOptions`, `KeywordTypeNode`, `ListIPSetsCommandInput`, `LineBasicMaterial`, `XAxisTheme`, `PluginConfigDescriptor`, `Dialect`, `IfExistsContext`, `PiConcept`, `PreferenceService`, `Difference`, `SO`, `props`, `TSSeq`, `IFunctionWizardContext`, `UserDevices`, `IDashboardConfig`, `JsonRpcResponsePayload`, `ResolveOutputOptions`, `CodeMirror.Doc`, `ExtendOptions`, `ComputedParameter`, `UseSavedQueriesProps`, `OffsetOptions`, `SelectSpace`, `Height`, `CoapPacket`, `DirectoryInfo`, `IExternalFormValues`, `IdentityContext`, `mitt.Handler`, `EXECUTING_RESULT`, `moneyMarket.market.BorrowerInfoResponse`, `AdagradOptimizer`, `IFilterItem`, `CommentAttrs`, `IChangesState`, `DashboardUrlGeneratorState`, `IUiState`, `NavigationService`, `IPropertyWithHooks`, `LinkOpts`, `ExtendedFeatureImportance`, `ReactExpressionRendererProps`, `CmsModelField`, `ExploreResult`, `TemplateFileInfo`, `Communicator`, `IStreamApiModel`, `MidwayFrameworkType`, `IDeployedContract`, `DfDvNode`, `BoostStyleProps`, `PaginationConfig`, `i18next.TFunction`, `PragmaNameContext`, `StopwatchResult`, `NodeImpl`, `FormatToken`, `ArkApiProvider`, `ParsingResult`, `CacheEntry`, `IWithHistory`, `monaco.languages.CompletionItem`, `INodeFilter`, `PageDescriptor`, `LookupByPath`, `SignInResult`, `RegionMetadataSchema`, `Refs`, `ModdleElement`, `ImportFromNode`, `QueryProviderAttributesRequest`, `SessionService`, `LIGHT_INFLUENCE`, `SnapshotDetails`, `Canceler`, `ChildNode`, `ArchiveHeader`, `ShadowsocksManagerServiceBuilder`, `MomentInput`, `IAPIService`, `WebsocketState`, `INotificationsService`, `SourceFileEntry`, `KeySuffixOptions`, `PropertySignature`, `vscode.Uri`, `ResponseCV`, `PlaywrightClientLike`, `ScaleByBreakpoints`, `BundleOrMessage`, `DotLayerArgs`, `ConnectorProperty`, `MetricData`, `TReducer`, `KanbanList`, `HttpHealthIndicator`, `ClientType`, `PropertyKnob`, `ts.ParsedCommandLine`, `CustomHelpers`, `ConnectionFetcher`, `NohmModel`, `RequestProgress`, `XEvent`, `CaBundle`, `ClientMessage`, `VaccinationEntry`, `DefaultAttributeDefinition`, `DamageEvent`, `TAccum`, `GitHubPRDSL`, `MyClassWithReturnArrow`, `LoginReq`, `StreamAction`, `SegmentedControlProps`, `XcodeCloud`, `EntryNested`, `SelectedScript`, `fixResult`, `KibanaSocket`, `IAugmentedJQuery`, `ClassLexicalEnvironment`, `StyleDeclaration`, `TileMap`, `ServiceTypeSummary`, `CompiledBot`, `DeletePolicyRequest`, `CoapRequestParams`, `RenderPassToDefinitionMap`, `JSParserOptions`, `ListTagsForStreamCommandInput`, `DehydratedState`, `ESTermSourceDescriptor`, `KWin.Client`, `IInputType`, `ConfigUpsertInput`, `IMessageResponse`, `SyncConfig`, `GearService`, `MIREphemeralListType`, `CppArgument`, `NameSpace.WithEnum`, `AsApiContract`, `XAnnotation`, `UnionRegion`, `GeometriesCounts`, `IJoin`, `DirectiveLocation`, `PaymentChannel`, `RoomSettings`, `GraphQLField`, `ITagNode`, `TheiaBrowserWindowOptions`, `ConfigDict`, `AudioProfile`, `CampaignTimelinesModel`, `graphql.GraphQLFieldConfigMap`, `Destroyable`, `TRPCErrorResponse`, `RootElement`, `Notice`, `anchor.web3.PublicKey`, `SessionData`, `PluginDeleteAction`, `CheckOptions`, `IStackStyles`, `ScriptCmd`, `Vehicle`, `ChangeCipherSpec`, `ITasks`, `InteractionReplyOptions`, `RecordStringAny`, `ActionCreatorWithoutPayload`, `DropdownComponent`, `DragInfo`, `CodeLocation`, `NewRegistrationDTO`, `DockerConfig`, `FileHandle`, `UpdateJobResponse`, `ImageIdentifier`, `NoteworthyApp`, `IndexedClassMapping`, `PartialVersionResolver`, `ArrayService`, `NSObject`, `InstallWithProgressResponse`, `MemberAccessInfo`, `V1ContainerStatus`, `ChatMessageReadReceipt`, `HassEntity`, `AssetPublishing`, `CodeItem`, `BaseFormValidation`, `BaseMarker`, `interfaces.MetadataReader`, `NSDatabase.ITable`, `requests.ListPrivateIpsRequest`, `ScaleHandle`, `NVM500NodeInfo`, `Products`, `Details`, `FieldRule`, `TString`, `SubProg`, `DecompiledTreeProvider`, `EntityAdapter`, `ScenarioCheckInput`, `RelationQueryBuilder`, `IconPack`, `ArweaveAddress`, `Popover`, `GitBlameLine`, `IconOptions`, `Http3Request`, `IVertex`, `MaskObject`, `web3.PublicKey`, `PathLike`, `BroadcastOperator`, `Glissando`, `OrderBalance`, `IInterceptors`, `LinkedPoint`, `SfdxError`, `TArg`, `CoreEventHandlers`, `Local`, `ISplitIndex`, `dia.Graph`, `StorageBackend`, `D3Link`, `ParametersHelper`, `OneInchExchangeMock`, `FlatCollection`, `WebcamIterator`, `NotificationState`, `NodeLocation`, `IMigrator`, `MetaDataOptions`, `StateMachine`, `Cpu`, `DataTypeFields`, `KeyOctave`, `p5`, `ActionLogger`, `LunarMonth`, `YogaNode`, `DeployState`, `NetInfoState`, `SVGTSpanElement`, `MVideoId`, `SliderInstance`, `CssClasses`, `GitHubInfo`, `MediaProvider`, `ProductOptionService`, `MockedObjectDeep`, `MessageComponentInteraction`, `RawRustLog`, `Slider`, `PickKeyContext`, `TechnologySectionProps`, `ListEntitiesCommandInput`, `vscode.NotebookData`, `UpdateArticleDto`, `ContainerArgs`, `BaseGraph`, `OffchainDataWrapper`, `IStatusResult`, `OutputTargetDistCustomElements`, `BlockNodeRecord`, `DisplayDataAmount`, `DateInterval`, `TranslateHttpLoader`, `XmlListsCommandInput`, `protos.common.IApplicationPolicy`, `RevalidatorOptions`, `ComponentSet`, `TextMap`, `MemoryDb`, `WholeJSONType`, `Awaitable`, `MapLocation`, `IAuthCredential`, `DeleteTagsCommandOutput`, `k8s.Provider`, `DiscoverTypings`, `FeedbackData`, `ReadOnlyFunctionResponse`, `ContextSet`, `Studio`, `ASRequest`, `CustomOracleNAVIssuanceSettings`, `GasTarget`, `SubmissionController`, `SwaggerSpec`, `CustomRequestOptions`, `iDraw`, `GaxCall`, `WorkspaceManager`, `NotificationError`, `IGraphData`, `ContractEntryDefinition`, `CallEffect`, `AppAuthentication`, `Auth`, `LabelModel`, `Walker.Store`, `Web3Provider`, `InMemoryStorage`, `PropertyData`, `ModelRef`, `Chai.Should`, `apid.VideoFile`, `ComponentChildren`, `EmployeeInfo`, `Organizations`, `CommandNode`, `AssignmentKind`, `Waypoint`, `CustomerModel`, `NamedField`, `IProp`, `PatternCache`, `Values`, `FormValidationResult`, `SimpleProgramState`, `BehaviorName`, `UndoPuginStore`, `d.WorkerMainController`, `KeypairBytes`, `InspectorViewProps`, `ZodIssue`, `SignatureReflection`, `HTMLBRElement`, `GLRenderPassContext`, `TeamsActions`, `IMoveFocusedSettings`, `DocViewsRegistry`, `Cube`, `Goal`, `White`, `HandPoseConfig`, `NotFoundException`, `IQueryParams`, `TableConfiguration`, `MethodOrPropertyDecoratorWithParams`, `Dsn`, `ArchTypes`, `ValidateOptions`, `SpringResult`, `AuditorFactory`, `CollectionBundleManifest`, `ICrudListQueryParams`, `WatchedFile`, `FluidObjectMap`, `StructType`, `ChangedDataRow`, `OidcClientService`, `DynamicEntries`, `PutBucketPolicyCommandInput`, `vsc.CancellationToken`, `JoyCon`, `TimeoutErrorMode`, `UserPrivilegeService`, `AdbBufferedStream`, `DataHandle`, `TestWorker`, `WebOutput`, `PageActions`, `ObservableArray`, `DataTable.ColumnCollection`, `Descendant`, `Node.DepositParams`, `BindingOptions`, `TransformedStringTypeKind`, `ScanMessage`, `NestedCSSProperties`, `EvaluateFn`, `HttpResponseBadRequest`, `CompositeParserException`, `SceneEmitterHolder`, `TD.ThingProperty`, `ApiPipelineVersion`, `IndividualTreeViewState`, `MarketHistory`, `InteractiveStateChange`, `FunctionTypeParam`, `IMaterialUniformOptions`, `IndicatorCCReport`, `TmGrammar`, `NzTreeNodeOptions`, `OAuthService`, `DateFormattingContext`, `DomManipulation`, `AppCompatActivity`, `DeleteMembersCommandInput`, `IParty`, `WrappingMode`, `GraphicsLayer`, `BoundBox`, `GLTFPrimitive`, `Entity.List`, `GameInfo`, `IMyTimeAwayItem`, `ShowProps`, `TriggerAction`, `FixHandlerResultByPlugin`, `SyntaxInterpreter`, `RemoveOutputRequest`, `CGOptions`, `VariableGroupDataVariable`, `V2`, `NotebookNamespace`, `effectOptionsI`, `EditPoint`, `SignalValues`, `ZWaveLogContainer`, `TooltipPortalSettings`, `ClientConfig`, `InlineFragmentNode`, `APIResponse`, `FullChat`, `PutAssetPropertyValueEntry`, `DataDocument`, `HslaColor`, `ThyTransferSelectEvent`, `PipelineStage`, `IEdge`, `GlobalScript`, `MousecaseResult`, `ContextType`, `TNerve`, `TransportParameterId`, `DeleteDocumentCommandInput`, `v`, `EnumIO`, `TypeEnv`, `ContainerBindingEvent`, `RouteHealthCheckResult`, `m.Comp`, `SignatureTypes`, `SignatureAlgorithm`, `T2`, `Node2D`, `CustomConfig`, `PrimaryContext`, `SourceFile`, `ExportingOptions`, `SpectrogramData`, `LegendValue`, `AwaitEventEmitter`, `TimeSlot`, `PoolConfig`, `HapiResponseObject`, `HomeProps`, `AsyncOpts`, `ResolvedStyle`, `DataDrivenQuery`, `SpyLocation`, `CompilerSystemRemoveDirectoryOptions`, `ObservableLike`, `UserNotification`, `cc.Event.EventMouse`, `EmployeeService`, `ViewItem`, `JVertex`, `FieldType`, `Address6`, `NonCancelableCustomEvent`, `FlowTypeTruthValue`, `StartMigrationCommandInput`, `Minion`, `RuledSweep`, `ListPackagesForDomainCommandInput`, `RedisCommandArgument`, `OperatorDescriptorMap`, `IVersion`, `AlertStatus`, `TypeGuard`, `OptimisticLockError`, `io.ModelArtifacts`, `HTMLImageElement`, `DeleteBranchCommandInput`, `TaroEvent`, `FieldFormatConfig`, `UpdateAccountCommandInput`, `ValidatorError`, `requests.ListManagedInstancesRequest`, `CreateApplicationCommandInput`, `ListingDefinitionType`, `LibraryComponent`, `AuthenticationFlowRepresentation`, `RowRendererProps`, `SerializedEvent`, `ast.PersistNode`, `OrganizationProject`, `DeferredImpl`, `StringNode`, `ModelItem`, `SchemaHelper`, `ModelCheckResult`, `AerialMappers`, `MultiFn2`, `IGroupData`, `EventFnError`, `SchemaGenerator`, `Executable`, `vscode.Extension`, `ObjectConstructor`, `FieldTypeSelectOption`, `ClassMethodDefinition`, `ScalarNode`, `WmsLayer`, `UnidirectionalTransferAppState`, `Success`, `DecodedLogEntryEvent`, `CheckItem`, `B14`, `TeamSpaceMembershipProps`, `PartyLeave`, `ContextPosition`, `QuotaSetting`, `Series.PlotBoxObject`, `ChangeAnnotationIdentifier`, `StartupInfo`, `CachedToken`, `PreviewPicture`, `StructCtor`, `IRunResult`, `CdsTreeItem`, `DescribeFileSystemsCommandInput`, `SymbolId`, `TokenDetailsService`, `Sein.IResourceState`, `CreateUserResponse`, `domain.Domain`, `CreateVpcPeeringConnectionCommandInput`, `BaseElement`, `ForgotPasswordVerifyAccountsValidationResult`, `PluginDiscoveryError`, `BlobBeginCopyFromURLResponse`, `BackgroundRepeatType`, `DiscordInteraction`, `BroadcastMode`, `SyntaxCursor`, `IIFeedsState`, `CSharpType`, `Op2`, `SessionClient`, `ProcessStorageService`, `VertoMethod`, `SimpleStateScope`, `PushOptions`, `CSSValues`, `ModelConstructor`, `MockedElement`, `RenderNodeAction`, `ElementArray`, `TooltipStateReturn`, `ITranslator`, `UNKNOWN_TYPE`, `HTTPHeader`, `CallHierarchyOutgoingCall`, `InstanceManager`, `ServiceWorkerVersion`, `FileUploadService.Context`, `GetCollapsedRowsFn`, `Float32List`, `ITodoItem`, `QRCodeScheme`, `AutoRenderOptionsPrivate`, `MachineEvent`, `IInstallManagerOptions`, `ViewPortHandler`, `MutationHandler`, `ecs.ContainerDefinitionOptions`, `WorkerMessageType`, `Clue`, `TypeAliasDeclaration`, `SGGroupItem`, `ICriteriaNode`, `TestFactory`, `PagerAdapter`, `AddressBookContact`, `AxisLabelFormatterContextObject`, `ServiceProxy`, `JSONRPCRequest`, `CliCommandProvider`, `EmbedToken`, `LedgerReadReplyResponse`, `DescriptorIndexNode`, `ConfigDeprecationProvider`, `KeyValueDiffers`, `ObjectData`, `AssertClause`, `FormatStringNode`, `ClientMatch`, `Workflow`, `AccountFacebookInstantGame`, `DiffInfo`, `BSPEntity`, `BitmapText`, `ISource`, `ProfilerConfig`, `DocumentProcessorServiceClient`, `RootLabel`, `OdmsPhaseActions`, `DynamicFormControlLayout`, `AnimationStateMetadata`, `AstNodeDescription`, `JoinClause`, `formatting.FormatContext`, `ChartAnimator`, `WalletKey`, `WordcloudUtils.PolygonObject`, `UIBeanStorage`, `Flavor`, `Twitter.Status`, `IPaneContent`, `DurableOrchestrationStatus`, `SavedObjectTypeRegistry`, `Fixed`, `AtomicAssetsHandler`, `LayerWeightsDict`, `JSONRPCProvider`, `blockchain_txn`, `TwoWayRecordObservable`, `WorkspacePath`, `RequestTask`, `AfterCaseCallback`, `DefaultGeneratorOptions`, `LOGGER_LEVEL`, `Asteroid`, `ErrorEvent`, `MongooseQueryParser`, `TableSuggestionColumn`, `BodyState`, `GameScene`, `FormatFactory`, `IContentFilter`, `DatabaseState`, `STColumnFilterMenu`, `QuantifierResult`, `IUserItemOptions`, `TransactionWithBlock`, `StateUpdatedEvent`, `StatusParams`, `TIO`, `ConsoleWidget`, `TwitchChat`, `MethodParam`, `OrganizationVendorService`, `CalculateInput`, `IOSInput`, `ExecutorMessages`, `CausalRepoBranch`, `SelectedPaths`, `ARPosition`, `CanvasSpaceValues`, `RestoreFn`, `sdk.ConversationTranscriber`, `GraphQLAbstractType`, `CellInterval`, `VcsAuthenticationInfo`, `SubmissionObjectState`, `ByteStream`, `MoveLandedType`, `CirclineArc`, `MessageRemoteImage`, `Queries`, `DaLayoutConfig`, `HttpStatus`, `Checkbox`, `IEmployeePresetInput`, `MarkdownParsedData`, `S2ExtensionType`, `Pred`, `ListViewProps`, `MultiDictionary`, `CreateStateContainerOptions`, `DateParts`, `LogObj`, `VisualizationOptionStore`, `PkSerializer`, `monaco.languages.ProviderResult`, `BaseCallbackConstructor`, `HDOMNode`, `SflTester`, `NewLineType`, `TreeModelChanges`, `EntitySchemaDatatype`, `JurisdictionDomainModel`, `IController`, `SavedObjectsExportTransformContext`, `RoughRenderer`, `CategoryState`, `ParameterDecorator`, `TemplateDiff`, `Html5QrcodeScannerState`, `Postfixes`, `MsgBlock`, `GX.CompareType`, `Interpreter`, `IArticleData`, `DescribeInputCommandInput`, `TabulatorThingChanges`, `StyleResults`, `BlockchainEnvironmentExplorerProvider`, `ShapeProps`, `ThemeMode`, `SpringFn`, `DelegateBuilder`, `RunShellResult`, `TestsManifest`, `WhileNode`, `DominantSpeakersInfo`, `SavedQuery`, `WhereClause`, `QueryAccountsRequest`, `SentMessageInfo`, `Panels`, `UrbitVisorConsumerTab`, `IConditionalTag`, `ControllerSpec`, `ApiClientConfiguration`, `JavaRenderer`, `OpenFile`, `ethereum.TransactionReceipt`, `E.ErrorMessage`, `RaribleProfileResponse`, `PolicyBuilderConfig`, `ChartPointsSource`, `PostEntity`, `PElementHandle`, `UrlGeneratorsSetup`, `CreateUserCommand`, `ParsingContext`, `ITabInfo`, `Buf`, `Bingo`, `DecadeCell`, `RenderBannerConfig`, `NamespaceDeclaration`, `GetContactCommandInput`, `StandardProjectCard`, `DepthwiseConv2D`, `OverlayBackgroundProps`, `DataTableFormatProps`, `DocumentClient`, `SecurityPolicy`, `ast.AssignNode`, `AstDeclaration`, `TagConfig`, `HumidityControlSetpointCCGet`, `TsSafeElementFinder`, `IAM`, `TriggeredEvent`, `ListTasksCommandInput`, `EventMap`, `pxt.PackagesConfig`, `PaySlip`, `ParsedIOMessage`, `Sexp`, `esbuild.Plugin`, `LVarKeySet`, `CElement`, `FetchStartedAction`, `EnumMetadata`, `Kind2`, `AuthenticationInterface`, `SvelteSnapshot`, `IText`, `ImmutableObjectiveTag`, `IFixture`, `JMapLinkInfo`, `Exercise.Question`, `IGroupFilterDefinition`, `Verify`, `SocketGraphicsItem`, `CustomError`, `DescribeWorkspacesCommandInput`, `GLint`, `MockLoadable`, `PDFObject`, `DebugProtocol.StackTraceResponse`, `StorageFormat`, `ZodObject`, `SignedVerifiableClaim`, `IHomebridgeAccessory`, `ChangeCallback`, `ListAttendeesCommandInput`, `CommentSeed`, `NameValueDto`, `BranchPruner`, `DataProcessor`, `CreateStreamCommandInput`, `Limiter`, `PossiblyAsyncOrderedIterable`, `PluginBuild`, `DocTable`, `glTF.glTF`, `OpenSearchQuerySortValue`, `ZipFileEntry`, `IndexResults`, `IKubernetesManifestCommandData`, `LifeCycle`, `Pbkdf2Digests`, `sdk.IntentRecognitionResult`, `TableReference`, `xLuceneTypeConfig`, `StyledForwardStyle`, `IScrollerInfo`, `ProjectProperties`, `ReplicaDetails`, `ProtectionRuleExclusion`, `$DFS.DFS_Config`, `SliderValue`, `LoggerProperties`, `SwankRequest`, `OutUserInfoPacket`, `BundleRef`, `Mark`, `DrawerState`, `ExtractorConfig`, `Redirect`, `vscode.WorkspaceFolder`, `INotifyItem`, `AnimationService`, `OrdererTreeItem`, `StackBuilder`, `DateTimeRecognizer`, `InputOptions`, `InputModalityDetectorOptions`, `AppState`, `Health`, `IntrospectionWarnings`, `TextureSlab`, `FirestoreConnectorModel`, `InstanceType`, `IActiveLearningSettings`, `IErrorsManager`, `SnackbarErrorAction`, `ClipPreRenderContext`, `PIXI.Renderer`, `ISaxParser`, `ApiLocatorService`, `TensorLike`, `ProviderType`, `FunctionJSON`, `Detection`, `AvatarConfig`, `GithubIssue`, `RawRow`, `ImageryLayer`, `FileRenameEvent`, `MemberSoundEffects`, `ShaderVariableType`, `ResetPasswordDto`, `GlobalEventsService`, `RelativeDateFilterTimeUnit`, `ng.IPromise`, `ExceptionlessClient`, `EngineMiddlewareParams`, `requests.ListLogGroupsRequest`, `PresentationManagerProps`, `StateAccessingOptions`, `GetCellColSpanFn`, `DataCallback`, `WalletCredentials`, `Dubbo`, `DaffCompositeProductItem`, `nVector`, `CursorMap`, `WorkerDOMConfiguration`, `TickFormatter`, `TPermission`, `ReturnT`, `RepositoryType`, `NdjsonToMessageStream`, `TimelineFilter`, `TableDataSet`, `MatchmakerMatched`, `BinaryOperator`, `ChallengeData`, `JSONMappingParameters`, `ThyTreeNode`, `ActivityAction`, `Registry`, `UserConfiguration`, `ChildProps`, `ConfigurationEnv`, `DigitalWire`, `IPFS`, `StackActivity`, `BuildConfigs`, `OpenApiDecorator`, `TransferHotspotV1`, `IIssueParms`, `RoutesWithContent`, `AxeResult`, `JsonSchema`, `BillingActions`, `DagOperator`, `RelationType`, `NucleusFile`, `DateCell`, `FormErrorMessageModuleConfig`, `BoolPriContext`, `MockStakingContract`, `ReturnValue`, `Binder`, `InStream`, `NzTabComponent`, `IPlug`, `LogisticsRequest`, `JRPCMiddleware`, `PerSideDistance`, `JSet`, `SelectableItem`, `MerchantGoodsService`, `GetModelTemplateCommandInput`, `DataflowAnalyzer`, `GetAllAccountsValidationResult`, `VdmParameter`, `ExtraGate`, `FaIconLibrary`, `ResourceConstant`, `ListOfPoints`, `ParamsFilter`, `QueryableFieldDescription`, `AlfrescoApiService`, `childProcess.ChildProcess`, `GetConnectionResponse`, `RowTransformCallback`, `SettingsNotify`, `OptsChartData`, `ExponentSpec`, `CinemaFrameType`, `DeleteMeetingCommandInput`, `ConnectionProfile`, `IZoweNodeType`, `FieldGroup`, `Vfs`, `OverrideContext`, `LineHeight`, `ITimeSlot`, `MotionInstanceBindings`, `BaseUIElement`, `BITBOX`, `PartialTransaction`, `Highcharts.AnnotationControllable`, `TextChange`, `C5`, `Requireable`, `ParseCxt`, `UserWhereInput`, `TermEnv`, `IntlType`, `ChangeAnnotation`, `ProviderOptions`, `SGArcItem`, `Verdaccio`, `ClientFactory`, `BaseEnvironment`, `AutoAcceptProof`, `ModalState`, `flags.Discriminated`, `LoaderConfOptions`, `IVue`, `EffectComposerComponent`, `coreClient.CompositeMapper`, `ProcessStatus`, `LibrarySearchQuery`, `InjectionService`, `CancellationToken`, `UIElement`, `NextResponse`, `ts.EntityName`, `HostRecord`, `DelayedRemovable`, `TextEditorEdit`, `TForwardOptions`, `PostTexMtx`, `ImportEqualsDeclaration`, `Versions`, `Brew`, `Algebra.PlanNode`, `GrafanaTheme`, `EndpointAuthorization`, `Support`, `ComponentCompilerMeta`, `CBService`, `TCacheResult`, `SVFunc`, `ICreateFormDialogState`, `ICollaborator`, `OpenSearchClientConfig`, `PhysicalModel`, `MDCTabIndicatorAdapter`, `HTTPAuthorizationHeader`, `azureBlobStorage.Container`, `ErrorBoundaryProps`, `HsdsId`, `TokenInterface`, `Json.Segment`, `ReadOnlyIterator`, `JSONAPIDocument`, `CrossTable`, `DirectivePosition`, `IpcCommandType`, `JsonPointer`, `Zoo`, `Point.PointLabelObject`, `ValueContainerProps`, `BTIData`, `IClient`, `SecretsService`, `AuthMode`, `GitFile`, `Neo4jService`, `IAzureQuickPickItem`, `RequestOption`, `ValueType`, `LineIndex`, `ecs.TaskDefinition`, `SfdxOrgInfoMap`, `Workbook`, `GfxVendorInfo`, `ObjectLayer`, `ProblemFileEntity`, `InternalTimeScalePoint`, `NFT721V2`, `WebviewPanelOnDidChangeViewStateEvent`, `gradient`, `ContextT`, `FakeHashProvider`, `Highcharts.VMLElement`, `IAggConfigs`, `IViewZoneChangeAccessor`, `IntrospectionNamedTypeRef`, `Rollup`, `Poll`, `VariableService`, `GBMinInstance`, `IndTexStage`, `PriceSpecInput`, `CdtTriangle`, `FlattenedProperty`, `OnSetOptionsProps`, `MapPolygon`, `PlayService`, `LogAnalyticsSourceLabelCondition`, `Donation`, `RhoContext`, `TransactionBuilderFactory`, `SendToAddressOptions`, `PGOrbitsDef`, `TupleTypeReference`, `LoaderContext`, `CalendarItem`, `CompoundSchema`, `DeleteComponentCommandInput`, `FieldStatsCommonRequestParams`, `TertiaryButtonProps`, `EntityDispatcherFactory`, `AccountId`, `XmlEmptyListsCommandInput`, `MountPoint`, `IInterval`, `DisjointRangeSet`, `ContractCallContext`, `NativeViewElementNode`, `UploadService`, `ThemeColors`, `PropTypesOf`, `PublicationViewConverter`, `PaletteMode`, `THREE.Ray`, `freedom.RTCPeerConnection.RTCPeerConnection`, `VariantOptionQualifier`, `StandardPrincipal`, `ISummaryTree`, `PropCombination`, `IAtomMdhd`, `MsgWithdrawLease`, `AnimGroupData_Draw`, `TextDocuments`, `MutableArrayLike`, `GBDialogStep`, `NormalRequest`, `AsyncMethodReturns`, `Undefinable`, `DataViewsContract`, `ClientState`, `DeleteStatus`, `TimelineProvider`, `AbstractNode`, `ReactFlowState`, `MyController`, `ActionMessage`, `Interfaces.ViewEventArguments`, `DebugSourceBreakpoint`, `FormattedString`, `IConnectionCredentialsQuickPickItem`, `AwsCallback`, `ZodEffects`, `Int8Array`, `DejaPopupConfig`, `OpenApi.Schema`, `AndroidProjectParams`, `SavedObjectsType`, `ColorStop`, `Supports`, `MultiTablePrettyfier`, `ObjectDoc`, `DGroup`, `PluginInstaller`, `ChangeFilter`, `ReactApolloRawPluginConfig`, `UserStoreAction`, `StrokeStyle`, `StorageObjectList`, `Jobs`, `MutableCategorizedArrayProperty`, `CurrentForm`, `PromiseEventResp`, `WebGLBuffer`, `WechatyVorpalConfig`, `DescribeScalingPoliciesCommandInput`, `AssociationAddress`, `FutureBoolean`, `GunRolls`, `ChannelMessage`, `SlotValue`, `Picker`, `MsgCloseDeployment`, `PlannerConfiguration`, `StaticdeployClient`, `ServiceDescription`, `SuggestionOperationType`, `WindowId`, `puppeteer.KeyInput`, `ProseMark`, `MapStateToPropsParam`, `Quantity.MANY`, `DeleteSlotTypeCommandInput`, `MockChannel`, `EventSourceMap`, `ConvertedToObjectType`, `BucketMetadata`, `UpdateStageCommandInput`, `ErrorNode`, `TrackedDocument`, `ConfigProvider`, `AsyncStream`, `Lens`, `NetworkgraphLayout`, `WorkerChild`, `MsgFromWorker`, `IFileAccessConfiguration`, `Claims`, `Changer`, `ServiceArgs`, `CVLanguageManager`, `RenderConfig`, `ConnectionManager`, `AuthenticationSessionsChangeEvent`, `AliasEventType`, `IsSpecificCellFn`, `ReducerList`, `RecipientMap`, `AV1Obu`, `ListPhoneNumbersCommandInput`, `GraphQLUnionType`, `OfflineAudioContext`, `ShaderDefine`, `TransientSymbol`, `ICliCommand`, `Marshaller`, `OverlayChildren`, `PrimitiveTypeAssertion`, `AuthUserContext`, `AttachmentID`, `MaybePromise`, `EditableSelection`, `Reference`, `TreeDecoration.Data`, `ValidatorProxy`, `UploadMetadata`, `CharCategory`, `GeometricElementProps`, `ServicesAccessor`, `UnionableType`, `ChangLogResult`, `BannerProps`, `HTTPResponse`, `MdcListItem`, `T11`, `CombineParams`, `RedirectionResponse`, `CommandRegistryImpl`, `PrismaClientErrorInfo`, `IRegisterItem`, `MatchCreate`, `NodeModel`, `ReindexSavedObject`, `PromoteReadReplicaDBClusterCommandInput`, `IDatabaseDataModel`, `BatchWriteCommandInput`, `PromiseLike`, `apid.LiveStreamOption`, `PGOrbit`, `FormEventHandler`, `SideNavItem`, `SqlVals`, `ILicenseState`, `InterceptedRequest`, `ObjectDetectorOptions`, `ChartCoordinate`, `GetNotificationsFeedCommand`, `ChainFunction`, `CreateRoomCommandInput`, `SubscriptionItem`, `AnInterface`, `binding_grammarListener`, `BigAmount`, `GetPublicKeyCommandInput`, `TargetData`, `Coordinate`, `ProjectDefinition`, `HalResourceConstructor`, `ImageClassifierOptions`, `SheetContextType`, `CustomCallbackArgs`, `ListObjectsResponse`, `tfc.serialization.ConfigDict`, `IPageRenderInstruction`, `ChildArenaNode`, `TopNavMenuProps`, `ComparisonOperand`, `ShelfFunction`, `Changelog`, `SaberProvider`, `PluginsServiceStartDeps`, `DebugProtocol.VariablesResponse`, `EmailHandler`, `DomainEndpointOptions`, `SolidityValueType`, `SelectReturnTypeOptions`, `DraggableProvided`, `QuadViewModel`, `ChampionsLeagueStat`, `MotionDataWithTimestamp`, `BlobId`, `Alg`, `NullableMappedPosition`, `ClassReflection`, `DependencyTree`, `AuthUser`, `IVideoFileDB`, `BucketInfo`, `CachingRule`, `ComputeImage`, `MappedDataSource`, `BeDuration`, `TaxonomicFilterGroupType`, `Examples`, `VerificationInput`, `DataPlanSObject`, `ValidationFlags`, `CurveCrossOutput`, `PredefinedGeneratorResolvers`, `NoteStorage`, `FakeSystem`, `Coin`, `ExternalEmitHelpers`, `CommitSelectionService`, `ModularPackageJson`, `byte`, `PageHeader`, `RemoteBreakpoint`, `MixedObject`, `Raycaster`, `SetupServerApi`, `ObjectDescription`, `ApiItemMetadata`, `Executor`, `ChildReference`, `GfxProgramDescriptorSimple`, `WaitContextImpl`, `AnyCallbackType`, `SendableMsg`, `HSD_LoadContext`, `RangeIterable`, `MicrosoftStorageStorageAccountsResources`, `EncoderOptionsBuilder`, `Point2D`, `JpegEmbedder`, `ContractMethod`, `CloudFrontHeaders`, `FetchDependencyGraph`, `u128`, `EnabledFeatureItem`, `INodeList`, `TileKeyEntry`, `ListParameters`, `RtcpSenderInfo`, `ReleaseAsset`, `Nullable`, `FormGroupField`, `LogError`, `AssignableObject`, `EggPlugin`, `TypescriptParser`, `WriterResource`, `CheckerOption`, `ApexVariable`, `MapExtent`, `ContinueNode`, `MergeConfig`, `APIConstructor`, `ShapeConstructor`, `SupervisionCCReport`, `ParticipantResult`, `NodeSpecOverride`, `LoanFactory2`, `Session.IOptions`, `Models.BlobMetadata`, `CanonicalOrder`, `IAggregationDataRow`, `Tracklist`, `XYPosition`, `FilterValues`, `ModelFitDatasetArgs`, `SqlParameter`, `ICellModel`, `ContentsXmlService`, `InvoiceService`, `core.Keyring`, `TProperty`, `GitHubPullRequest`, `flags.Kind`, `IProxySettings`, `RoadmapProps`, `SimpleRule`, `UnorderedQueryFlow`, `Stanza`, `HelpRequestArticle`, `AnnotationAnalyticsAggregation`, `DerivedAtomReader`, `ProgressInfo`, `TabPanelProps`, `ListChannelsCommandInput`, `ConnectionData`, `RenderRow`, `BlockOptions`, `SavedObjectFinderProps`, `UpdateApp`, `FileItem`, `AuthenticationModel`, `RegisterValue`, `MonitoringResources`, `Phone`, `DrawingGraph`, `IScoreCounter`, `Person`, `ApolloVoyagerContextProvider`, `ListExperimentsCommandInput`, `IPole`, `ProofFile`, `CreateTransactionOptions`, `SharedTree`, `RectangleShape2DSW`, `BundleRefs`, `RewardVaultItem`, `TestHostComponent`, `Inheritance`, `IDBVersionChangeEvent`, `options`, `Types.Authentication`, `TestExecutionInfo`, `TestInterval`, `Clipboard`, `GoldTokenInstance`, `EvalEnv`, `EsLintRule`, `SourceMetadata`, `requests.ListBlockVolumeReplicasRequest`, `TsActionCreator`, `UI5ClassesInXMLTagNameCompletion`, `Crisis`, `AsyncExecutor`, `ChromeNavLink`, `CardTitleProps`, `Atom.TextEditor`, `IZosmfIssueParms`, `NexusExtendTypeDef`, `ArianeeHttpClient`, `AxiosPromise`, `com.google.firebase.database.DataSnapshot`, `ABuffer`, `GraphQLGenie`, `Paths`, `BillingGroup`, `DragDataStore`, `MatrixProfileInfo`, `DeleteRuleCommandInput`, `Func1`, `ExpoWebGLRenderingContext`, `ApplyBuffEvent`, `SymbolLinks`, `Animator`, `IRunConfiguration`, `TagSet`, `TraderConfig`, `OperationStream`, `RoomFacade`, `CreateWalletFlow`, `InputListConfig`, `TradeComputed`, `ParsedImport`, `XrmUiTest`, `ExportService`, `MediaStream`, `WorkRootKind`, `RSAPrivateKey`, `NewId`, `Locals`, `SourceStatus`, `WrappedValue`, `MarketTicker`, `StandardPrincipalCV`, `IndexConfig`, `ResponderEvent`, `CustomFile`, `IPFSFile`, `InternalNamePath`, `IHeaderItem`, `UserFilter`, `IRowIndices`, `ast.LiteralNode`, `HTTPProvider`, `STExportOptions`, `ItemTypeNames`, `IValidateProjectOptions`, `WriteFileCallback`, `ChangeSetData`, `AlertsProvider`, `StructService`, `City`, `LangiumConfig`, `TimeDistributed`, `MML`, `XElementData`, `ModeledMarker`, `ILoadAll`, `TemplateParser`, `TComponentControls`, `DescribeRepositoryAssociationCommandInput`, `WantedTopics`, `ArticlesService`, `TSTypeAliasDeclaration`, `IndexStore`, `GlobalNode`, `DeleteResourcePolicyResponse`, `OutgoingRegistry`, `IZosFilesResponse`, `MatSnackBarContainer`, `EventHandlerType`, `BaseClosure`, `SecretUtils`, `ContainerImage`, `SolidDashedDottedWavy`, `MutableVector2d`, `SVGRenderer.ClipRectElement`, `BugState`, `TextAreaTextApi`, `MDCListFoundation`, `PropertyOperationSetting`, `UnpackAttrs`, `CognitoIdentityServiceProvider`, `ReferenceList`, `IBlobSuperNode`, `MyTargetProps`, `ReferenceResult`, `SourceSymbol`, `CountingData`, `ENDElement`, `DiscordToken`, `IMetricAggConfig`, `StateA`, `TSTypeParameter`, `ServiceBuild`, `InputSearchExpression`, `DbEmoji`, `ErrorBag`, `MatchingOptions`, `STSortMap`, `DeltaInsertOp`, `QueryServiceStartDependencies`, `MenuDataItem`, `RunTaskOption`, `ResponseObject`, `SuggestionFactory`, `WindowState`, `MainController`, `Interpolations`, `IKeycodeCategoryInfo`, `Equiv`, `ListBuildsCommandInput`, `THREE.ShaderMaterial`, `DS`, `LinkSteamRequest`, `NodePort`, `LoadOnDemandEvent`, `UpdateReplicationConfigurationCommandInput`, `PluginDomEvent`, `RunSuperFunction`, `PQLS.Library.ILibrary`, `Gauge`, `IAtomStsd`, `MultisigBuilder`, `MetricInterface`, `AllSelection`, `FormValidation`, `LoadRange`, `MutableCategorizedPrimitiveProperty`, `IRankingHeaderContext`, `IRenderingContext`, `ResolvedProjectReference`, `ComponentCompilerStaticProperty`, `GetServerSidePropsContext`, `ParquetCodecOptions`, `Entity.Notification`, `CallbackOptionallyAsync`, `ApiParams`, `TConfiguration`, `FrequentLicences`, `requests.ListHttpProbeResultsRequest`, `IEventEmitter`, `OptimizeJsOutput`, `AcNotification`, `ts.PropertyName`, `INodeParameters`, `BazelOptions`, `u16`, `NzCalendarHeaderComponent`, `PSTNodeInputStream`, `GitBranch`, `CSSBlocksConfiguration`, `TKey`, `ParserState`, `TransactionBeganPayload`, `Transform3D`, `Artist`, `SanitizerFn`, `PddlSyntaxNode`, `IViewPathData`, `RouteItem`, `LabwareDefinition2`, `DataSet`, `WasmResult`, `HTMLVmMenuRadioElement`, `TestFunctionImportMultipleParamsParameters`, `InstallMessage`, `messages.Hook`, `JSONLocationFunction`, `ContractMethodDescriptor`, `ReactTestRendererJSON`, `HelloWorldContainer`, `TypeElementBase`, `CommunicatorEntity`, `ApiResponse`, `StacksNode`, `V1CertificateSigningRequest`, `IObjectInspectorProps`, `CoreTracerBase`, `BalanceMap`, `SupportedPackageManagers`, `InflightKeyGenerator`, `TypeShape`, `TEAttribute`, `ListDiscoveredResourcesCommandInput`, `HsQueryVectorService`, `Scenario_t`, `JsonSchema7Type`, `IJsonStep`, `__String`, `HeroSelectors$`, `NormalizedPackageJson`, `IElementInfo`, `TaskEither.TaskEither`, `HTMLScStatusTimelineOverlayRowElement`, `StreamGraphNode`, `Dense`, `FiscalCode`, `UserInstance`, `IntrospectionObjectType`, `UpSetAddon`, `Imports`, `SeriesType`, `ContextMenu`, `q.TreeNode`, `squel.Select`, `GlobalizeConfig`, `GUIOrigin`, `IVideoApiModel`, `ProofDescriptor`, `ISharedFunctionCollection`, `Claim`, `ITranscriber`, `FunctionComponentElement`, `OpHandler`, `EventActionHandlerMeta`, `FakeComponent`, `IEvmRpc`, `MsgCreateCertificate`, `IStreamPropertiesObject`, `WikidataResponse`, `TSLet`, `BodyPixInput`, `PageViewComponent`, `DaffCartFactory`, `NedbDatastore`, `PeerConnection`, `V1Role`, `Summary`, `ISceneView`, `ImageFormatTypes.JPG`, `ScmResource`, `SweetAlertResult`, `JEdge`, `OSCMessage`, `EncodedTransaction`, `ResourceProvider`, `TError`, `Jwt`, `NodeClass`, `PageEvent`, `Context`, `TypingVersion`, `BuilderContext`, `BorderConfig`, `Realm.ObjectSchema`, `SerializeSuccess`, `HashMapStructure`, `CanvasModel`, `SmartContractPayload`, `InternalOptions`, `NewFOS`, `SlpRealTime`, `PointCompositionOptions`, `SeriesDoc`, `EggAppConfig`, `TestSerializer`, `SystemVerilogParser.SystemVerilogContainerInfo`, `IResolverObject`, `SavedObjectsSerializer`, `WebhookEvent`, `ExecuteCommandState`, `DeprovisionByoipCidrCommandInput`, `ApiErrorService`, `AddressString`, `IStackItemStyles`, `CanvasBorderRadius`, `BehaviorHost`, `AgentMessage`, `Equivalence`, `TestSpec`, `Solver`, `Users`, `NotificationChannel`, `F2`, `TOCHeader`, `ApolloClientOptions`, `TemplateLiteralTypeSpan`, `GasOptionConfig`, `RelativeDateRange`, `TsConfigLoaderResult`, `SModelElementSchema`, `SV`, `OgmaService`, `NumberNode`, `RefType`, `ServiceEnvironmentEndPointOverview`, `util.TestRunError`, `ComponentResolver`, `ICredentialsResponse`, `EditorChange`, `AugmentedActionContext`, `StubbedInstance`, `ValueHolder`, `ResolvedConfig`, `TestEntity`, `SystemVerilogSymbol`, `ApiSchema`, `SpectatorHostFactory`, `ServerApi`, `AnnotationTypeOptions`, `HostWatchFile`, `ConnectionProperty`, `SyncToolSettingsPropertiesEventArgs`, `PointCloudOctreeGeometryNode`, `FabricEnvironmentRegistryEntry`, `LoadedVertexData`, `Vector3Like`, `ConnectionDictionary`, `ArrayContext`, `ClientChannel`, `Combatant`, `JsonArray`, `TestTreeHierarchyNode`, `WriteRequest`, `Basic`, `K.LiteralKind`, `OrchestrationClientInputData`, `VAceEditorInstance`, `ArrayBufferView`, `KeyRegistrationBuilder`, `BreakpointState`, `TDestination`, `UIButton`, `RouteManifest`, `EffectVblDecl`, `WrappedWebGLProgram`, `SimpleComparator`, `ColorDef`, `CustomDate`, `ResourceMetadata`, `Cypress.cy`, `CommandlineOption`, `SCanvas`, `IDomainEvent`, `DocsLibrary`, `Tsconfig`, `FieldVisConfig`, `IdeaDocument`, `UserDevice`, `ts.ParseConfigHost`, `CipherBulkDeleteRequest`, `Foobar`, `VAIndent`, `IHsv`, `TransportParameters`, `LocalButtonProps`, `ContainerSiteConfig`, `IFormData`, `RoundingModesType`, `GfxChannelBlendState`, `ServerSettings`, `DeleteFilterCommandInput`, `CompilationData`, `GenericNumberType`, `AlphaDropout`, `Company`, `ResponseBuilder`, `Quadratic`, `MetaesException`, `DefaultIdentity`, `WarningPrettyPrinter`, `DbCall`, `InputState`, `WalletInterface`, `StateDiff`, `TweenMax`, `OperationCallback`, `MessageButton`, `requests.ListIamWorkRequestsRequest`, `ErrorType`, `WorkflowStepInput`, `MarkerScene`, `AlignConstraint`, `MerchantMenuOrderGoodsEntity`, `PostMessageService`, `SelectableState`, `SparseSetProps`, `CreateContextReturn`, `ImportCertificateCommandInput`, `IGenericTarget`, `JavaScriptEmbedder`, `AwaitedCommandEntry`, `UI5Config`, `GroupInfo`, `KeyMacroAction`, `TestViewport`, `EntryPoint`, `ComparisonKind`, `ActionObject`, `DiffSettings`, `AsyncSubscription`, `PageItem`, `OrderableEdmTypeField`, `TDiscord.Message`, `IAssetPreviewProps`, `RouterLocation`, `GetActionTypeParams`, `Handler`, `SLL`, `StreamConfig`, `types.Span`, `NeisCrawler`, `OmitFuncProps`, `TimeOffService`, `Like`, `TracklistActions`, `DaffCategoryFilterEqualFactory`, `HDWalletInfo`, `CompilerModeStyles`, `SubMeshStaticBatch`, `LoadContext`, `GameData`, `DeleteDomainCommandOutput`, `requests.ListFastConnectProviderServicesRequest`, `RolloutTracker`, `ParseErrorLevel`, `SignatureInfo`, `ObjectLiteralExpr`, `ComponentProp`, `IAuthenticationService`, `d.DevServerConfig`, `OTRRecipients`, `SpyPendingExpectation`, `SynState`, `FX`, `RippleAPI`, `RelatedClassInfoJSON`, `TreePath`, `ToolbarWrapper`, `CollectionView`, `_m0.Writer`, `IRunExecutionData`, `GeneralInfo`, `IRestResponse`, `VariableState`, `t_3b6b23ae`, `CheerioStatic`, `MasterNodeRegTestContainer`, `ITableParseResult`, `Highcharts.AnnotationControlPoint`, `TResource`, `MarkupContent`, `NgZonePrivate`, `MatButtonToggleChange`, `ChannelOptions`, `IndicatorsData`, `GfxRendererLayer`, `NodeSourceType`, `IAppSettingsClient`, `ColorSwitchCCReport`, `ICtrl`, `JupyterFrontEndPlugin`, `HydrateStaticData`, `MapReward`, `HookType`, `StructServiceOptions`, `ListRevisionAssetsCommandInput`, `ARPlane`, `FamilyPage`, `SearchkitClient`, `TestUiItemsProvider`, `OpticFn`, `StatusBarService`, `IconProps`, `TreeNodeService`, `ShHeap`, `NftMeta`, `DeviceManagerImpl`, `LeakyReLULayerArgs`, `JointTransformInfo`, `ContextAccessor`, `NodeState`, `IProjectInformation`, `CSVMappingParameters`, `ILink`, `FilterPredicate`, `IRuntimeFactory`, `OrbitCameraController`, `MultilevelSwitchCCSet`, `execa.ExecaReturnValue`, `ModuleFormat`, `monaco.Uri`, `FlagType`, `CheckBuilder`, `ViewFactory`, `BrowserFetcherRevisionInfo`, `ReplicationRule`, `CombinedThingType`, `BSplineCurve3d`, `ScalePower`, `BaselineInfo`, `HttpHeaders`, `SendFunc`, `URLLoaderEvent`, `Cell`, `ViewStyle`, `PaginationProps`, `ParallelWorkflow`, `SecondLayerHandlerProcessor`, `MBusForm`, `WalletVersion`, `AngularDirective`, `Capacity`, `IUIMethod`, `IArgDef`, `RSPState`, `ColorPicker`, `Seq`, `StateReceipt`, `i0.ɵViewDefinition`, `System_Object`, `StringOrTag`, `TaskOption`, `CodeBuildAction`, `ParticleEmitter2`, `TrackProp`, `WindowCorrection`, `KeyboardEvent`, `requests.ListTagNamespacesRequest`, `EditorRenderProps`, `ISetCombinations`, `ConceptResponse`, `LexicalEnvironment`, `ToastComponent`, `VersionBag`, `ContributionRewardSpecifiedRedemptionParams`, `Offset`, `GenericWatchpoint`, `QueryDslQueryContainer`, `ComputedUserReserve`, `CAPIContent`, `EventEmit`, `GridIndicator`, `OutcomeType`, `World`, `AggFilter`, `CreateProfile`, `ThyPlacement`, `AddOutputRequest`, `files.SourceDir`, `TryNode`, `NamedBounds`, `IUpSetStaticDump`, `Named`, `FlowPreFinallyGate`, `RegTestContainer`, `VolumeType`, `ImageDataBase`, `TwingTemplateBlocksMap`, `IPresentationTreeDataProvider`, `DataAsset`, `FireLoopData`, `QuestionAdornerViewModel`, `tfl.LayersModel`, `Jsonable`, `Invocation`, `TestRelation`, `IRCMessageData`, `DataTypeFieldAndChildren`, `SourceStorage`, `MagickOutputFile`, `SocketMeta`, `LiftedState`, `Members`, `AsteriskToken`, `SearchCommand`, `ItemIdToExpandedRowMap`, `ReplFs`, `TimeHolder`, `SurveyModel`, `IStopsProvider`, `PrepareQuery`, `BinaryLike`, `Http3QPackEncoder`, `IIssuerConfig`, `CreateFlowCommandInput`, `TripleIds`, `BaseIndexPatternColumn`, `HdRipplePayments`, `ReadModelEnvelope`, `BasicResumeNode`, `IUIDefine`, `ColorResult`, `SourceDescriptionChunk`, `EmployeeAppointmentService`, `model.InstanceOf`, `GX.TexMapID`, `requests.ListInstancePoolsRequest`, `GmailMsg`, `NSSet`, `FlowItemAssign`, `TwingLoaderInterface`, `DynamicCommandLineParser`, `QuizLetter`, `TextBufferObject`, `WarehouseService`, `unicode.UnicodeRangeTable`, `Terms`, `RecordedTag`, `Coordinates`, `BinderFindBindedPositionRet`, `ts.VariableDeclaration`, `UnitMusteringRule`, `BaseN`, `Modifier`, `CreateMasternode`, `BoxListEntity`, `ICustomViewStyle`, `IGroupTemplate`, `SavedObjectMigrationMap`, `RuleWithCnt`, `AccountServiceProxy`, `FieldApi`, `DebugCallback`, `ImageTransformation`, `SurveyPDF`, `UAVariable`, `ITccSettings`, `InternalData`, `RnM2Primitive`, `LineCaps`, `TimeConfig`, `ServerMethods`, `JSONRoot`, `TransferTransition`, `TimePicker`, `TestFileSystem`, `SaleorClient`, `StyleSet`, `ContentType1524199022084`, `MachineInfo`, `AsyncUnorderedQueryFlow`, `Matchers`, `TabApi`, `UpdateRoomMetadataRequest`, `ISharingResponse`, `AnyToken`, `IMyDateRange`, `InstructionType`, `StockSandbox`, `BaseAttribute`, `EventLog`, `PaginationPayload`, `ResolveTree`, `ProcessInstanceTableEntry`, `FileResponse`, `OpenTarget`, `Tweet`, `PlayerInput`, `StatusController`, `EthersProvider`, `providers.BlockTag`, `IModalService`, `CustomStore`, `AlertInputOptions`, `Drag`, `ScanDetails`, `DeleteScalingPolicyCommandInput`, `HashData`, `LogLevels`, `DeleteDBClusterEndpointCommandInput`, `IAnswers`, `MALEntry`, `DiffLayouterFactory`, `SuggestionItem`, `Highcharts.NetworkgraphPoint`, `OptionalVersionedTextDocumentIdentifier`, `Aggregate`, `CiaoService`, `MDCChipAction`, `Search`, `MainAccessRequest`, `NetworkTargetGroup`, `Dep`, `InputBlock`, `UnsubscribeMethod`, `Window`, `CalendarInput`, `CommandRelay`, `TGraphQLContext`, `TableSchemaSpec`, `TypeScriptDeclarationBlock`, `IntTerm`, `QueryBuilderProps`, `AccountGoogle_VarsEntry`, `ng.IQService`, `IOnValidateFormResult`, `MetricsResults`, `CallParams`, `CurveColumnSeries`, `PlaybackRate`, `CSSTemplate`, `AwaitExpression`, `PageRequest`, `DefaultReconnectionHandler`, `DefaultChildrenWNodeFactory`, `ISchemaCollector`, `CssNodeType`, `ProgressList`, `ViewContext`, `Investor`, `WinState`, `TooManyTagsException`, `ConvertedDocumentUrl`, `BrowseCloudDocumentWithJobs`, `BlockOutputFormat`, `RecordObject`, `TimelineGridWrapper`, `GfxReadbackP_GL`, `HtmlContextTypeConvert`, `IAuthContextData`, `CompressedId64Set`, `AnyEvent`, `Aliases`, `ParametricRegExp`, `TrustIdHf`, `IServerSideGetRowsRequest`, `ScrollPosition`, `ApplicationDefinition`, `ShortUrl`, `CallingBaseSelectorProps`, `EncryptionLevel`, `DebugCurve`, `PayableOverrides`, `Triple`, `CreateSavedObjectsResult`, `ProposeMessage`, `Grouping`, `RibbonEmitterWrapper`, `ProblemViewPanel`, `ViewColumn`, `d.SerializeImportData`, `IBlobINode`, `EmittedMessage`, `Polyline`, `d.FunctionalComponent`, `GroupMetadata`, `DefaultRes`, `FleetMetricSummaryDefinition`, `ChangeAccumulator`, `DigitalObjectSet`, `ProductMap`, `MinimalNodeEntity`, `SMTDestructorGenCode`, `ttm.MockTestRunner`, `ChangesetGenerationHarness`, `Addon`, `LayoutPartialState`, `VisHelpTextProps`, `CasesClientInternal`, `AuxChannel`, `THREE.Line3`, `Package.Target`, `ts.ClassElement`, `NormalizedPath`, `CancelablePromise`, `RequestValues`, `RegistrationPage`, `BaseInteractionManager`, `msRest.OperationSpec`, `GeomEdge`, `AuthenticationProgramStateBCH`, `LogMeta`, `_1.EventTargetLike.HasEventTargetAddRemove.Options`, `grpc.Code`, `ValidationController`, `WeightsManifestEntry`, `NetworkInfoStore`, `LocalMigration`, `IBlock`, `RenderCallback`, `ListWorkspacesCommandInput`, `Main`, `InputContext`, `StringNote`, `ListArtifactsCommandInput`, `MockedOptions`, `Describe`, `SIGN_TYPE`, `NumOrElement`, `ExecutionConfig`, `MigrateFunction`, `Git.IStatusFile`, `ResponsivePartialState`, `FetchEvent`, `SDPCandidateType`, `jest.CustomMatcherResult`, `IValidator`, `CodeMaker`, `AppConfiguration`, `$mol_atom2`, `LoginDTO`, `WithGeneric`, `ISerializedRequest`, `AnyError`, `IFragment`, `DatasourceRefType`, `PageImportExportTask`, `Symbols`, `TodoAction`, `LegacyReputationToken`, `AnimalType`, `SolveType`, `JPAFieldBlock`, `CircleObject`, `Char`, `ActionStatusResolverService`, `ISignerProvider`, `AccountFixture`, `ModelDefinition`, `CandidateInterviewService`, `Vuetify`, `LambdaOutput`, `Knex.CreateTableBuilder`, `ScanDb`, `ActiveTaskExtended`, `AngularExternalStyles`, `LineConfig`, `Story`, `FooterComponent`, `OscType`, `ModulusPoly`, `NewSpecPageOptions`, `RepoData`, `ActionListItem`, `ReactiveObject`, `Coord`, `RTCPeerConnectionIceEvent`, `RequestApprovalTeam`, `PlatformAccessory`, `_BinaryWriter`, `RoomObject`, `StackItemType`, `CucumberQuery`, `DeleteConnectionRequest`, `ImportIrecDeviceDTO`, `SeriesTypeOptions`, `RoomPayload`, `GitHubApi`, `MatchExpression`, `SpectatorServiceFactory`, `PerQuadrant`, `ExpShape`, `SecurityCCCommandsSupportedReport`, `MapToType`, `IFolder`, `TBookAuthorMapping`, `TestFixtureComponent`, `CompositionItem`, `ExportJob`, `CanvasSide`, `Nodes.Node`, `SimpleCondition`, `MediaWiki`, `_1.Operator.fλ.Stateless`, `MutationObserver`, `JSXElement`, `MdcSelect`, `ManifestCacheChangedEvent`, `TikTokConstructor`, `FlattenSimpleInterpolation`, `Rule.RuleModule`, `BasicTarget`, `HeftSession`, `FlameGraphNode`, `RemoveArrayControlAction`, `QueryAllProvidersAttributesRequest`, `ImportService`, `Methods`, `uint16`, `DescribeEventSubscriptionsCommandInput`, `p5.Color`, `requests.ListManagedInstanceErrataRequest`, `EngineType`, `IlmPolicyMigrationStatus`, `MultiFileRenderResult`, `VertexBuffer3D`, `ActionEffectPayload`, `LavalinkNode`, `UseFormReset`, `LyricFont`, `IConfigOptions`, `PlaceholderComponent`, `YaksokRoot`, `CollisionPartsFilterFunc`, `NetworkPolicy`, `MessageInterface`, `IOHandler`, `PortSet`, `IConfigurationModify`, `NavigationEdgeStatus`, `ExperimentPhase`, `StateInvocationParams`, `ComponentModel`, `Common.ILog`, `DOMElement`, `Octokit`, `BaseChannel`, `CodePoint`, `ReturnTypeFuncValue`, `TransactionFormSharedState`, `CancelParameters`, `IClock`, `IDocumentWidget`, `RootObject`, `Selectable`, `GetActionParams`, `SelectionDirection`, `ClusterRoleBinding`, `IButtonProps`, `BarcodeScannerOperationParams`, `IBundleWithoutAssetsContent`, `RsRefForwardingComponent`, `DateSkeleton`, `SessionManager`, `CT`, `ProofItem`, `YoganOptions`, `ContentTypeReader`, `SendMessage`, `ModelBuilder`, `Disposer`, `TRawComponent`, `IScript`, `IndoorMap`, `UpdateResult`, `ApolloReactHoc.OperationOption`, `AnimationGroup`, `ConvectorControllerClient`, `MatchModel`, `A8k`, `Optional`, `ElasticsearchResponseHit`, `PostConditionMode`, `CellData`, `ParsedTranslation`, `WithSubGenericInverted`, `ScreenDetailDto`, `ScreenshotConnectorOptions`, `PackageJsonFile`, `OverlayStart`, `DiskOptions`, `MockLink`, `postcss.LazyResult`, `data`, `Testing`, `UserPresence`, `JsonStringifierContext`, `TokenizerConfig`, `HostSettings`, `ValidTimeoutID`, `Exceptions`, `FIRVisionImage`, `CrudRepositoryCtor`, `JsonConfig`, `GrowableFloat64Array`, `IStorageProvider`, `StrategyOrStrategies`, `EditorSchema`, `WorldService`, `MutateResult`, `ChipDirective`, `ts.TypeAliasDeclaration`, `WorkspaceStructure`, `CompactInt`, `PropIndex`, `StringAtom`, `Tsa.SourceFile`, `CliOptions`, `QueryConditionOptions`, `ResultMapper`, `PedAppearance`, `ScrollView`, `Swiper`, `IExtentStore`, `AError`, `AnimatorControllerLayer`, `IInterceptor`, `SearchInWorkspaceRootFolderNode`, `EncodedDeviceType`, `CfnPolicy`, `NormalizedExtension`, `requests.ListLimitDefinitionsRequest`, `AntiVirusSoftware`, `UpdateUserSettingsCommandInput`, `SystemVerilogExportInfo`, `UseLazyQueryState`, `JMapIdInfo`, `R1`, `IRawStyle`, `Pathfinder`, `ProjectConfig`, `TestcaseType`, `GetMyOrganizationCommand`, `AppService`, `vscode.TreeItemCollapsibleState`, `Toolkit.IPluginExports`, `KeyPhrase`, `SkipListNode`, `SnsMetricChange`, `Actions`, `AddToCaseActionProps`, `Prose2Mdast_NodeMap_Presets`, `IChatMessage`, `TextCanvas`, `IDirective`, `CharacterMetadata`, `IRoot`, `SubcodeLine`, `ExceptionBlock`, `NDArray`, `TaskExecutor`, `Visualization`, `UrlTemplate`, `StateStorageService`, `DestructuringAssignment`, `SkipListSet`, `TypeDBOptions`, `DocumentLinkParams`, `STPPaymentHandlerActionStatus`, `XmlAttributes`, `RolandV60HDConfiguration`, `Export.DefaultInterface`, `QueryParams`, `ActorId`, `FilterFor`, `ShowModalOptions`, `DescribeSourceServersCommandInput`, `TConvData`, `InterceptorFn`, `RelationsInputType`, `RectLike`, `KeyStore`, `vscode.ViewColumn`, `MethodHandler`, `UnpackNode`, `LogAnalyticsParser`, `TelegramBot.Chat`, `MenuCardProps`, `CityBuilderStore`, `vile.YMLConfig`, `DevToolsNode`, `ISnapshotTreeEx`, `OrdersService`, `React.LegacyRef`, `Run`, `VnetGateway`, `TokenStorage`, `CategorySegment`, `d.CompilerFileWatcherEvent`, `BaseToken`, `RetryConfigurationDetails`, `StatusResponse`, `CardContextOptions`, `MarkEncoding`, `AbortController`, `FileQuickPickItem`, `AngleFromTo`, `Stitches.PropertyValue`, `AllState`, `NormalizedMessage`, `SymbolInfo`, `Releaser`, `OutputLocation`, `MessageTimer`, `Marker`, `MouseState`, `aws.S3`, `ArcTransactionResult`, `StringLiteralLike`, `IRegistryInfo`, `TSESTree.Identifier`, `BitcoinCashAddressFormat`, `VanessaTabs`, `ODataServiceFactory`, `UseMutationResponse`, `MyEditor`, `RequestInput`, `GroupChannel`, `AttrRewriteMap`, `CounterAction`, `ContractWrapperFactory`, `PathFilter`, `Skeleton_t`, `PatternLiteralNode`, `ExpressionsServiceSetup`, `RepoFrontend`, `AutoTranslateServiceAPI`, `PartType`, `MockContractFactory`, `PostConditionPrincipal`, `GraphEdges`, `NotificationService`, `PedigreeConstraint`, `ICategoricalStatistics`, `RuntimeCacheInterface`, `GlobalAction`, `IProcess`, `DisassociateFromMasterAccountCommandInput`, `apid.RuleId`, `DocsBinding`, `AnalysisOptions`, `BasePeerType`, `InjectableDependency`, `VcsFileChange`, `IMaterialAttributeOptions`, `DocumentInfo`, `RAFirebaseOptions`, `FilterCriteria`, `Facet`, `PromoteGroupUsersRequest`, `ConvLSTM2DArgs`, `CausalObjectStore`, `Z64LibSupportedGames`, `TextDiff`, `CinemaHallSeat`, `DateTimeFormatOptions`, `RestSession`, `ConvWithBatchNorm`, `MerkleTreeNode`, `RouteInfoWithAttributes`, `ENDProgram`, `UpperMainBelow`, `NodeFileSystem`, `IToaster`, `ts.BinaryExpression`, `QueueServiceClient`, `FieldData`, `TelemetryOptions`, `FromToWithPayport`, `PluginLoaderService`, `ParameterDesc`, `ValidResponses`, `DecodedData`, `TypeReferenceNode`, `PropertySignatureStructure`, `IHostedZone`, `SupportedLocale`, `WorkflowStep`, `Application`, `Arpeggiate`, `KernelFunc`, `UserCredentials`, `ShaderInstance`, `VectorSourceRequestMeta`, `JitMethodInfo`, `MESSAGE_ACTIONS`, `ArtifactDownloadTicket`, `LoginFieldContainer`, `TabbedAggRow`, `BezierSeg`, `SymString`, `Fog`, `NucleusChannel`, `DiffSelection`, `DocController`, `DocumentFilter`, `EditorController`, `StatusBarItem`, `DimensionRecord`, `ThemeOptions`, `BindingOrAssignmentElement`, `WalletAccount`, `DeployHelpers`, `TimelineState`, `Module`, `Vp9RtpPayload`, `StyleType`, `UIInterfaceOrientation`, `CustomRenderElementProps`, `MutableMatrix22`, `NotificationProps`, `JQueryDeferred`, `CreateChannelMessage`, `NotebookDocument`, `Modifiers`, `NodeJS.Platform`, `MockStorage`, `Audio`, `TaskRunnerFactoryInitializerParamsType`, `IDirectory`, `ColorInformation`, `UserPreferencesService`, `cc.Vec3`, `PoisonPayload`, `PrimitiveShape`, `IParseInstruction`, `SubcodeWidget`, `ResolveType`, `TabId`, `QueryFlag`, `CSSState`, `MActorLight`, `IGarbageCollectionData`, `HapticOptions`, `RouterStore`, `ParamData`, `AnimatorClassSettings`, `requests.ListCustomProtectionRulesRequest`, `AccountFacebookInstantGame_VarsEntry`, `Dockerode`, `SlotId`, `IYamlApiFile`, `MatCheckboxChange`, `VisibilityType`, `SendCommandOptions`, `BaseDirective`, `ButtonToolConfig`, `React.BaseSyntheticEvent`, `MessageOrCCLogEntry`, `StyleStore`, `IStageManifest`, `XY`, `ThingMetaRecord`, `AllowedNetworks`, `BaseVerifiableClaim`, `ITimeToSampleToken`, `OutdatedDocumentsSearchRead`, `PackageManagerCommands`, `SingleConfig`, `UseAsyncReturn`, `BaselineOptions`, `CreateApp`, `CertificateAuthorityRule`, `SonarQubeConfig`, `TabStorageOptions`, `TypeAttributeMap`, `CustomResponse`, `IPanel`, `GestureStateEventData`, `PackedTrie`, `PolyPoint`, `Compressor`, `DaffQueuedApollo`, `VideoObject`, `TerminalNode`, `ListenForCb`, `Writable`, `WorkTree`, `ChatPlugService`, `LiveObject`, `CardManifest`, `i32`, `IGetMembersStatistics`, `FileHashCache`, `Sorter`, `MapControlsUI`, `MsgUpdateDeployment`, `HubInfo`, `CategoryRecordsDict`, `CreateComponent`, `FormatProvider`, `ResultProps`, `ActivityStatus`, `CreateFileSystemCommandInput`, `WebpackType`, `WishListRoll`, `CliProxyAgent`, `FastFormContainerComponent`, `TypeChange`, `MatSnackBar`, `IClassicListenerDescription`, `FcEdge`, `AnnotationData`, `AFSReference`, `LocationData`, `IndTexMtx`, `ConditionalArg`, `Domains`, `FloorCode`, `DictionarySchema`, `CacheSnapshot`, `BottomNavigationViewType`, `ApolloServerPlugin`, `DeleteIPSetCommandInput`, `PresenceSync`, `CoreCompiler`, `Tnumber`, `SalesOrderState`, `RESTResponseDataType`, `TransliterationFlashcardFields`, `Stem`, `AccountKey`, `SlotAst`, `TaggedProsemirrorNode`, `wdpromise.Promise`, `Manifest`, `GroupHoldr`, `Electron.MenuItem`, `ODataStructuredType`, `DeserializeOptions`, `CardId`, `Ingress`, `QuadrantRow`, `DynamicMatcher`, `GridSize`, `VariableRegistry`, `CertificateSummary`, `OptionValues`, `ClientDetails`, `DtlsPlaintext`, `DeserializeWireOptions`, `GetCellValueFn`, `RootData`, `AFSQuery`, `ScopeManager`, `WalletInit`, `IHttpProvider`, `GfxTextureP_GL`, `Mass`, `YjsEditor`, `JPA.JPABaseEmitter`, `SearchResultsArtist`, `Pointer`, `ComponentConstructor`, `ILogger`, `_IType`, `VDocumentFragment`, `PyJsonValue`, `WalletAdapter`, `ResultError`, `Mars.TransactionOverrides`, `CommonLanguageClient`, `TestSettings`, `SVGCircleElement`, `ClassGenerics`, `TabsModel`, `OperatingSystem`, `LoggedInUser`, `Charset`, `ContractAbiDefinition`, `CircleDatum`, `SpecFiles`, `PlantProps`, `WidgetObject`, `SignedTx`, `SqlFragment`, `MiBrushAttrs`, `d.ComponentCompilerPropertyType`, `CodeNameDTO`, `ResolvedGlobalId`, `InternalPlugin`, `ISnapshotProcessor`, `AlertInstanceState`, `WebApi.JsonPatchDocument`, `GbBackendHttpService`, `PermissionResponse`, `ArchDescr`, `GeneratorSourceConfig`, `SRoutingHandle`, `InvalidNextTokenException`, `CreateCertificateDetails`, `ICommandResponse`, `UserInfoData`, `TokenSmartContract`, `TProduct`, `protocol.FileLocationRequestArgs`, `AlignItems`, `JSBI`, `StreamParam`, `EffectRef`, `RtkRequest`, `SchemaOptions`, `PBRStandardMaterial`, `RenderObject`, `ConstructorAst`, `PutDedicatedIpInPoolCommandInput`, `PlayerSubscription`, `ExpressionValue`, `DeleteWebhookCommandInput`, `React.ChangeEvent`, `BindingKey`, `TriangleFilterFunc`, `CryptoContext`, `basic.Token`, `RemoteDataBuildService`, `MessageAttributes`, `PossibleSelections`, `WalletOrAddress`, `VisibilityNotifier2D`, `OverridedSlateBuilders`, `ScopedPlannerConfiguration`, `NotificationRequestInput`, `ContextMessageUpdate`, `CreateAppInstanceAdminCommandInput`, `ConvertedRemoteConfig`, `MetricsServiceSetup`, `MemoizedSelector`, `IOptionalIType`, `ReferenceUsedBy`, `BoundsData`, `SavingsService`, `TargetProperty`, `Feed`, `ConstraintService`, `ANIME_DICT`, `Readonly`, `FinalConfig`, `ErrorProps`, `SVGPathFn`, `OrganizationPoint`, `StyledComponent`, `RGBColor`, `JSDocsType`, `ListFileStatResult`, `UploadFileOptions`, 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`AppenderConfigType`, `WKWebView`, `ThrottleOptions`, `That`, `Models`, `PreloadedState`, `io.SaveConfig`, `EntityStatus`, `FunctionFactory`, `DefaultApp`, `FindManyOptions`, `TurnClient`, `IModalContent`, `Events.initialize`, `MappingFn`, `FieldHierarchyRecord`, `JSXMemberExpression`, `IPropertyIdentValueDescriptor`, `MsgCloseLease`, `Permute`, `SymbolCategory`, `cwrapSignature`, `ImGui.U32`, `MockRequestParams`, `TSType`, `HashValue`, `nodes.Stylesheet`, `SparseMerkleTree`, `DeleteDatasetGroupCommandInput`, `SlotDefaultValue`, `TypedEventFilter`, `SocketOptions`, `MockPort`, `AsyncActionType`, `IEndExpectation`, `ObjectSet`, `WithGetterString`, `ts.Identifier`, `LogCallbackType`, `VersionMismatchFinderEntity`, `OutlineSymbolInformationNode`, `IDinoProperties`, `GridsterItemComponentInterface`, `IDatabaseDataActionClass`, `TagInformation`, `Opt`, `Poly`, `GraphRecord`, `GameModule`, `ImageryMapExtentPolygon`, `RuleId`, `DownwriteUIState`, `Components`, `ICheckAnalysisResult`, `PrincipalCV`, `WorkflowStateType`, `GridChildComponentProps`, `ConfigAccumulator`, `GraphQLRequest`, `EntityToFix`, `StorageMigrationToWebExtension`, `Responses.IViewContentItemResponse`, `primitive`, `TaroElement`, `ITsconfig`, `OpenDateRange`, `protocol.Location`, `Optimization`, `RtfDestination`, `Register64`, `GX.LogicOp`, `IntrospectionType`, `AuthorizationError`, `IOpenSearchSearchResponse`, `ResultNode`, `AttendanceStatusType`, `AccentColor`, `NumericNode`, `DynamoDB.DeleteItemInput`, `IFilters`, `SSAState`, `SessionStorage`, `S3.Types.PutObjectRequest`, `SettingOption`, `GroupSpec`, `OpenObject`, `Plan`, `TransportContext`, `CustomDialogOptions`, `WorkerContext`, `LocalState`, `EventSpy`, `ValueFormField`, `SymShape`, `BabelTarget`, `SectionsService`, `ExternalStyleCompiler`, `StringShape`, `TEvent`, `AntVSpec`, `requests.ListDbCredentialsRequest`, `RedAgateElement`, `NgSelectConfig`, `P2SVpnConnectionRequest`, `TemplateProps`, `ListTagsForResourceCommandInput`, `ControlBase`, `PluginMetrics`, `BindingWrapper`, `ITargetInfoProps`, `IORedis.Redis`, `ITaskLibrary`, `PuzzleState`, `CarService`, `PlanetPortalApplication`, `GitHubRepoData`, `vscode.WorkspaceConfiguration`, `VaultEntry`, `LiveEventSession`, `YieldNode`, `Defer`, `VisDefaultEditor`, `GUILocationProperties`, `ArrayFunc`, `Type_Interface`, `StepAdjustment`, `Nerve`, `AxisMilestone`, `FieldsSelection`, `ICompetitionDefault`, `ViewController`, `PaperProps`, `CstNode`, `SubsetConstraints`, `ApiTableData`, `TooltipContextValue`, `UseQueryResult`, `AggregateRowModel`, `StateT1`, `DFAState`, `NavigationItem`, `JsonDocs`, `CustomFilterArgs`, `Skin`, `PositionStrategy`, `IRenderData`, `CommentRequest`, `PluginExtended`, `StackLayout`, `ClientDTO`, `IAssetProvider`, `GraphQLServiceContext`, `py.Expr`, `DescribeRegistryCommandInput`, `StyledTextProps`, `IProjectsRepository`, `DescribeJobCommandInput`, `Pie`, `ISnapshot`, `Tuple`, `ApiV2Client`, `OriginGroup`, `RoomParticipantIdentity`, `ServiceDiscoveryPlugin`, `Webhooks`, `Tensor5D`, `BIP85`, `NgxUploadLogger`, `PartialResults`, `DAL.DEVICE_ID_SYSTEM_MICROPHONE`, `SVGLineElement`, `NgrxJsonApiStoreData`, `ConflictMap`, `AssetProps`, `IActivitiesGetByContactState`, `RegisterInput`, `Workunit`, `StaticArray`, `ActionObservations`, `InterventionTip`, `StaticSiteCustomDomainRequestPropertiesARMResource`, `StdlibRegistry`, `TinaFieldEnriched`, `ListRenderItem`, `AZSymbolInformation`, `IOriginConfiguration`, `SearchQuery`, `OpenSearchError`, `CreateTagsCommandInput`, `InternalMetric`, `MenuStateReturn`, `Dock`, `GunMsg`, `StateKey`, `PublishParams`, `RangeDelta`, `IamRoleName`, `ViewGroup`, `ResolverRelation`, `MarkdownNode`, `ViewModel`, `CreateDataAssetDetails`, `AwsShapes`, `FundedAward`, `ImageType`, `V1Pod`, `PackageDefinition`, `ModuleType`, `MonthViewProps`, `TreeItemCollapsibleState`, `CliCommandOptions`, `OperationHandlerPayload`, `BuildSourceGraph`, `SequentDescriptor`, `IUserDTO`, `DropdownMenuItemLinkProps`, `ScannedPolymerElement`, `GsTeam`, `ScreenMatrixPixel`, `Analyzer`, `HttpClientRequest`, `MediaFile`, `RowLayoutProps`, `requests.ListAutonomousDatabaseBackupsRequest`, `ComponentHost`, `ContentInfo`, `OnReferenceInvalidated`, `Errors`, `ChromeExtensionManifest`, `PubKeyType`, `GraphQLInputObjectType`, `ClassElement`, `T19`, `EventHint`, `MfaOption`, `ClusterCreateSettings`, `FieldsetContextProps`, `LayoutState`, `HistoryInteractionEvent`, `Themer`, `PresetType`, `requests.ListCachingRulesRequest`, `ManyApiResponse`, `Notebook`, `ConstructorOptions`, `$ResponseExtend`, `SelectFileModel`, `TsOptionComponent`, `ProcessService`, `DocService`, `IMovable`, `UserDoc`, `ClickHandler`, `Ball`, `Crosshair`, `CandleGranularity`, `LocalizedSteps`, `FlashbotsBundleProvider`, `OasOperation`, `RejectInvitationCommandInput`, `MethodHandle`, `AbiFunction`, `ProxyInfo`, `MaxAttrs`, `RuleDescriptor`, `OmitsNullSerializesEmptyStringCommandInput`, `PropOfRaw`, `MaterialOptions`, `K.BlockStatementKind`, 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`HsLaymanService`, `TextTrackCue`, `V1StepModel`, `PaginatedRequestOptions`, `WatchOptions`, `AzureFirewall`, `DiscogsTrack`, `IndexerManagementClient`, `IOnSketchPreviews`, `RenameInfo`, `ApiToken`, `XMLAttribute`, `LoopBounds`, `RawDoc`, `MultiTrie`, `Relayer`, `LemonTableColumns`, `ColorStyle`, `ParsedAccount`, `ICollectItem`, `SyntaxError`, `InputParamMapper`, `ICfnFunctionContext`, `DropTarget`, `ForwardingParams`, `PluginStorageKind`, `CreateIndexBuilder`, `HubUtility`, `IFrontendDomChangeEvent`, `TestDirectEscrow`, `ICoreMouseEvent`, `ListAvailabilityDomainsResponse`, `StylesMap`, `SimControlLog`, `HdmiInput`, `Staking`, `HumanData`, `DocumentSymbolProvider`, `Events.preupdate`, `AggsCommonStartDependencies`, `LedgerTransport`, `t.SourceLocation`, `OpenDialogReturnValue`, `NodeAttributes`, `IComponentWithRoute`, `Attachment`, `GetDedicatedIpsCommandInput`, `StatementNode`, `SysUser`, `InputActionMeta`, `AdamaxOptimizer`, `GfxInputState`, `Path2`, `ILineGeometry`, `TT.Level`, `BasicSourceMapConsumer`, `TableNS.RowProps`, `requests.ListAutoScalingConfigurationsRequest`, `QuickPick`, `DietForm`, `F3DEX_Program`, `StoreGetter`, `IStepAdjustmentView`, `BaseShrinkwrapFile`, `IApplicationShell`, `TLang`, `UnionMemberMatchTransformer`, `PluginTransformResults`, `picgo`, `IdentityDictionary`, `numVector`, `Constant`, `Query`, `ServerStatus`, `pxt.Map`, `DropData`, `TallySettingsIni`, `Journey`, `CharacterCreationPage`, `GetDomainNamesCommandInput`, `SpatialCategory`, `GetAdministratorAccountCommandInput`, `FirestoreUserField`, `IBaseComponent`, `SQLParserVisitor`, `MIREntityTypeDecl`, `Structure`, `SaveFileArgs`, `ABN`, `StringLocation`, `ValidationParams`, `UsersService`, `LinkService`, `HTMLTableHeaderCellElement`, `Archiver`, `IStorageSchema`, `MouseService`, `Order2Bezier`, `Packages`, `ContentLinesArrayLike`, `EpicTestMocks`, `JSDefinitionNode`, `InsertQueryBuilder`, `RadSideDrawer`, `LatLon`, `TAccesorData`, `ReadonlyDeep`, `StoreItem`, `ServerRoute`, `AppxEngineActionContext`, `TransactionQueryPayload`, `ImageTexture`, `SubmissionObject`, `IAuthorizer`, `Widgets`, `BudgetGroup`, `MultilevelNode`, `DesignerVariable`, `requests.ListPublicationsRequest`, `KeyFrame`, `ControlDirective`, `Accessor`, `ZWaveController`, `MigrationService`, `Loading`, `RequestPolicyOptionsLike`, `SwapEncoder`, `Papa`, `NoteStateWithRoot`, `DIContainer`, `TestGroup`, `CardDatabase`, `EmittedObject`, `TMetricAggConfig`, `VideoConverter`, `PointerButton`, `IUserProfile`, `AsyncModuleConfig`, `IDebugProvider`, `ElTreeModelData`, `ActivityTimeSeriesMetrics`, `StartPoint`, `DetectedFeatures`, `GameTreeNode`, `AuthOptions`, `Budget`, `ISummaryHandle`, `Guide`, `BackendTimingInfo`, `PostResult`, `DaffCartItemInput`, `IMrepoConfigFile`, `CourseDuration`, `MavenTarget`, `IWhitelistUser`, `KeyboardEventToPrevent`, `RateLimitOptions`, `AreaPointItem`, `AccountResource`, `UntagResourceCommandInput`, `pulumi.ResourceOptions`, `ShoutySession`, `ListBackupsRequest`, `Big`, `d.HostElement`, `CdsInternalPopup`, `MccScrollspyGroup`, `EnrichedPostageBatch`, `BasicLayoutProps`, `UseQueryStringProps`, `GridGraph`, `TopNavigationEntry`, `Vnode`, `InsertContentDOM`, `CompletionOptions`, `DeleteGroupRequest`, `PushToServiceResponse`, `requests.ListIncidentResourceTypesRequest`, `PieceSet`, `ConverterFunction`, `ImageDefinition`, `CompositeContentBuilder`, `Migrate`, `ValidationSchema`, `RatingProps`, `NestedDict`, `LinksList`, `UserId`, `ComboBoxGroupedOptions`, `CommandRegistry`, `PrimaryKeyOptions`, `ElkNode`, `JSONTree`, `StreamResetResponseParam`, `UseMutationReducerAction`, `SchemaTypes`, `DrawingNode`, `SpeedDialItem`, `ELULayerArgs`, `QueryOrderMap`, `CoordinateConverter`, `MissingFilter`, `Reducer`, `RippleRef`, `CreateTaskCommandInput`, `IFunctionParameter`, `CurveVector`, `IDisposable`, `TileMatrixType`, `MyPromise`, `DeleteResourcePolicyCommandInput`, `TTarget`, `EdgePlaceholder`, `express.Response`, `DbTokenMetadataQueueEntry`, `Jsonp`, `MVideoThumbnail`, `JSDOM`, `ApplicationConfigService`, `Restangular`, `ListTagsForResourceResponse`, `FleetRequestHandler`, `ExtendedMesh`, `ChangeEvent`, `ReportParameter`, `UseCaseBinder`, `DeadLetterConfig`, `Vector3_`, `Cross`, `PolylinePoint`, `ActionExecutionContext`, `ProjectsService`, `ClarityAbiType`, `FieldDoc`, `PsbtTxOutput`, `OwnerItemT`, `RangeError`, `DataPromise`, `GhcModCmdOpts`, `ts.ReturnStatement`, `ProtoPos`, `CsvInputOptionsNode`, `ITokensState`, `Seed`, `InputStyleProps`, `ChartDataset`, `VerifiableClaim`, `TSetting`, `UpdateApplicationResponse`, `OneToManyOptions`, `FabricGatewayRegistryEntry`, `MessageOption`, `SessionProposal`, `HookConfig`, `SubmissionQueueItem`, `LS.CancellationToken`, `WebGLVertexArrayObject`, `ReAtom`, `SharePlugin`, `PendingUpdateDetails`, `ApplicationConfigState`, `d.OutputTargetDocsJson`, `Panel`, `Visitors`, `JieQi`, `MonzoAccountResponse`, `DirectoryEntry`, `SyntaxType`, `CreateEntrypoint`, `IndexFileInfo`, `ServicesState`, `FnReturnType`, `StynTree`, `AnalyicsReporterConfig`, `QWidget`, `MlCommonUI`, `PlaneByOriginAndVectors4d`, `ExpressLikeStore`, `Flicking`, `UserManagerInstance`, `GitHubIssueOrPullRequest`, `GethInstanceConfig`, `DashboardContainerOptions`, `StreamID`, `TimelineRecord`, `TextDocumentRegistrationOptions`, `GeoService`, `Book`, `WalletManager`, `CoreTracer`, `alt.RGBA`, `UIImage`, `AnyRouter`, `WatcherFactory`, `ProcessResult`, `PluginModule`, `common.ConfigFileAuthenticationDetailsProvider`, `UploadOptions`, `LocalizationProviderProps`, `address`, `HTMLTableCellElement`, `MenuProps`, `ITwin`, `GtConfigSetting`, `FormikActions`, `code.Uri`, `PluginManager`, `UserReport`, `OptimizationPass`, `MActorId`, `ITimelionFunction`, `requests.GetJobLogsRequest`, `AutoImportResultMap`, `CardContentProps`, `IFirmwareCodePlace`, `CreateGrantCommandInput`, `Lyric`, `DaffCategoryFilterEqual`, `IconButtonProps`, `apid.BroadcastingScheduleOption`, `TelemetryData`, `XYZStringValues`, `AcornNode`, 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`UpdateFilterCommandInput`, `JoinNode`, `TeamsState`, `PolicySummary`, `ResourceKey`, `TaroNode`, `MDCMenuFoundation`, `BatchValidator`, `serialization.SerializableConstructor`, `MutationRecord`, `When`, `OpenBladeInfo`, `PromiseRequest`, `MetricDataPoint`, `SpaceType`, `PaletteRegistry`, `IAccountProperties`, `IntCV`, `LibraryNotificationAction`, `UI5XMLViewCompletion`, `OpenApiDocumentRefs`, `PageAPIs`, `Guard`, `ObjectStore`, `ResolveCallback`, `PropertyCategoryRendererManager`, `core.IThrottler`, `UITextView`, `IEmail`, `IFilterItemProps`, `BoxCollisionShape`, `ts.ImportDeclaration`, `HDNode`, `ImageVideo`, `PathEdge`, `UpdateOrganizationConfigurationCommandInput`, `ListCardContent`, `NZBAddOptions`, `LeafNode`, `ClarityType`, `PutResourcePolicyCommandInput`, `GroupedFields`, `Conditional`, `IStorageScheme.IStorage`, `ProjectGraph`, `AppEventsState`, `IGeometryAccessor`, `IMdcChipElement`, `AssociationGroupInfoCCInfoGet`, `ISets`, `GraphQLFormattedError`, `DocSourceFile`, `IZipEntry`, `ESLScreenBreakpoint`, `GraphicUpdateResult`, `FirebaseUser`, `ICharacteristic`, `DocumentError`, `HTMLFormElement`, `Block`, `AstEditorProps`, `MeterCCReset`, `ComponentStory`, `GroupItem`, `TaggingInfo`, `CoreSetup`, `UAProxyManager`, `server.Diagnostic`, `LiveEventMessagingService`, `KeyboardEventHandler`, `ParquetData`, `THREE.Object3D`, `TableColumnWidthInfo`, `IMusicDifficultyInfo`, `Applicative2C`, `IImageConstructor`, `CaptionSelector`, `AxisTick`, `Event`, `ClusterMetadata`, `CardBrand`, `FileTrackerItem`, `IGraphDef`, `GraphNode`, `ISessionContext`, `findUp.Options`, `ComponentResult`, `Discord.GuildMember`, `SnackbarState`, `DeclarationMapper`, `ChangesetFileProps`, `ComponentTag`, `PersonFacade`, `ListObjectsRequest`, `Tsoa.Method`, `TTypescript.ParsedCommandLine`, `PutPermissionPolicyCommandInput`, `FieldConfiguration`, `WolfState`, `TestResponse`, `PlayerPageSimulation3D`, `UAMethod`, `JsonSchemaDataType`, `Mock`, `ScmDomain`, 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`ThemeColorState`, `ErrorData`, `ExadataInfrastructureContact`, `vscode.MessageItem`, `GetRotation`, `VendorType`, `Globals`, `CustomSpriteProps`, `IMatrixCell`, `IdentifierObject`, `FunctionFallback`, `ActivationLayer`, `PlayingState`, `DebugProtocol.StepOutArguments`, `AliasMap`, `ObservableLanguage`, `CSSRule`, `FieldErrors`, `ParsedRoute`, `PutResourcePolicyCommand`, `ContainerForTest`, `RequestResult`, `SelectDropdownOption`, `JsonResponse`, `V1Namespace`, `MethodMap`, `DynamoDB.DocumentClient`, `MlContextValue`, `GraphConfiguration`, `IUserSubscription`, `EthTxType`, `DaffCartPaymentFactory`, `IgnoreQueryParamsInResponseCommandInput`, `Shuriken`, `ScopedClusterClientMock`, `Highcharts.PolarSeries`, `IRNG`, `Atomico`, `Kafka`, `PlansState`, `LoginResult`, `ViewCell`, `VerticalAlignments`, `IRuleCheck`, `TextDocumentChangeEvent`, `DefaultInputState`, `LedgerWalletProvider`, `ARCamera`, `PDFField`, `ActionSheetProps`, `MangleOptions`, `WebdriverIO.Browser`, `PureIdentifierContext`, `IGroupItem`, `OrganizationInterface`, `VoiceServerUpdate`, `SettingsService`, `QueryHints`, `DefaultState`, `MemFS`, `ResolvedEntitySchema`, `IOObjectSet`, `Research`, `Semigroup`, `MacroInfo`, `UnderscoreEscapedMap`, `MeshVertex`, `okhttp3.WebSocket`, `LoadEvents`, `SignedToken`, `MockWebSocket`, `IAnimationState`, `UpdateSecurityProfileCommandInput`, `ConfigurationOptions`, `ListSecretVersionsRequest`, `Ppu`, `UpdateContactCommandInput`, `VarAD`, `AppABIEncodings`, `CloseChannelParams`, `TranslatePipe`, `CdkDropList`, `q.Tree`, `GraphQLSubscriptionConfig`, `IOContext`, `UseSubscription`, `SNode`, `Observation`, `ParamConfig`, `types.IAzureQuickPickOptions`, `MyNFT`, `CompletedGatewayOptions`, `ContactsProvider`, `functions.storage.ObjectMetadata`, `DateOrString`, `AbstractMethod`, `Response`, `ComponentCommentIterator`, `DocumentRegistry.IContext`, `StartPlugin`, `River`, `FoamTags`, `TextType`, `EElementSignature`, `IAnimationOptions`, `Heading`, `JobNumbered`, `IMQRPCRequest`, `ChangeTheme`, `UIFill`, `MagentoOrder`, `EditableContent`, `MetaValue`, `clientSocket`, `MatchedStory`, `FileSystemEntryKind`, `Scroll`, `IKeyboardInput`, `PreprocessorGroup`, `NewableFunction`, `IGherkinLine`, `UpSetQueries`, `IElementColors`, `MdcChipSet`, `Unsub`, `JobRunLifecycleState`, `CBCharacteristic`, `IQueryProps`, `DefaultTextStyle`, `CancelTokenStatic`, `ExpShapeConcat`, `ErrorObject`, `ng.IHttpService`, `VariableDefinition`, `SelectDownshiftRenderProps`, `RelationshipProps`, `ContentState`, `ScannedProperty`, `ListTableRowsCommandInput`, `MessageCollector`, `FilterEntity`, `RendererNode`, `CrudRequest`, `ResolverData`, `ViewContainerTitleOptions`, `CommentItem`, `ContainerSample`, `StreamMetricReport`, `TransactionModel`, `ISiteScriptActionUIWrapper`, `OpaqueToken`, `CertificateSummaryBuilder`, `Files`, `PlanInfo`, `TabularDataset`, `nanoid`, `CallbackObject`, `TraitLocation`, `Element`, `Apps`, `CalculatedTreeNode`, `AccountService`, `PluginStrategy`, 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`ReadonlyTuple`, `PaginationServiceStub`, `IGridColumnFilter`, `CopySnapshotCommandInput`, `AnimeNode`, `APIGateway`, `MergeTreeChunkV1`, `LroImpl`, `d.OutputTargetDocsReadme`, `SubmittableExtrinsic`, `DismissedError`, `GraphNodeID`, `MultisigItem`, `ClientSessionEntryIded`, `ObservableConverter`, `DeleteChannelModeratorCommandInput`, `RebaseResult`, `RootScreenDelegate`, `peerconnection.PeerConnection`, `MySQL`, `ImmutableAssignment`, `Connector`, `AppEpic`, `ObjectIdentifier`, `CustomConfigurationProvider`, `OutgoingStateType`, `MetricsModel`, `AuditedAttributes`, `PaperAuthor`, `TournamentList`, `ValidationRules`, `LiveSelector`, `SmallMultiplesGroupBy`, `BlobCreateSnapshotResponse`, `TestFunctionImportEntityReturnTypeParameters`, `NodeObject`, `ConsumeMessage`, `AuthRouteHandlerOptions`, `RadioOption`, `IPluginsContext`, `PrimitiveBundle`, `FoundationElementDefinition`, `IEventData`, `VisEditorOptionsProps`, `StructureRampart`, `ServerIdentity`, `IconifyElement`, `SequencePatternInfo`, `GitContributor`, `UsePreparedQueryOptions`, `settings.Settings`, `RatingPair`, `FieldTemplateProps`, `FieldArrayRenderProps`, `mod.LoadBalancerTarget`, `PopupInfo`, `LogType`, `DocumentSymbolParams`, `Metadata_Item`, `STColumnFilter`, `KVNamespace`, `DataRecognizer`, `FullConfig`, `TypedDataDomain`, `EntryList`, `ITokenService`, `EthereumCommon`, `LineSegments`, `BaseConverter`, `ToastItem`, `NameObjExecuteInfo`, `ESTree.MemberExpression`, `DomainSummary`, `DeleteGlobalClusterCommandInput`, `ProgressBarProps`, `CacheNotifyResult`, `GridLineStyle`, `InternalInstanceState`, `L2Item`, `ReadModelReducerState`, `IContent`, `AccountRepository`, `d.EmulateConfig`, `ExecutionScopeNode`, `IQueryParameter`, `IFieldOption`, `MenuController`, `Wine`, `Bindable`, `PhysicalObject`, `RawOptions`, `ColorPresentationParams`, `IEnvironmentRead`, `Identity`, `PolicyStatement`, `scriptfiles.ASScope`, `TimePeriod`, `SortConfig`, `MemoryStorage`, `AutocompleteProps`, `BuildTarget`, `Heightfield`, `UserMetadataStore`, `Bals`, `ParserInput`, `DaffCategoryFilterToggleRequestEqualFactory`, `YamlMap`, `SchemaEnv`, `RefactorContext`, `DetectionResult`, `IClusterClient`, `TypeAttributes`, `BaseDbFieldParams`, `Angle`, `TypeParameterReflection`, `MooaApp`, `fabric.IObjectOptions`, `ComponentFactory`, `ReplayTabState`, `RE`, `CustomLink`, `FieldArgs`, `PermissionContext`, `ColumnComponent`, `WindowRef`, `UnitsMap`, `StepOption`, `Renderer3`, `TypeApp`, `LogAnalyticsMetric`, `ICollectParms`, `OnboardingOpType`, `IntervalScheduler`, `AdvancedDynamicTexture`, `DataLoader`, `MonitorCollection`, `SafeElementForMouse`, `ResizeInfo`, `BiKleisli`, `Plugins`, `IAsset`, `firestore.QueryDocumentSnapshot`, `AudioVideoController`, `NavNode`, `ModalOptions`, `RuleContext`, `InsightType`, `DescribeEventsRequest`, `CommandExecutor`, `AccountID`, `CreateCertificateResponse`, `CreateClusterRequest`, `CellInput`, `ObservableHash`, `AsyncProcessingQueue`, `WStatement`, `GSMemoryMap`, `RSS3Index`, `SplitCalculator`, `ExchangePriceRepository`, `IPublicKey`, `Fn2`, `ManifestLoader`, `ILinkWithPos`, `ParsedFile`, `SiteStatus`, `PopoverStateReturn`, `listOptions`, `TraverseFunction`, `PageBlockRule`, `ContractDeployer`, `ToasterService`, `ethers.ethers.EventFilter`, `TypeContext`, `InMemoryFileSystemHost`, `FragLoaderContext`, `IEntry`, `DropletInfo`, `FactEnvelope`, `DotenvConfigOutput`, `SparseMerkleTreeImpl`, `Table2`, `ThreadData`, `IExecuteCommandCallback`, `AxisCoordinateObject`, `GetWorkRequestResponse`, `LayoutFacade`, `InterceptorManager`, `response`, `TokenFactory`, `ERC20Value`, `TrackGroup`, `TypeTemplates`, `TaskPool`, `CliCommandExecution`, `FunctionExpression`, `CkElement`, `IAtomHeader`, `SerializedConsoleImpl`, `FunctionDocumentation`, `EventType`, `capnp.List`, `ErrorBoundaryState`, `DummyTokenContract`, `MemoString`, `IPlan`, `TDataProvider`, `LocalProxiedEntry`, `ModuleMap`, `IStorages`, `AlertId`, `Types.RequestParameters`, `PerSignalDetails`, `TestRun`, `PassImpl`, `HubConnection`, `IBucket`, `DummyResolver`, `ISceneConfiguration`, `MVideoAccountLight`, `DashboardContainerInput`, `RematchStore`, `Align`, `P2PResponsePacketBufferData`, `ObservableFromObject`, `AddSchema`, `CRC16CCCommandEncapsulation`, `TransientGraphUtility`, `Experiment`, `RenderProps`, `QueryPrecedenceCommandInput`, `DebugProtocol.Response`, `GlobalsService`, `ShoppingCartService`, `MapboxGL.Map`, `ICandidateInterviewersCreateInput`, `StatusType`, `Preimage`, `CommunicationIdentifier`, `Fixtures`, `HTMLIonAccordionElement`, `CoreType`, `RequestHandlerParams`, `Span_Event`, `ButtonSize`, `UriLocation`, `SegmentHandler`, `AbbreviationMap`, `IDataPoint`, `RawProcess`, `ObjectPredicate`, `SankeyNode`, `SkipOptions`, `IocContext`, `requests.ListAccessRulesRequest`, `requests.ListAddressListsRequest`, `TooltipPosition`, `ExchangePriceRecord`, `TasksPluginReminderModel`, `FundedAwardModel`, `ResponsiveState`, `LmdbDbi`, `ConfigurationCCSet`, `ts.WhileStatement`, `GetRoomCommandInput`, `Orders`, `ArticleService`, `NodesRef`, `Pokemon`, `SpatialImageEnt`, `CustomersState`, `ZipIterator`, `ParameterInjectInfoType`, `OutlineManualServerEntry`, `React.ErrorInfo`, `ValueSuggestionsGetFnArgs`, `InstallerMachineContext`, `NotNeededPackage`, `RedBlackTree`, `OgmaPrintOptions`, `MemberInfo`, `SetupParams`, `ValueOrPromise`, `IPointPosition`, `PuppetRoomJoinEvent`, `VNodeWithAttachData`, `TooltipOperatorOptions`, `MarkdownView`, `WebStandardsDashboard`, `Collection`, `UserDataStore`, `EnvironmentVariables`, `PropertyFilter`, `CmbData`, `ConsoleSidebarLink`, `StatsCompilation`, `TransactionData`, `ManagedHsm`, `IGceDisk`, `WorkspaceDefinition`, `VisibilityFilter`, `TransactionEndedPayload`, `TAccessor`, `Material_t`, `QueryableFieldSummary`, `Enzyme.ShallowWrapper`, `CameraControllerClass`, `ZoneAndLayer`, `IAuthentication`, `R`, `WithGenerics`, `DynamoDbWrapper`, `MUST_CALL_AND_RETURN_SUPER_METHOD`, `UserVariableContext`, `ISharedDirectory`, `ServerDataImportStore`, `AsyncIterableIterator`, `TransientStore`, `RefreshTokenEntity`, `ContributorService`, `IChoice`, `SinonSandbox`, `ButtonColors`, `$RequestExtend`, `ClientInfo`, `AwsState`, `FunctionCallValue`, `GoToLabelProps`, `DeleteWriteOpResultObject`, `AssignmentNode`, `D2`, `Attribute.JSON`, `DxModelContstructor`, `RawDraftContentBlock`, `ContextMenuAccess`, `Paginate`, `PathMatcher`, `_ITable`, `p5ex.ShapeColor`, `ValueEdge`, `ApiTypes.UploadLinkRequest`, `language`, `IGetOptions`, `Plugin.Shared.Definition`, `LogicalExpression`, `ParserSourceFileContext`, `MyContext`, `QueryArg`, `StreamPipeOptions`, `JestEnvironmentGlobal`, `SyncSubject`, `NameSpaceInterfaceImport.Interface`, `ODataOptions`, `MathToSVGConfig`, `IHubContent`, `express.Application`, `NgxSmartLoaderService`, `TableRow`, `LoadingEvents`, `AutocompleteSelectCellEditor`, `Accessibility.SeriesComposition`, `UserRegister`, `ComponentStatus`, `IAstBuilder`, `TwilioServerlessApiClient`, `BitcoinjsKeyPair`, `ItemController`, `DaffCategoryFilterEqualOption`, `VerifyErrors`, `OutputDataSource`, `ModbusTransaction`, `NodeAndType`, `KanjiNode`, `TypedObject`, `Concept`, `CarSpec`, `DidChangeTextDocumentParams`, `SensorObject`, `IExecutionQueue`, `IOrganizationCreateInput`, `LogProperties`, `DirectoryResult`, `Pouchy`, `ContainerModel`, `requests.ListQuotasRequest`, `UseLazyQuery`, `CanvasTexture`, `PointerEventInit`, `UserAdministrative`, `ClarityAbiFunction`, `ICreateSessionOptions`, `QueryStart`, `FormService`, `ValidationFn`, `MetaTransaction`, `Parameterizer`, `Oracle`, `ColorDirection`, `ISelectedEmployee`, `BudgetItem`, `Physics2DServer`, `MatSlideToggleChange`, `SendTransactionOptions`, `IDialogConfiguration`, `UserAuth`, `ConcreteTaskInstance`, `FlatNode`, `ScrollEventData`, `SimpleToast`, `HeaderMapTypeValues`, `Throttler`, `SetInstallPrompt`, `ActivityItem`, `XI18nProperty`, `VertexLabels`, `CanaryExecutionResult`, `SelectionScopeRequestOptions`, `Required`, `VirtualNetworkGateway`, `WaterfallStepContext`, `T.Component`, `NumberRange`, `Deno.Addr`, `AnnotationService`, `EqlCreateSchema`, `StyledElementLike`, `BitcoinStoredTransaction`, `monaco.languages.IState`, `dia.Element`, `RoutesService`, `TKind`, `BigIntInstance`, `InfluxDB`, `CustomWorld`, `ErrorTypes`, `HistoryItemImpl`, `MlJobWithTimeRange`, `workspaces.WorkspaceDefinition`, `CollectDeclarations`, `ArXivStorage`, `k8s.types.input.core.v1.PodTemplateSpec`, `SettingsRepository`, `SessionStateControllerTransitionResult`, `BlockStatement`, `GetSampledRequestsCommandInput`, `Auto`, `InitializeSwapInstruction`, `HalfEdge`, `TwingTest`, `MockEvent`, `ConfigState`, `CheckSavedObjectsPrivileges`, `Guid`, `Spinner`, `RootSpan`, `TableAliasContext`, `requests.ListAvailableWindowsUpdatesForManagedInstanceRequest`, `PersistedStateKey`, `StructureNode`, `ListNotificationsRequest`, `EvaluateCloudFormationTemplate`, `UpdateProjectCommandInput`, `DemographicsGroup`, `ComboBox`, `requests.ListScheduledJobsRequest`, `CommandInterface`, `UpdateWriteOpResult`, `By`, `FilePickTriggerProps`, `WalkResult`, `Orderbook`, `AbstractCamera`, `CheckRun`, `t.Expression`, `FocusEvent`, `ThemeState`, `IBoxProps`, `RenderView`, `DeployUtil.ExecutableDeployItem`, `DataViewComponentState`, `StoreCreator`, `MergeTree.TextSegment`, `IAlert`, `SettingEntity`, `MyClass`, `BIterator`, `ITimerToggleInput`, `Newsroom`, `EncryptedShipCredentials`, `XTransferSource`, `DataId`, `CalendarDateInfo`, `DaffCartItem`, `LocalPackageInfo`, `MVideoFullLight`, `SparseVec`, `WebGLRenderingContext`, `UserAnnotationSet`, `InternalCoreUsageDataSetup`, `MappingsEditorTestBed`, `CmsGroup`, `Launcher`, `MyEThree`, `listenTypes`, `ICoverageCollection`, `ListJobsByPipelineCommandInput`, `AndroidActivityBackPressedEventData`, `ThemeService`, `ActivityFeedEvent`, `ControllableEllipse`, `BMapGL.Point`, `DescribeConnectionsCommandInput`, `TitleProps`, `AfterCombatHouseCardAbilitiesGameState`, `ContractData`, `ChangeMap`, `IBlockchainProperties`, `AuthorizeOptions`, `FunctionContext`, `EnvelopeListener`, `Events.kill`, `ora.Ora`, `RepositoryStateCache`, `Justify`, `ShapeInstanceState`, `QuickInputButton`, `DeleteRepositoryResponse`, `WFWorkflow`, `CallOptions`, `MaybeType`, `OptionsWithMeta`, `QueryDefinition`, `DatabaseTransactionConnection`, `CollectionTransaction`, `FirstConsumedChar`, `IndexingConfig`, `FieldFilter`, `WyvernSchemaName`, `DinoContainer`, `FakeCard`, `UpdateAccountRequest`, `AstVisitor`, `UpdateDeploymentCommandInput`, `ClassSymbol`, `files.FullFilePath`, `StylableResolver`, `JsonDocsMethod`, `Draft`, `ColorString`, `CoreSavedObjectsRouteHandlerContext`, `LexDocument`, `PartyLeader`, `TabularLoaderOptions`, `LegendItem`, `DataTable.CellType`, `ir.Stmt`, `IParameterTypeDefinition`, `GfxTexture`, `TextEditChange`, `ICloudFoundryCreateServerGroupCommand`, `IntersectParams`, `Views.View`, `INgWidgetPosition`, `IUpworkDateRange`, `IDeviceInterface`, `GetFieldsOptions`, `ChatModule.chatRoom.ChatPubSubMessage`, `ConventionalCommits`, `GameStateModel`, `BuildFailure`, `CreateIndexNode`, `IDescriptor`, `FieldParser`, `CompilerIR`, `EventDispatcherEntry`, `RemoveSourceIdentifierFromSubscriptionCommandInput`, `IChange`, `IUpdateOrganizationCommandArgs`, `VirtualElement`, `LoaderService`, `ast.AbstractElement`, `SpriteSheet`, `RequestApprovalEmployee`, `GraphQLQueryBuilder`, `DialogContextValue`, `CachedProviders`, `EventFilter`, `ESLAnimateConfigInner`, `TokenizerOutput`, `AccessToken`, `MyUnion`, `RtcpHeader`, `EvaluationFunction`, `Comparer`, `dom.Node`, `React.Context`, `FlowsenseCategorizedToken`, `IndyLedgerService`, `MediatorMapping`, `DSpaceObjectDataService`, `DatabaseFacade`, `ExternalAuthenticateResultModel`, `ListApplicationsRequest`, `Monoid`, `TikTokScraper`, `RouteLocationNormalized`, `SpriteEffect`, `InstalledPlugin`, `ThySlideService`, `StorageTransformPlugin`, `SwitchIdInfo`, `IHash`, `ColumnExtension`, `OriginConnectionPosition`, `StatefulSearchBarDeps`, `Cancellation`, `CommandDescriptor`, `GameVersion`, `AddAsTypeOnly`, `XMLBuilderState`, `IOrganizationVendor`, `XPath`, `JitsiLocalTrack`, `TestFunctionImportComplexReturnTypeCollectionParameters`, `CohortCreationState`, `RelativeTimeFormatOptions`, `TokenBurnV1`, `ServiceStatusLevel`, `ChapterStatus`, `QueryCacheEntry`, `J3DLoadFlags`, `CreateTRPCClientOptions`, `GridCellValue`, `IMyChangeRequestItem`, `IServerResponse`, `OrSchema`, `DecltypeContext`, `IObjectDefinition`, `ViewPortService`, `MAL`, `TSPass`, `NzDestroyService`, `DeploymentTargetConfig`, `coord`, `HostCreatedInstance`, `ITestState`, `ResourceRequirement`, `TReference`, `ParserPlugin`, `ResEntry`, `IssuesListCommentsResponseItem`, `FixedTermLoan`, `LiftedStore`, `RuleExpr`, `AnimationKeyframe`, `WgConfigFile`, `WalletKeys`, `nodenCLContext`, `FilterProps`, `ts.ScriptTarget`, `Subscribable`, `IAuthContext`, `NodeWithPos`, `SanitizedProtonApiError`, `IVSCodeWebviewAPI`, `OrderImpl`, `INumberFilter`, `BeancountFileService`, `ScaleString`, `DayHeaderWrapper`, `ListPortalsCommandInput`, `YAMLMap`, `TransactionConfig`, `IDetachable`, `TsConfigSourceFile`, `IRedisOptions`, `UI5SemanticModel`, `PlanGraph.Entities.GraphData`, `CustomTag`, `MaxVersions`, `BeButtonEvent`, `PrivateKey`, `ShowNewVisModalParams`, `SelectorFn`, `NodeEvaluateResult`, `RequesterMap`, `FsUri`, `NameIdentifier`, `Spatial`, `tf.io.TrainingConfig`, `IConnectionInfo`, `Font`, `XYZSizeModeValues`, `MessagingPayload`, `AvailabilityZone`, `XMessageService`, `AsyncSettings`, `CreateConfigurationSetEventDestinationCommandInput`, `HTMLProgressElement`, `ImmutableMap`, `DAL.DEVICE_NULL_DEREFERENCE`, `ConnectionPositionPair`, `Associativity`, `ParameterDetails`, `PaymentOpts`, `Any`, `requests.ListBootVolumeAttachmentsRequest`, `PathMatch`, `SearchInWorkspaceWidget`, `Idea`, `WrappingCode`, `message`, `ClassMemberLookup`, `FsReaddirItem`, `GuildChannel`, `AngularFirestoreCollection`, `ITelemetryLoggerPropertyBags`, `SubtleCrypto`, `ExpressionContainer`, `CreateStateHelperFn`, `HookHandler`, `DefinitionYAMLExistence`, `IEntityGenerator`, `Incoming`, `parser.Node`, `Xform`, `CircularQueue`, `OpenCommand`, `Dree`, `PostgresInfo`, `LabelProvider`, `MssEncryption`, `ProgramOptions`, `TransformNode`, `NavigationGraphicsItem`, `SinglePointerEvent`, `IFabricEnvironmentConnection`, `IRoomData`, `requests.ListComputeGlobalImageCapabilitySchemasRequest`, `TensorContainer`, `TargetDetectorRecipeDetectorRuleSummary`, `d.RobotsTxtResults`, `ContextFlags`, `IModelContentChangedEvent`, `LocalizeFunc`, `NewDeviceDTO`, `ITelemetryBaseEvent`, `PseudoClassSelector`, `AtomGetter`, `SerializedAnalysis`, `FovCalculation`, `QuestaoModel`, `FractionalOffset`, `Uint64`, `RepoSideEffectPendingExpectation`, `EnumNodeAndEdgeStatus`, `Type_AnyPointer_ImplicitMethodParameter`, `NamedProblemMatcher`, `ExtendedFloatingActionButton`, `RadixAID`, `IFormItemProps`, `IJetApp`, `CreateAudioArgs`, `IUploadedFile`, `requests.ListTaggingWorkRequestsRequest`, `active`, `MockDeploy`, `ArgMap`, `BlockNumber`, `BottomNavigationBar`, `DevServerService`, `ColumnPropertyInternal`, `WebviewPanelImpl`, `ScopeTransform`, `ProductsService`, `CatchClause`, `TracingBase`, `Dimension`, `RTCSctpTransport`, `SSHExecCommandResponse`, `ChatMessageReceivedEvent`, `IMonthAggregatedEmployeeStatisticsFindInput`, `Phaser.Types.Core.GameConfig`, `Mathfield`, `DataQueryRequest`, `TextEditor`, `ConvLayerArgs`, `ProductReview`, `SpringChain`, `StandardAuthorization`, `CascaderOption`, `MethodDeclarationStructure`, `VisualizationListItem`, `SVGVNode`, `DrilldownState`, `ReplacePanelActionContext`, `HubConfigInterface`, `BindingType`, `OrderBook`, `DoorLockLoggingCCRecordReport`, `DetectedCronJob`, `ContractOperationCallback`, `PrimitiveTypeDescription`, `ChainablePromiseElement`, `NamedStyles`, `Property`, `SchemaFunctionProperty`, `MSGraphClient`, `EventPartialState`, `LoginSession`, `IGatewayMember`, `UnitSystemKey`, `MonadIO`, `TSubscribeHandler`, `SendProp`, `IChangeEvent`, `TypeDBTransaction.Extended`, `RepositoryKind`, `InternalBulkResolveParams`, `SFCBuildProps`, `UICollectionDelegateImpl`, `X12Element`, `Outcome`, `OverviewTestBed`, `TopologyData`, `AwsTaskWorkerPool`, `StorageObjects`, `FindEslintConfigParams`, `RefactorBuffer`, `ImportsMetadata`, `TransformationMatrix`, `ProcessStageEnum`, `RemoveTagsFromResourceCommandInput`, `AliasOrConnection`, `StorageService`, `BlogService`, `Rights`, `Timespan`, `ResolverOptions`, `SavedObjectOptionalMigrationFn`, `ITagSet`, `ITypeMatcher`, `EqState`, `MessageBuffer`, `UpdateManager`, `Fn1`, `Part`, `SpecHelperConnection`, `IWarrior`, `LaunchRequestArguments`, `Html2OrgOptions`, `EdiDocumentConfigurationResult`, `CLLocationCoordinate2D`, `FootnotesItem`, `AddressDetails`, `requests.ListAutonomousDatabaseClonesRequest`, `LogFunctions`, `GqlExecutionContext`, `DashboardComponent`, `OutboundPackage`, `VFSRef`, `t.File`, `LocKind`, `DrawerNavigationState`, `SharedMatrix`, `UpdateResponseData`, `ContactList`, `ModifyLoadBalancerAttributesCommandInput`, `BezierCurve3dH`, `WaterPoint`, `ICategoricalColorMappingFunction`, `SavedObjectType`, `TSESTreeToTSNode`, `CieloTransactionInterface`, `RtcpPacket`, `ModuleJob`, `IApprovalPolicyCreateInput`, `SinonFakeTimers`, `BotState`, `IQuizFull`, `Yendor.Tick`, `CollectorFetchContext`, `fromSingleRepositoryStatisticsActions.GetRepositoryStatistics`, `TickSource`, `androidx.transition.Transition`, `OuterExpressionKinds`, `TsProject`, `HeatmapConfig`, `Curried`, `GitHubIssue`, `QUICError`, `TypeResult`, `SolutionDetails`, `MeetingState`, `ISignal`, `ControlsProps`, `CustomRegion`, `TextWidthCache`, `SelectRangeActionContext`, `CachedMapEntry`, `PreparedFn`, `ApplicationTemplateAPIAction`, `BarDataSet`, `UtilProvider`, `HighlightInfo`, `SocketIoChannel`, `INodeType`, `EndpointInfo`, `PopulatedTransaction`, `RecentData`, `IPartitionLambdaFactory`, `SpanAttributes`, `GroupOrientation`, `JobResultDTO`, `Facade`, `IntNode`, `Range`, `ComputedScales`, `InputLayer`, `GeolocationService`, `FeedbackState`, `AjaxAppender`, `Events.start`, `CreateTypeStubFileAction`, `ConsoleLogger`, `UserAccountID`, `ConfigurationProperty`, `DataAccess`, `GetterHandler`, `RenderDeps`, `IBuildApi`, `AuthToolkit`, `WorkspaceConfig`, `ItemIndex`, `FeatureValue`, `KbnFieldType`, `AtomizeNecessary`, `MatchersUtil`, `CredentialPreview`, `ExpShapeConst`, `MlCapabilities`, `HTMLHtmlElement`, `ApplyHandler`, `Replica`, `Espree`, `IpcMainEvent`, `IResponseMessageHandler`, `MessageItem`, `EthereumClient`, `ParameterGroup`, `MatTabChangeEvent`, `GeoCoordinatesLike`, `PickerProps`, `PDFAcroCheckBox`, `ArianeeWallet`, `ElectronRoleCommand`, `SuggestionsComponentProps`, `ChatAdapterState`, `Monitoring`, `InstancePool`, `DeleteScheduledActionCommandInput`, `Overloads`, `ComponentWithMeta`, `SignInOutput`, `RawAlertInstance`, `ConsoleMessage`, `PSIChar`, `RulesTestEnvironment`, `VisualizeFieldContext`, `ts.SetAccessorDeclaration`, `NucleusVersion`, `InheritedCssProperty`, `StreamState`, `TableViewModel`, `HTMLCanvas`, `IStepAdjustment`, `TimeoutError`, `ISampleDescription`, `ts.SourceFile`, `OrbitDefinition`, `PostgresAdapter`, `ScrollOptions`, `FieldHierarchy`, `chromeWindow`, `Dynamic`, `DbPatch`, `StatelessOscillator`, `EmitHelper`, `DaffAuthToken`, `ts.PropertyAccessExpression`, `q.Message`, `FailureDetails`, `SavedSearch`, `CollapsedFormatField`, `ResolvedSchema`, `CampaignTimelineChanelPlayersModel`, `DragObjectWithType`, `InternalSymbol`, `JSDocUnionType`, `PlainValue`, `SUUID`, `InterfaceWithCallSignature`, `ObservablePoint3D`, `ExperimentStateType`, `OpenYoloProxyLoginResponse`, `RawError`, `SwaggerConfig`, `BanList`, `NzCascaderOption`, `IStoreState`, `FormConfig`, `ICkbMint`, `ExchangeAccount`, `IMDBVertex`, `AceConfigInterface`, `XmlFile`, `MergeTree.PropertySet`, `GunGetOpts`, `Value`, `MakeErrorMessage`, `RadixAddress`, `InlineComposition`, `MediaDeviceInfo`, `IUploadAttributes`, `I80F48`, `vscode.ConfigurationTarget`, `VerifyEmailAccountsRequestMessage`, `GPattern`, `LeafonlyBinaryTree`, `HarperDBRecord`, `ViewBase`, `RemovableAtom`, `InsertUpdate`, `GitHubRepository`, `IAckedSummary`, `CacheStore`, `DynamicArgument`, `LocalActorSystemRef`, `PreviousSpeakersActions`, `PhysicsBody`, `InjectedQuery`, `TodoTxtTask`, `IReserveUpdateValues`, `Cache`, `MutableVector3`, `OceanSpherePoint`, `DefaultViewer`, `ConnectionAction`, `SpeechConnectionMessage`, `ISurveyCreatorOptions`, `UnitConversion`, `MiddlewareContext`, `CodeGenDirective`, `Meter`, `PluginViewWidget`, `ethereum.UnsignedTransaction`, `ResourceHolder`, `fieldType`, `VariableDefinitions`, `GetOrganizationParams`, `ChangedData`, `TOperand`, `DbDrop`, `ModulesContainer`, `StartServicesGetter`, `interfaces.CommitType`, `IImageryMapPosition`, `BuiltRule`, `LPStat`, `CommentInfo`, `LookupExpr`, `StylableMeta`, `Connection`, `DMMF.OutputType`, `CompilationError`, `Cards`, `Package`, `MockERC20Instance`, `TokenTypes`, 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`DatabaseUsageMetrics`, `AuthorisationService`, `FeatureType`, `VectorStylePropertiesDescriptor`, `AssetReferenceArray`, `DocumentColorParams`, `TextureMapping`, `Renderer`, `AnnounceNumberNumberCurvePrimitive`, `BuildHandlerOptions`, `IStatusProvider`, `IReactComponentProps`, `PIXI.Texture`, `ICkbBurn`, `MatDrawer`, `VerificationClientInterface`, `CreateKeyPairCommandInput`, `ElevationRange`, `MonitoringParametersOptions`, `ISupportCodeExecutor`, `NodeVM`, `PositionOptions`, `ERC20FakeInstance`, `OnPreRoutingResult`, `LoaderInstance`, `SpaceBonus.DRAW_CARD`, `onChunkCallback`, `AssessmentItemController`, `LogoImageProps`, `ParserErrorListener`, `requests.ListLogsRequest`, `ArcGISAuthError`, `TransactionReducerResult`, `SupCore.Data.ProjectManifestPub`, `ShownModallyData`, `DeleteManyResponse`, `IWorkspaceDir`, `HKDF`, `Explorer`, `ReadonlyMap`, `TaskEvent`, `ExecutionContext`, `Season`, `TPluginsSetup`, `ReflectCreatorContext`, `ReportTaskParams`, `IKeyObject`, `ConditionalStringValue`, `track`, `OverridedMdastBuilders`, `VsCodeApi`, `IJsonRpcRequest`, `DeleteBackupResponse`, `$p_Expression`, `FailedAttemptError`, `ts.LiteralTypeNode`, `IHttpPromise`, `DirectoryItem`, `ILibraryResultState`, `TreeNodeGroupViewModel`, `TrackOptions`, `Stack`, `FieldDetails`, `LocationSet`, `CodeSpellCheckerExtension`, `TableStorageContext`, `RendererResult`, `WechatyPlugin`, `SpatialImagesContract`, `StepExecution`, `VueSnipState`, `TabsProps`, `CorsRule`, `CardRequirement`, `DistanceMap`, `CommandStatus`, `requests.ListCrossConnectLocationsRequest`, `FieldPath`, `FunctionBuilderArguments`, `XSLTokenLevelState`, `lsp.Diagnostic`, `StripeService`, `ListOption`, `CommandFunction`, `IT`, `DeltaAssertions`, `SpawnerOrObservable`, `AnimationPosition`, `FormFieldsType`, `ReferenceEntry`, `NetworkListenerArgs`, `ColumnOptions`, `FilteringPropertyDataProvider`, `requests.ListEdgeSubnetsRequest`, `CategorizedMethodMemberDoc`, `WeakMap`, `UIntCV`, `Register8`, `EllipseProps`, `angular.IHttpPromise`, `WorkflowEntity`, `AreaFormType`, `AnnotatedFunctionABI`, `APIEndpoint`, `Indexed`, `TypeResolution`, `IConstrutor`, `SwitchApplicationCommand`, `ClientSession`, `PendingResult`, `AlertAccentProps`, `SnapshotGenerator`, `KeyValType`, `CreateConfig`, `OverlayInitialState`, `MyResource`, `SelectTokenDialogEvent`, `IceTransport`, `SFPage`, `CredentialCache`, `TranslationChangeEvent`, `StateMethodsImpl`, `RequiredOrOptional`, `Descriptor`, `BaseGraphRewriteBuilder`, `CertificateAuthorityConfigType`, `Logout`, `GenerateOptions`, `NonEmptyString`, `OmvFeatureFilter`, `FileSchemaKey`, `DataBuckets`, `FluentUITypes.IDropdownOption`, `RestFinishedResponse`, `ScenarioData`, `JSONInMemoryCache`, `ConfigurationFile`, `ErrorDetailOptions`, `BScrollFamily`, `DLLData`, `MetricSet`, `NodeCheckFlags`, `DefaultTheme`, `PianoService`, `VdmEntity`, `QuickPickOptions`, `FilterNode`, `DepositAppState`, `PreviewProps`, `SourceString`, `Mars.NumberLike`, `ScheduledEventRetryConfig`, `messages.IdGenerator.NewId`, `PageCollection`, `Editor`, `LambdaEvent`, `SpeechCommandRecognizerResult`, `HsSaveMapService`, `TLineChartPoint`, `AgentIdentity`, `TabChangeInfo`, `TCalendarData`, `Advisor`, `ApiSettings`, `QueryStateChange`, `MockRequest`, `TransferedRegisterCommand`, `DistinctPoints`, `ListChannelsModeratedByAppInstanceUserCommandInput`, `OpenChannel`, `CalendarsImpl`, `WorkerMsgHandler`, `ObservableOption`, `ENV`, `OpenSearchDashboardsDatatableColumn`, `ImageSpecs`, `Cost`, `ElementComponent`, `PhysicalElementProps`, `UnsignedMessage`, `KeyframeIcon`, `Annotations`, `StyleAttribute`, `IEventLogService`, `MatrixType`, `Prisma.JsonValue`, `Apify.RequestQueue`, `Visual`, `KernelMessage.IOptions`, `AttributeDecoratorOptions`, `tmp.DirectoryResult`, `D.State`, `FacemeshOperatipnParams`, `TypeParameterDeclaration`, `ReadonlyObject`, `CSReturn`, `IRecurringExpenseEditInput`, `ReadableByteStreamOptions`, `HapiResponseToolkit`, `Register32`, `VisualDescriptor`, `IMouseEvent`, `ObjectDeclaration`, `UpdateParameterGroupCommandInput`, `DaffCategoryFilterRangePair`, `RequestManager`, `ajv.ErrorObject`, `TimelineLite`, `Precision`, `jasmine.CustomReporterResult`, `Types.PluginOutput`, `TransmartPackerHttpService`, `MockContainerRuntimeFactory`, `TagResourceOutput`, `VideoFileModel`, `IndexPatternFieldMap`, `PropertyResolver`, `GShare`, `scribe.Config`, `api.ISnapshotTree`, `DatabaseV2`, `InstallProfile`, `Timeslice`, `ManagedDatabase`, `WatchDirectoryFlags`, `AngularExternalResource`, `NodeProtocolInfo`, `SymbolMetadata`, `events.Args`, `ExpanderQuery`, `IOrganizationProject`, `AbstractView`, `LogResult`, `FixableProblem`, `SceneState`, `RxCacheService`, `DescribeEventsCommand`, `IiOSSimulator`, `IImage`, `ValidationExceptionField`, `LogViewer`, `ForwardInfo`, `SteemConnectProvider`, `IValidBranch`, `BarColorerStyle`, `ContainerPassedProps`, `TopNavConfigParams`, `IpcRendererListener`, `TreeItemIndex`, `INodeExecutionData`, `$Promisable`, `GenericAction`, `Quickey`, `ListWebhooksCommandInput`, `CompilerSystemRemoveFileResults`, `IContact`, `AvailabilityTestConfig`, `InstrumentationConfig`, `FullPath`, `TaskParameters`, `MathOptions`, `DecodedMessage`, `MoveAction`, `TimelineBucketItem`, `IExternalPrice`, `OutputTargetDist`, `IProvider`, `ColorTokens`, `IDataRow`, `ApplicationCommandOptionData`, `Inversion`, `DeeplyMockedKeys`, `ExtendedCluster`, `EdgeSnapshot`, `ListStudiosCommandInput`, `IParserConfig`, `JoinStrategy`, `ExceptionConverter`, `StaticSiteARMResource`, `CreateInstanceCommandInput`, `CacheKey`, `HSD_TExp`, `AnimationsService`, `InsertOptions`, `TypeModel`, `OneOrMore`, `MagicSDKError`, `RepositoryModel`, `RecordDataIded`, `SecurityAlertPolicyName`, `HLTVConfig`, `ExerciseService`, `ElementNames`, `SinglesigAddressType`, `ParseString`, `Mount`, `BlockParameter`, `ModeType`, `DiskAccess`, `AttributeSelector`, `RawData`, `SkeletonShapeProps`, `DataProviderProxy`, `SearchParamsMock`, `RuleDeclaration`, `CancelQueryCommandInput`, `vscode.DocumentSelector`, `ITccProfile`, `IFBXRelationShip`, `PluginInterface`, `SourceDocument`, `HammerManager`, `BaseVisType`, `ICharacter`, `GameStartType`, `DayFitnessTrendModel`, `ResolvedRecordAtomType`, `ServerResponse`, `ValueAndUnit`, `BlockchainPropertiesService`, `ADTClient`, `ArrayValue`, `JupyterLab`, `Immutable.Map`, `ParsedUrlQuery`, `NeverType`, `NVNode`, `ParsedDevModuleUrl`, `SFSchemaEnum`, `Audit`, `IssuePayload`, `ShoppingCartContextValue`, `PrimitivePolygonDrawerService`, `StyleObject`, `PagedResult`, `MultiSigSpendingCondition`, `XMessageBoxService`, `ToolAssistanceInstruction`, `MemoryUsage`, `backend_util.BackendValues`, `SchemaVisitorFactory`, `AssetBindings`, `VdmMappedEdmType`, `BibtexAst`, `RouteGroup`, `DaffError`, `GalleryItem`, `MousePressOptions`, `Aurelia`, `UseMutation`, `io.LoadOptions`, `PoiTableEntry`, `DaffProductServiceInterface`, `ModalHelperOptions`, `JoinRow`, `ProblemMatcher`, `CreateJobResponse`, `GuideData`, `BedrockFileInfo`, `ExtraData`, `ContractABI`, `TagListQueryDto`, `FactoryContext`, `ExtractorInput`, `ServerViewPageObject`, `ChatNode`, `MenusState`, `ApisService`, `EdgeDescriptor`, `ItemState`, `Deserializer`, `IBLEAbstraction`, `AbstractFetcher`, `TransactionRequest`, `requests.ListWaasPolicyCustomProtectionRulesRequest`, `AutorestContext`, `AwarenessUpdate`, `SchemaName`, `SigError`, `RequestArgs`, `TrackEntry`, `ReactFCNoChildren`, `MatchLeave`, `ts.TupleTypeNode`, `Probot`, `TileCoordinator`, `Student`, `TextRewriterState`, `IThemeWeb`, `IDatabase`, `FilePath`, `IClusters`, `InternalException`, `TxPayload`, `MockClass`, `angular.ui.bootstrap.IModalService`, `TypeOfContent`, `IndexTemplateMapping`, `Burst`, `TestMessages`, `ContainerType`, `Benchmark`, `AttributeValueType`, `vscode.Diagnostic`, `Key1`, `QBoxLayout`, `PersistenceManager`, `SymbolOriginInfo`, `Issue`, `ObjectSelector`, `RequestWithdrawalDTO`, `Align1`, `SearchCriteria`, `Operations`, `AsyncStateRetry`, `LanguageMatcher`, `ContractAbi`, `ICommit`, `StateHelper`, `IKeyEntry`, `Web3SideChainClient`, `CrochetTypeConstraint`, `DefaultBrowserBehavior`, `UserDocument`, `VariableArgs`, `RenderTreeEdit`, `TransactionList`, `StripeConfig`, `SetGetPath`, `RouteInitialization`, `NavItemProps`, `Redis.Redis`, `TypedLanguage`, `IExpectedSiop`, `d.Module`, `ConsoleInterceptor`, `IDataContextProvider`, `GfxrResolveTextureID`, `RetrieveResult`, `TDeclarations`, `TokenDetails`, `OverlayOptions`, `VueApolloSmartOpsRawPluginConfig`, `PiElement`, `PublicKeyData`, `IconifyAPIIconsQueryParams`, `ErrorThrower`, `DatasetManagerImpl`, `Filesystem.PackageJson`, `SFCBlockRaw`, `WrappedComponentRoot`, `LiteralSource`, `EditorModel`, `CallHierarchyIncomingCallsParams`, `React.ForwardRefExoticComponent`, `ISubmitEvent`, `Cdt`, `Simulation`, `ApolloSubscriptionElement`, `requests.ListStandardTagNamespacesRequest`, `GDQOmnibarListElement`, `ConcurrentModificationException`, `UserButton`, `MockStyleElement`, `IUnit`, `LinkModel`, `PublicPlayerModel`, `PeerTypeValues`, `ICallback`, `StateTimeline`, `MaterialButton`, `CommonInfo`, `LabwarePositionCheckStep`, `DiagnosticAction`, `SutTypes`, `ICategoryCollectionState`, `ColorSchemeId`, `SpyAsyncIterable`, `BuilderProgramState`, `TrainingConfig`, `PDFOptions`, `ManagedItem`, `MDCDialogCloseEvent`, `StatBlock`, `quat`, `MockAthena`, `AggregateBuilder`, `ExpressionFunctionVisualization`, `MaterialEditorOptions`, `AbstractSqlDriver`, `LatexAtom`, `MangoAccount`, `LibraryOptions`, `CurveFactory`, `ServerActionHandler`, `IDragEvent`, `JSHandle`, `AssertionContext`, `PlayerClass`, `SynthDefResultType`, `vscode.CompletionContext`, `WriteStorageObject`, `RawMatcherFn`, `ServiceHelper`, `HSLA`, `TestDisposable`, `Category2`, `XsltPackage`, `JPAResourceRaw`, `InstanceOf`, `CommandEnvelope`, `RadioComponent`, `XConfigService`, `IPricedItem`, `OutputTargetDocsVscode`, `JSheet`, `NineZoneStagePanelsManagerProps`, `StructurePreviewProps`, `BuildOnEventRemove`, `SelectionSource`, `IGetTimeSlotStatistics`, `ts.TextChangeRange`, `ISearchParams`, `IVocabularyItemWithId`, `TemplateBlock`, `PAT0_MatData`, `LineGeometry`, `ActOptions`, `PvsTheory`, `HelperOptions`, `DOMWindow`, `FileUploadState`, `ShortId`, `IDebtsGetByContactState`, `ProxySettings`, `ModuleWithComponentFactories`, `PluginConfigSchema`, `OptionTypeBase`, `XNotificationOption`, `EnteFile`, `d.ComponentRuntimeMeta`, `FieldMeta`, `EndpointName`, `TooltipState`, `TAccessQueryParameter`, `WorldgenRegistryHolder`, `SharingResult`, `RenderTexture2D`, `CAST_STRATEGY`, `DidOpenTextDocumentParams`, `TestItem`, `IFetchOptions`, `IUiSettingsClient`, `ColorInfo`, `LSAndTSDocResolver`, `PurchaseList`, `Parent`, `appleTransactions.Table`, `IniData`, `DescribeLoadBalancerAttributesCommandInput`, `DSONameService`, `LambdaCloseType`, `AdjustNode`, `OptimizeModuleOptions`, `Overlay`, `ChatService`, `RowSet`, `UserClients`, `ResultItem`, `SExp`, `GraphImpl`, `RestoreDBClusterToPointInTimeCommandInput`, `AsyncSnapshot`, `Firmware`, `DataViewFieldBase`, `UiPlugins`, `Url`, `ActionTypeRegistry`, `ReactorConfig`, `MessageDescriptor`, `HTMLButtonElement`, `XYZValuesArray`, `OpenYoloError`, `ResizableTest`, `ExecaChildProcess`, `IApiSnapshot`, `ReductionFn`, `SentimentValue`, `ComponentRuntimeMembers`, `IVirtualDeviceConfiguration`, `IEditorTracker`, `DynamicFlatNode`, `ToastProps`, `ScreepsReturnCode`, `MirroringHost`, `IToken`, `RenderedSpan`, `RuntimeFn`, `PeriodInfo`, `TagComponent`, `PluginVersionsClient`, `Axial`, `PathParamOptions`, `IReportingRule`, `PointTuple`, `CUUID`, `YACCDocument`, `TupletType`, `IAnimal`, `ResolvedConfigFilePath`, `BackgroundAnalysisBase`, `PreflightCheckNamespacesResult`, `FiddleSourceControl`, `ITerminalChunk`, `IBaseNode`, `UserApp`, `TableRefContext`, `MigrationFeedback`, `chrome.tabs.TabActiveInfo`, `AngularEditor`, `CSVDataset`, `CoinbasePayload`, `StoreGroup`, `VideoSettings`, `FlowType`, `BuildResult`, `MethodDecorator`, `Unpacked`, `HostConfig`, `ReduxRootState`, `AppInsightsQueryResultTable`, `ApplicativeHKT`, `IUnitProfile`, `TableAccessByRowIdStep`, `KeyID`, `TransportMessage`, `RSS3List`, `sdk.Conversation`, `WebsiteScanResult`, `Arity2`, `CubicBezier`, `GestureType`, `LineSeriesStyle`, `SourceFileNode`, `AutorestConfiguration`, `ChapterData`, `AimEvent`, `ClientTag`, `CameraGameState`, `EnumDictionary`, `ExampleMetadata`, `puppeteer.Page`, `LambdaAction`, `GaugeAction`, `Fermata`, `ClientBuilder`, `GrammaticalGender`, `PickerColumnOption`, `TodoList`, `InlineField`, `TransactionEventArgs`, `ICXGenericResult`, `BareFetcher`, `ScopedSlotReturnValue`, `ApplicationListener`, `MockXMLHttpRequest`, `ServerHelloDone`, `EqualsGreaterThanToken`, `StatePages`, `QueryInput`, `ActionFunctionAny`, `OrganizationsClient`, `NodeClient`, `ActionHandlerContext`, `SVGVNodeAttrs`, `HubIModel`, `builder.Session`, `WebGLUniformLocation`, `BlobTestServerFactory`, `SequenceNode`, `ERC20`, `FrameNote`, `CreateEventSubscriptionResult`, `UICollectionViewDataSourceImpl`, `WebGLEngine`, `MyService`, `VerifiedToken`, `MixerCommunicator`, `NSRange`, `backend_util.Conv2DInfo`, `Web3ProviderEngine`, `TableRecord`, `p5ex.SpriteArray`, `CarouselProperties`, `FunctionTypeNode`, `ImageCacheItem`, `TelemetryService`, `EventDef`, `LegacyWalletRecord`, `IfStatement`, `Color3`, `NgrxJsonApiStoreQueries`, `choices`, `RestConfigurationMethod`, `KeyInput`, `DAOcreatorState`, `Thought`, `CohortPatient`, `CarImage`, `PouchDB.Database`, `IJsonRPCError`, `NetworkEdge`, `ProdutoDTO`, `GestureDetail`, `Observations`, `ChipService`, `YT.SuggestedVideoQuality`, `ITestResult`, `ListTournamentsRequest`, `MultipleInterfaceDeclaration`, `IScopeData`, `FIRUser`, `KeyboardManager`, `HStackProps`, `IRgb`, `ListApmDomainsRequest`, `ElementDataset`, `VirtualEditor`, `a.Type`, `jest.Mock`, `SlmPolicy`, `DocHandler`, `RankedTester`, `VectorEntry`, `BaseProvider`, `AbstractCommandDescriptor`, `WNodeFactory`, `FullFilePath`, `WholeStoreState`, `THREE.BufferAttribute`, `ListFriendsRequest`, `LexerResult`, `FirebaseServiceNamespace`, `WrapConfig`, `ITargetFilter`, `ICallsGetByContactState`, `ContractInterfaces.Market`, `ICalDateTimeValue`, `SystemData`, `SampleDataType`, `CharacterStore`, `ITimelineGroup`, `Obj`, `QuestionType`, `IpcSender`, `EnhancedTestStore`, `GetAttendeeCommandInput`, `esbuild.BuildResult`, `NonThreadGuildBasedChannel`, `Owner`, `CannedMarket`, `DescribeBackupsCommandInput`, `SimpleLogger`, `LangiumServices`, `EllipticCurves`, `MockContainerRuntimeForReconnection`, `SmartBuffer`, `IAnimation`, `IValidatorOptions`, `TestApi`, `ComponentTemplateDeserialized`, `DialogContextOptions`, `StreamService`, `xlsx.CellObject`, `RcModuleV2`, `ConeSide`, `FlashSession`, `EDerivativeQuality`, `SerializedSlot`, `FilterConstructor`, `BLAKE2s`, `MessageEvent`, `ODataStructuredTypeFieldParser`, `Nature`, `ClaimantInfo`, `ImporterRegistry`, `EntityInterface`, `ArtworkData`, `Engine`, `Definitions`, `LogSplitLayout`, `TypeESMapping`, `PlayerService`, `LockStepVersionPolicy`, `Free`, `EVMParamValues`, `SideMenuState`, `MDCSemanticColorScheme`, `UpdateConfigurationSetEventDestinationCommandInput`, `Accumulator`, `AppFilters`, `ListCtor`, `RaceCancellation`, `ProjectImage`, `SyncedRef`, `AccountsServer`, `GitDiff`, `Implementation`, `ObjectLiteral`, `ElementRef`, `TargetedMouseEvent`, `SigningKey`, `Kubeconfig`, `StatsTable`, `SFTPWrapper`, `CommandClassOptions`, `MapAnchors`, `RouterData`, `MockWrapper`, `GX_VtxAttrFmt`, `EvalParam`, `TreeProps`, `MarkdownSection`, `PolySynth`, `ITabInternal`, `IFS`, `ListUsersCommandOutput`, `Leaf`, `ErrorFn`, `SqrlExecutable`, `CohortService`, `FileTransportInstance`, `ToastState`, `EscapedPath`, `ExcerptToken`, `Middleware`, `PlacementStrategy`, `ControlPointView`, `GridApi`, `CircuitGroup`, `Parse.User`, `Softmax`, `PopupUtilsService`, `DurationUnit`, `AccountModel`, `Area`, `NameAndContent`, `AddTagsToResourceCommandOutput`, `BufferTypeValues`, `d.DevClientConfig`, `StoredReference`, `WebSiteManagementModels.FunctionEnvelope`, `com.github.triniwiz.canvas.ImageAsset.Callback`, `LoggerTask`, `NumberFilter`, `TableEntry`, `LeaderboardEntry`, `IAddAccountState`, `NodeMaterialBlock`, `InitiatingTranslation`, `ContractDeployOptions`, `ThresholdCreateSchema`, `TimeGranularity`, `IRawDiff`, `ResponseEnvelope`, `NgrxFormControlId`, `NumberFormat.UInt32LE`, `ThyDragStartEvent`, `CoinPrimitive`, `OnPreResponseInfo`, `PolkadotConnection`, `GLTF2.GLTF`, `NumberRenderer`, `Environment_t`, `requests.ListPingMonitorsRequest`, `APIGatewayProxyResult`, `InternalVariation`, `BurnerPluginContext`, `Main.LogScope`, `PostfixUnaryOperator`, `Dev`, `KillRing`, `IUniform`, `Express.Response`, `ConfigConfig`, `CharacterInfo`, `VisualProperties`, `ThyGuider`, `CommandBus`, `IType`, `MinMax`, `OF.IDropdownOption`, `GeocodeQueryInterface`, `ResolveImportResult`, `DSVRowString`, `TronTransactionInfo`, `RetryLink`, `ProviderEventType`, `TransformParams`, `DOption`, `Toggle.Props`, `AutorestSyncLogger`, `ITxRecord`, `resourceI`, `SuggestMatch`, `CommonDivProps`, `HttpPayloadTraitsWithMediaTypeCommandInput`, `PresetOptions`, `OptionalCV`, `ConfigInterface`, `models.ArtifactItem`, `Windup`, `APIResource`, `CLM.AppDefinition`, `RRdomTreeNode`, `SmdDataRowModel`, `Vec2Term`, `UserEvent`, `PreviewSize`, `requests.ListObjectsRequest`, `NotifyFn`, `RestRequestOptions`, `FilterType`, `PoolInfo`, `RecognizerResult`, `NAVObjectAction`, `Release`, `ESMessage`, `CipherData`, `SourceDetails`, `CellKey`, `IListViewCommandSetListViewUpdatedParameters`, `TDeleteManyInput`, `PackageAccess`, `JSChildNode`, `ChainInfoInner`, `MarketCurrency`, `RouterExtensions`, `ILocationResolver`, `UrlGeneratorId`, `PostMessageStorage`, `District`, `LineSeries`, `DeleteSettingCommand`, `observable.EventData`, `TableBuilderComponent`, `SharedFunctionsParser`, `CompletionEntry`, `MaterialInstanceConfig`, `MIRStatmentGuard`, `tf.io.ModelArtifacts`, `Endian`, `UnsupportedTypeLog`, `PreActor`, `UnionShape`, `ComposedChartTickProps`, `StyledProps`, `Legend.Item`, `ng.IModule`, `StorableUrl`, `SeriesOptions`, `LoginResultModel`, `MDCContainerScheme`, `DebugNode`, `ListQueuesRequest`, `MapNode`, `IDropboxEntry`, `ComparisonNode`, `Browser`, `AudioInputDevice`, `UserApollo`, `AudioStreamFormat`, `BufferSource`, `CommonService`, `PartsModel`, `SemanticTokens`, `AccessorComponentType`, `StackCardInterpolationProps`, `theia.DocumentSelector`, `WorkRequestError`, `IDatasource`, `Status`, `MongoCallback`, `CLM.LogDialog`, `Repeater`, `IDiffStatus`, `DevError`, `ArrayPromise`, `IOperandPair`, `Arbitrary`, `UserDetailsQuery`, `ModuleSymbolMap`, `ArmFunctionDescriptor`, `AccessorNames`, `GitStore`, `memory`, `SocketHandler`, `GetIPSetCommandInput`, `d3.Selection`, `SeparatorAxisTest2D`, `RangeDataType`, `GlobalStore`, `DAL.KEY_COMMA`, `BrowseProductsFacade`, `MaterialRenderContext`, `OrderJSON`, `IMiddlewareEvent`, `ILoginResult`, `PostItem`, `IDocString`, `WishlistsDetailsPage`, `ActionSheetButton`, `ForceLightningLwcStartExecutor`, `HardhatUserConfig`, `LocalVideoStream`, `ValueTransformer`, `InspectorLogEntry`, `PatchObjectMetadata`, `CacheHandler`, `ChatPlugin`, `SimpleExpressionNode`, `StringFilterFunction`, `AnySchema`, `FlightType`, `XYBrushEvent`, `ElementProfile`, `DeployOrganizationStep`, `TokenInfo`, `DeflateWorker`, `TaskManager`, `ModuleSpec`, `FrameInfo`, `ITokenClaims`, `StaticBuildOptions`, `DashboardCollectorData`, `OptionsConfig`, `Tolerance`, `MatchExplanationTreeNode`, `MicrophoneIterator`, `TextBlock`, `SessionStorageSinks`, `FrameNavigation`, `TelemetryReporter`, `InvalidParameterException`, `egret.Point`, `MlRoute`, `MatrixMessageProcessor`, `ModuleContext`, `PutMessagesResultEntry`, `Lunar`, `AxeCoreResults`, `CompletedPayload`, `DisabledRequest`, `StreamData`, `HomePage`, `FeaturePrivilegeAlertingBuilder`, `Readable`, `IAlertProps`, `SupCore.Data.Entries`, `GQLResolver`, `TIntermediate1`, `SortedSetItem`, `DatasourceRef`, `DirectionDOMRenderer`, `DisplacementFeature`, `MarkdownContentService`, `QueryChannelRangeMessage`, `IPeacockSettings`, `ParamMap`, `FilterValueExpressionOrList`, `DotIdentifierContext`, `ViewportCoords`, `ChangesetIndex`, `MapConstructor`, `UiSyncEventArgs`, `ProviderRegistry`, `ISODateTime`, `OasRef`, `AppData`, `Wizard`, `DeleteOptions`, `PutObjectOptions`, `ParingTable`, `Monad3`, `Point2d`, `Shard`, `Groupby`, `KdfType`, `ActiveProps`, `DamageType`, `CommonMiddlewareUnion`, `InviteService`, `Scalar`, `IViewProps`, `FeedbackRecord`, `AnyValidateFunction`, `SdkDataMessageFrame`, `RarePack`, `IAttentionSeekerAnimationOptions`, `SessionTypes.Settled`, `IDocumentServiceFactory`, `RedPepperService`, `ServerDevice`, `SNSEvent`, `TelegramClient`, `ClaimingSolution`, `AllActions`, `QueryPointer`, `AnalysisContext`, `CalculateHistogramIntervalParams`, `PluginWriteAction`, `TestingLogger`, `LogAnalyticsSourcePattern`, `OffsetConnectionType`, `ng.IAngularEvent`, `GX.CompType`, `Record.Update`, `vsc.Uri`, `MatOption`, `MenuStateBuilder`, `SnippetVisibility`, `MapSavedObjectAttributes`, `RecordPatternItem`, `GraphSnapshot`, `RandomNormalArgs`, `FontSize`, `ZoneWindowResizeSettings`, `SingleRepositoryStatisticsState`, `api.IZoweTree`, `PlaceEntity`, `NotificationActions`, `Hmi`, `RSSFeed`, `AbstractTransUnit`, `AnyStandaloneContext`, `IHandlerAdapter`, `DocumentClassList`, `FogBlock`, `StateForStyles`, `ILoginOptions`, `actionTypes`, `ITerm`, `AlertExecutionStatus`, `CodeFixAction`, `TValPointer`, `FnN4`, `Voyager`, `VIdentifier`, `AssociationConfig`, `TestContractAPI`, `Intervaler`, `SuperTest.SuperTest`, `InputBoxOptions`, `APITweet`, `JsxOpeningElement`, `BundleManifest`, `RouterContext`, `TestUseCase`, `Fixed8`, `ConnectResponseAction`, `PlayerData`, `GADBannerView`, `DescribeCommunicationsCommandInput`, `TVLAnalysis`, `DbRefBuilder`, `UrlResolver`, `ConstructDataType`, `AzureFunction`, `RowViewRef`, `TopicChangedListener`, `TEBopType`, `FormConnectionString`, `TDynamicObj`, `InternalCorePreboot`, `OperatorOption`, `ReadReceiptReceivedEvent`, `BatchGetItemInput`, `FakeInput`, `RediagramGlobalConfig`, `TObject`, `SlateEditor`, `BindingTemplate`, `GitHubUser`, `DescribeLoggingOptionsCommandInput`, `ObjMap`, `OutputAdapter`, `Outside`, `StableToken`, `OutputBinaryStream`, `CombinedState`, `ContractOptions`, `IBlockchainEvent`, `TrialVisitConstraint`, `FileStatus`, `IOrder`, `NotificationChannelServiceClient`, `IWindow`, `TransformingNetworkClient`, `StringSchema`, `CheckableElement`, `HomeAssistantMock`, `UniversalAliasTable`, `SurveyForDesigner`, `optionsType`, `MySpacesComponent`, `MemberId`, `IList`, `CanvasTypeProperties`, `UntagResourceResponse`, `RnPromise`, `PathCandidate`, `Change`, `CollectionOptions`, `pw.Page`, `ChatNodeVM`, `IncomingDefault`, `FieldUpdate`, `TeamProps`, `PRNG`, `RouteChildrenProps`, `ListDomainsRequest`, `SempreResult`, `MainDate`, `SqrlTest`, `RedirectUri`, `pageOptions`, `UInt128`, `QueryBuilder`, `DataStoreService`, `InteractivityChecker`, `ExtProfile`, `APEv2Parser`, `MetricSourceIntegration`, `OpenAPIV2.Document`, `CampaignItemType`, `AttributeContainer`, `ChannelSigner`, `DefaultEditorAggSelectProps`, `EditorFromTextArea`, `IRouterSlot`, `ProtocolVersionFile`, `SlaverListener`, `TPagedParams`, `ConfigProps`, `Events.postkill`, `MapStateToProps`, `ApplyPendingMaintenanceActionCommandInput`, `CursorEvents`, `Constraints`, `FavoritesState`, `UpdateInfoJSON`, `MockValidatorsInstance`, `PublicPolynomial`, `ActionsConfigurationUtilities`, `SurveyResultMongoRepository`, `ThemeValue`, `UnitWithSymbols`, `ILeague`, `ICardInfo`, `ContributionProvider`, `AssertionResult`, `TimerType`, `TabularCallback`, `TPLTextureHolder`, `GetTagsCommandInput`, `SvgIconConfig`, `MediaDef`, `YAxis`, `PromptResult`, `JSONSchemaSourceData`, `ts.HeritageClause`, `MessageWithReplies`, `vec3`, `ListFunctionsRequest`, `DAL.DEVICE_ID_SERIAL`, `JobResult`, `android.animation.Animator`, `IUpworkClientSecretPair`, `TaskDetails`, `UserFunction`, `WidgetTracker`, `TextDecoration`, `ParsedUrlQueryInput`, `DocusaurusContext`, `SerumMarket`, `Portion`, `SchemaConfig`, `ServiceNameFormatter`, `GetServersCommandInput`, `ListClient`, `RouteShorthandOptions`, `Miscellaneous`, `DragLayerMonitor`, `IndexedXYZCollection`, `Out`, `QueryIdempotencyTokenAutoFillCommandInput`, `StandardTableColumnProps`, `ExceptionIndex`, `Reward`, `ISubWorkflow`, `TSESLint.Scope.Reference`, `ThingProto`, `SignedOperation`, `ILoggerModel`, `CreateElement`, `MagickColor`, `UserSummary`, `FormGroupControls`, `SourceFileContext`, `LngLat`, `IssueAnnotationData`, `Arrayish`, `ITest`, `CallAgentProviderProps`, `GenericBreakpoint`, `SfdxTestGroupNode`, `FooValueObject`, `PagerDutyActionTypeExecutorOptions`, `messages.Attachment`, `GraphQLTypeInformer`, `AggParamEditorProps`, `IStateTypes`, `StatefulLogEvent`, `TextTexture`, `CheckupConfig`, `CheckboxFilter`, `Mesh_t`, `d.OutputTargetAngular`, `PostsContextData`, `google.maps.GeocoderResult`, `RootPackageInfo`, `DateFormatter`, `Encoding.Encoding`, `IReserveApiModel`, `AuthDataService`, `TextEditorConfiguration`, `AttrState`, `OpeningHours`, `BroadcastTxResponse`, `ClientSocketPacket`, `PartialOptions`, `ConformancePatternRule`, `ListConnectionsResponse`, `AccessKeyId`, `ReactionId`, `PgdbDataSource`, `EditMediaDto`, `ActionTypeModel`, `TextBuffer.Point`, `FungibleTokenDetailed`, `ISearchSetup`, `ValidatorConfig`, `ApiCredentials`, `SchemaComposer`, `STRowSource`, `PerformanceEntryList`, `BencheeSuite`, `TransitionConditionalProperties`, `IPropertyPaneConfiguration`, `DataImportRootStore`, `ObjectContent`, `Mars.AddressLike`, `DescribeInstancesCommandInput`, `IMinemeldStatusService`, `ISampler3DTerm`, `DropoutLayerArgs`, `ApplicateOptions`, `DataLayer`, `ExpressionsStart`, `ProgressBarEvent`, `EventMutation`, `Cancelable`, `OpenCLBuffer`, `ExtensionSettings`, `IViewport`, `UInt64`, `ApplicationLoadBalancer`, `MerkleIntervalInclusionProof`, `EntityDTO`, `ContractTransaction`, `CommandConstructorContract`, `Cypress.Actions`, `PlanetData`, `firebase.Promise`, `ParquetCompression`, `CanvasSpaceNumbers`, `LegendOrientation`, `EyeGazeEvent`, `NNode`, `DebugSystem`, `ScaleValue`, `DefaultRenderingPipeline`, `Oas3`, `IScripts`, `RecentDatum`, `_ts.Node`, `ICassClusterModuleState`, `IVar`, `tensorflow.IGraphDef`, `TargetConfiguration`, `YearToDateProgressConfigModel`, `DynamicFormLayoutService`, `ComponentArgTypes`, `ListColumn`, `ColumnDefinitionBuilder`, `WakuMessage`, `Config.GlobalConfig`, `PageHelpers`, `IPSet`, `Triangle`, `AssessmentType`, `DomApi`, `Hasher`, `SpectrumElement`, `BuildAnnotation`, `MatrixUser`, `VideoInfo`, `ASTConverter`, `SentimentAspect`, `FileSystemCommandContext`, `ParserContext`, `StorageObjectAcks`, `HealthPolledAction`, `BaseHub`, `Accord`, `JobStatus`, `UserPreferences`, `MediationState`, `CommonOptions`, `MapImage`, `SharedConfig`, `KibanaExecutionContext`, `CmsContext`, `ScaledSize`, `PropEnhancers`, `NetworkBuilder`, `ChemicalState`, `EngineArgs.ListMigrationDirectoriesInput`, `IMonitorPanelAction`, `EvActivityCallUI`, `NumberLike`, `requests.ListWorkRequestLogsRequest`, `StackHeaderProps`, `PropertyAnimation`, `NetworkConfig`, `GeometryKind`, `IVertoCallOptions`, `StarPieceHostInfo`, `FaunaPaginateOptions`, `Vars`, `React.DragEvent`, `Eth`, `WebhookProps`, `SearchEmbeddableConfig`, `TwingTemplate`, `PolymorphicPropsWithoutRef`, `EntityObject`, `Answers`, `GetResult`, `DriverException`, `CreateUser`, `ToolbarButton`, `SubscriptionField`, `reflect.TypeReference`, `InsightShortId`, `MapDispatchToProps`, `IResultSetRowKey`, `HalfEdgeGraph`, `InstanceClient`, `TestabilityRegistry`, `ObjectNode`, `SwapInfo`, `DeviceConnection`, `TEBinOp`, `ServiceManager`, `ViewMetaData`, `OscillatorNode`, `LayerObjInfoCallback`, `JHistory`, `OperationBatcher`, `FrameGraphicsItem`, `DateIntervalDescriptor`, `ContentChangedCallbackOption`, `BufferLine`, `IColorModeContextProps`, `OverrideOptions`, `ActionToRequestMapper`, `ModelObj`, `RowLevel`, `MiniMap`, `ReadableStreamController`, `MsgAndExtras`, `EngineResults.DevDiagnosticOutput`, `ChainedIterator`, `DAL.DEVICE_ID_GESTURE`, `DryPackage`, `RedisConnectionManager`, `GaussianDropout`, `TheiaDockPanel`, `EthereumEvent`, `StripePaymentMethod`, `TreeChanges`, `IGhcModProvider`, `AMock`, `RouteProp`, `AppStatusChangeFaker`, `CalendarRange`, `MoveData`, `InsertOneResult`, `AlbumListItemType`, `GrowableXYZArray`, `MemoryDump`, `AC`, `TagKey`, `NewSyntax`, `MonitoredHealth`, `NFT1155V3`, `LineChartLineMesh`, `Libraries`, `QueueData`, `EntityKey`, `CommentRange`, `requests.ListDhcpOptionsRequest`, `Pully`, `DataConfig`, `WsViewstateService`, `ElementDefinition`, `Of`, `AutocompleteProvider`, `VaultAdapterMock`, `SavedObjectsServiceStart`, `DataDown`, `PrefFilterRule`, `Knex.Transaction`, `NaviRequest`, `AutoRest`, `binding_grammarVisitor`, `EventPublisher`, `VirtualFilesystem`, `SetupModeProps`, `ArtifactItem`, `StynPlugin`, `MarkConfig`, `ExtendedAppMainProcess`, `Reader`, `MalRequest`, `ApolloServerExpressConfig`, `VSnipContext`, `GetResponse`, `TreemapSeries.ListOfParentsObject`, `MultiPolygon`, `IcalEventsConfig`, `FileEditorSpec`, `ImageSourcePropType`, `OsmObject`, `DeployStageExecutionStep`, `IUiStateSlice`, `ComponentFixture`, `FilterFunction`, `ShortcutEventOutput`, `ZoomOptions`, `VisTypeTimeseriesVisDataRequest`, `TransitionDefinition`, `VisualizationConfig`, `ChannelState`, `S3Control`, `Computed`, `SwitchOptions`, `ImageInspectInfo`, `PhrasesFilter`, `CronService`, `WeaponMaterial`, `git.ICreateBlobParams`, `ArweavePathManifest`, `androidx.appcompat.app.AppCompatActivity`, `DoorLockCCOperationReport`, `SupervisionResult`, `VisualizationsSetupDeps`, `SavedObjectsPublicPlugin`, `SeriesOption`, `Scope`, `TouchGestureEventData`, `HintMetadata`, `TestBed`, `JointConfig`, `TableOffsetMap`, `THREE.Euler`, `GenerateClientOptions`, `HomePageProps`, `TypeName`, `TypeCacheEntry`, `SingleEmitter`, `ReindexState`, `FunctionImportRequestBuilder`, `SavedObjectsImportOptions`, `SwitchAst`, `LoginOptions`, `Resources`, `IDBTransactionMode`, `TensorLike2D`, `RTCRtpParameters`, `ChartParams`, `Types.TooltipCfg`, `UserStakingData`, `TransferType`, `ConstrainDOMString`, `HomeReduerState`, `AlainI18NService`, `EditorCompletionState`, `PlanPreviewPanel`, `IdentityNameValidityError`, `AddMessage`, `RecommendationLevel`, `Partition`, `SubscriberType`, `ItemTable`, `DecoratorDefArg`, `MOscMod`, `AddonEnvironment`, `DispatchWithoutAction`, `DebtKernelContract`, `IController.IParameter`, `DriverModel`, `Matrix22`, `SheetRef`, `URLParse`, `GiphyService`, `SVGLabel`, `StreamModel`, `ExceptionsBuilderExceptionItem`, `WindiPluginUtils`, `TerraNetwork`, `GraphQLFieldMap`, `GetItemOutput`, `ImageViewerProps`, `ProjectInfo`, `ConfigSet`, `FunctionProp`, `WeaponData`, `ForgotPasswordVerifyAccountsRequestMessage`, `UserID`, `Snap`, `Web3ReactContextInterface`, `IFilterListGroup`, `ActionWithError`, `IBalance`, `ListInstancesCommandInput`, `AggConfigOptions`, `BillId`, `GameSettings`, `MediaFileId`, `ICredentialsDb`, `CallArguments`, `StatusFollow`, `sdk.TranslationRecognitionEventArgs`, `FrameType`, `EngineEventType`, `FormWindow`, `loader.Loader`, `CreateConfigurationCommandInput`, `GeoBoundingBoxFilter`, `DataSharingService`, `GameInput`, `Pile`, `FadeSession`, `RawNodeData`, `PresentationRpcRequestOptions`, `InternalHttpServiceSetup`, `PropParam`, `LinkedAccount`, `AxisDimension`, `ILiquorTreeNode`, `IGradGraphs`, `CSSProperties`, `LuaDebugVarInfo`, `ChampList`, `StorageRecord`, `Aser`, `BufferConstructor`, `ProjectMeta`, `DescribeTagsCommand`, `SelectorT`, `EvaluateOperator`, `env`, `HTMLPreElement`, `RegisteredTopNavMenuData`, `OperationQueryParameter`, `MatchDoc`, `ConflictResolution`, `ConverterDiagnostic`, `SoundConfig`, `CompanyType`, `MetadataSelector`, `Dump`, `vscode.TextDocument`, `DatabaseOptions`, `CreateDBClusterParameterGroupCommandInput`, `RequestorBuilder`, `ShoppingCartStore`, `IDependenciesSection`, `PbSecurityPermission`, `IServerSideDatasource`, `WFunction`, `FeedbackId`, `QueryMiddleware`, `DocumentMetadata`, `MaxNormArgs`, `GlobalInstructionData`, `AppletIconStyles`, `SandDance.specs.Insight`, `AuthorModel`, `GetEmailTemplateCommandInput`, `UpdateFlowCommandInput`, `CreateSubnetGroupCommandInput`, `CircuitInfo`, `ENGINE`, `Events.enterviewport`, `CachedImportResults`, `Git`, `PluginDependencies`, `FileSpec`, `TimingSegmentName`, `ISavedObjectsPointInTimeFinder`, `LoaderBundleOutput`, `ScreenTestViewport`, `AdvancedFilter`, `DeleteChannelMessageCommandInput`, `IBox`, `requests.ListComputeGlobalImageCapabilitySchemaVersionsRequest`, `TDiscord.GuildMember`, `ForgeModAnnotationData`, `ChildAttributesItem`, `DBUser`, `RefreshAccessTokenAccountsValidationResult`, `BreadCrumb`, `URL`, `ISequencedDocumentMessage`, `Eventual`, `GraphQLHandler`, `DeleteDatasetRequest`, `Curve`, `IPackage`, `InterfaceTemplate`, `OptionKind`, `NeverShape`, `KeyResultUpdateService`, `IMineMeldAPIService`, `MockProject`, `FileHandlerAPIs`, `HsUtilsService`, `TestRouter`, `MediaTrackSupportedConstraints`, `MLKitRecognizeTextResult`, `AxisBuilder`, `TState`, `GreetingStruct`, `EdmTypeShared`, `TreeFile`, `Theme`, `Variants`, `SpriteFont`, `IndigoOptions`, `IWriteOptions`, `AppStateSelectedCells`, `TRPGAction`, `ContainerContext`, `ColorValue`, `NinjaPriceInfo`, `AgentConnection`, `WordCharacterClassifier`, `Decider`, `VoidFunctionComponent`, `enet.IDecodePackage`, `BlockReference`, `S.Stream`, `RouteRule`, `IButtonStyles`, `SessionUserAgent`, `InheritedChildInput`, `mmLooseObject`, `ModelEvaluateDatasetArgs`, `CtrBroad`, `SignedMessage`, `MessageServiceInterface`, `INodeContainerInfo`, `MockFluidDataStoreRuntime`, `ComboFilterSettings`, `NumericOperand`, `Sql`, `MigrationSubject`, `CompositeTreeNode`, `FlexElementProps`, `PDFRadioGroup`, `MetricName`, `DraggableEvent`, `TypographyDefinition`, `InspectReport`, `RetryAction`, `HashSet`, `WebpackRule`, `ChakraComponent`, `LiteralMap`, `RequestPolicyFactory`, `ReadAddrFn`, `SendDataMessage`, `IMarkdownDocument`, `Batcher`, `IObject3d`, `AttendanceDay`, `IExpression`, `NockDefinition`, `MenuItem`, `ts.ModuleResolutionHost`, `ContactInterface`, `SiteSourceControl`, `ITestPlan`, `app.FileService`, `ICellStructure`, `IHasher`, `GraphQLParams`, `Buildkite`, `IsNumber`, `ISampleSizeBox`, `lspCommon.WorkspaceType`, `FsTreeNode`, `Generic`, `globalThis.MouseEvent`, `DepositKeyInterface`, `DescribeExecutionCommandInput`, `sinon.SinonStubbedInstance`, `DescribeSubnetGroupsCommandInput`, `ApiJob`, `SubscribeEvents`, `IDockerComposeResult`, `PostMessageStub`, `MultilevelSwitchCCReport`, `LogLevel`, `IHydrator`, `MEPChromosome`, `RegisteredClient`, `ContentRepository`, `MacroBuffer`, `ResourcePage`, `apid.ProgramId`, `PrimitiveArg`, `CIMap`, `ViewRect`, `UInt128Array`, `AuthenticationService`, `OpenSearchQueryConfig`, `$FixMe`, `ProcessAccountsFunc`, `HDKeychain`, `EventsTableRowItem`, `Referral`, `VisorSubscription`, `MapPool`, `ITableProps`, `SeriesSpecs`, `ShadowGenerator`, `MapperService`, `SessionCsrfService`, `DateObject`, `EmailConfig`, `ExtraDataTypeManager`, `PartyMatchmakerAdd_StringPropertiesEntry`, `AccountBase`, `NodeParserOption`, `CC`, `ImageResolvedAssetSource`, `LiveAnnouncerDefaultOptions`, `MathfieldPrivate`, `DQLSyntaxErrorExpected`, `StacksNetwork`, `ObjectFetcher`, `Panner`, `Pkg`, `ErrorBarSelector`, `ExecutionResult`, `MockBaseService`, `BMD`, `d.OptimizeJsInput`, `OrderType`, `CustomAnimateProps`, `ScopeContext`, `Compatible`, `DevServerEditor`, `ScopeQuickPickItem`, `ViewFunctionConfig`, `StopExperimentCommandInput`, `GradientObject`, `RegisterDr`, `Distance`, `DisplayableState`, `TodoController`, `TaskChecklistItem`, `InternalKeyComparator`, `JumpFloodOutput`, `VarianceScalingArgs`, `ISizeCalculationResult`, `StringLiteral`, `CopyDirection`, `ImageInfo`, `tmp.DirResult`, `UnionC`, `APropInterface`, `OrganizationContext`, `FieldContextValue`, `StackHeaderInterpolatedStyle`, `UserDataContextAPI`, `ListTagsCommand`, `ComplexArray`, `BucketHandler`, `ScrollState`, `IQueryParamsConfig`, `GitHubActionWorkflowRequestContent`, `t.Node`, `DataStreamInfo`, `Switch`, `IDerivation`, `DateRangeMatch`, `ChildSchoolRelation`, `P5`, `IndexStats`, `FileStats`, `SymbolDefinition`, `CellValueChangedEvent`, `UpdateUserInput`, `RenderSchedule.ScriptProps`, `MochaOptions`, `IApolloContext`, `StyleRecord`, `SelectableListService`, `supertest.SuperTest`, `BinaryHeap`, `InterfaceWithConstructSignatureReturn`, `VideoLayer`, `IEcsDockerImage`, `BarEntry`, `Cloud`, `ReduxState`, `IValueChanged`, `NormalizedDiagnostic`, `TBook`, `SceneTreeTimer`, `ResponseMeta`, `ElUploadRequest`, `builders`, `DateTimeFormat`, `PartitionedFilters`, `ListUsersCommand`, `ErrorService`, `Disposable`, `DescribeDatasetImportJobCommandInput`, `CustomMapCache`, `SubstrateEvent`, `StreamFrame`, `TransitionPreset`, `ReadOnlyFunctionOptions`, `DirectThreadEntity`, `Mocha.Context`, `SFProps`, `ViewPropertyConfig`, `prettier.Options`, `TPath`, `UIEventSource`, `vscode.TextLine`, `SettingsProvider`, `DeviceTypeJson`, `ContactSubscriptions`, `DataObject`, `ListAlarmsRequest`, `CodepointType`, `ContextWithMedia`, `GraphQLEntityFields`, `TTag`, `FlexLine`, `GraphQLResolverContext`, `SitesFixesParserOptions`, `DecoratorNode`, `ts.UserPreferences`, `WrapExportedClass`, `CompleteResult`, `execa.ExecaChildProcess`, `ISuggestValue`, `PersistedSnapshot`, `WebDNNWebGLContext`, `TypeDef`, `CollisionObject2DSW`, `TransactionPayload`, `vscode.EndOfLine`, `SourceCodeInfo_Location`, `CliInfo`, `requests.ListWafLogsRequest`, `ICoverageFragment`, `ApiInterfaceRx`, `PersistAppState`, `AstNode`, `PLI`, `requests.ListCloudVmClusterUpdateHistoryEntriesRequest`, `InstancePrincipalsAuthenticationDetailsProvider`, `WorkRequestStatus`, `TreeEdge`, `VariableUiElement`, `BlockElement`, `ColumnProps`, `AppleTV`, `WXML.TapEvent`, `ListDomainNamesCommandInput`, `ITagProps`, `RTCIceTransport`, `Ad`, `ArticleStateTree`, `ClusterEvent`, `WorldgenRegistry`, `SyntaxDefinition`, `AnchorBank`, `GradleVersionInfo`, `TsSelectComponent`, `Victor`, `EmailTempState`, `IExtentChunk`, `ITrackEntry`, `ShaderVariable`, `WorkerProxy`, `PriceState`, `TranslatedValueID`, `IFileDescription`, `ImGui.Vec2`, `PythonPreviewConfiguration`, `d.CompilerBuildResults`, `EventDelegator`, `InstanceLocator`, `DatasourcePublicAPI`, `InferableComponentEnhancerWithProps`, `CreateDatabaseCommandInput`, `VoiceConnection`, `WrapOptions`, `IVoicemail`, `IRNGNormal`, `s.Field`, `PersonAssignmentData`, `AP`, `LazyMedia`, `LintResult`, `Bus`, `ConsolidateArgs`, `PlasmicConfig`, `CausalRepoIndex`, `NavigationIndicator`, `ClassMetadata`, `IAppStrings`, `DeleteDestinationCommandInput`, `SchemeRegistrarWrapper`, `PathItemObject`, `RecipientOrGroup`, `poller.IPollConfig`, `GherkinQuery`, `Multer`, `AddonClass`, `MaterialAccentColor`, `UrbitVisorConsumerExtension`, `Account`, `ComponentDecorator`, `BabelOptions`, `AuxUser`, `TabStyle`, `DeleteInstanceProfileCommandInput`, `BudgetResult`, `EmailConfirmationsStore`, `ScriptData`, `AccessTokenProvider`, `TinyQueue`, `VgApiService`, `DictionaryEntryNode`, `BlockNode`, `RTCIceGatherer`, `TldrawApp`, `Banner`, `MapBounds`, `CheckpointNode`, `Integer`, `Interfaces.IBroker`, `ConfigurationCCBulkSet`, `StyledOtherComponent`, `Others`, `RoomItem`, `MethodAst`, `DefaultTreeDocument`, `ContextMenuExampleProps`, `ChannelInflator`, `ComponentStrings`, `EndpointDefinition`, `UITabBarController`, `FullIndex`, `Preset`, `IAttr`, `CommonMiddleware`, `ApiMethod`, `NearSwapTransaction`, `InitParams`, `OpenSearchDashboardsDatatable`, `ZonedDateTime`, `IndexPatternRef`, `IDocumentFragment`, `GlobalEventName`, `PromptProps`, `CreateChannelBanCommandInput`, `ActorArgs`, `IResultSetElementKey`, `PredictionContext`, `GridBase`, `EffectFunction`, `GroupMembershipEntity`, `UtilObject`, `https.AgentOptions`, `SDK`, `ObjectDetails`, `_ISelection`, `Config.IConfigProvider`, `IConfigurationExtend`, `Widget.ChildMessage`, `IToastOptions`, `UserResult`, `TestingSystem`, `IBaseTabState`, `LoginForm`, `DebugStateAxes`, `EdmxEntityTypeV4`, `UInt256`, `SemanticRole`, `MessageDataFilled`, `ethOptionWithStat`, `Event1EventFilter`, `vscode.CompletionList`, `CommentState`, `ItemEntity`, `ResponseWrapper`, `MenuSurfaceBase`, `PIXI.Graphics`, `InMemoryLiveQueryStore`, `TLockfileObject`, `DeviceChangeObserver`, `JsSignatureProvider`, `ExcludedEdges`, `ListKeyVersionsRequest`, `StringLiteralExpr`, `Link`, `Events.pointercancel`, `MDCBottomSheetController`, `identity.IdentityClient`, `MemberDoc`, `FaktoryControl`, `HeadClient`, `IConversation`, `DiffedURIs`, `PublishOptions`, `theia.SemanticTokensLegend`, `AppServiceBot`, `ConnectedPeer`, `ChangeLanguage`, `LocalActions`, `V3SubgraphPool`, `IConnectionExecutionContextInfo`, `YAMLSchemaService`, `IInvoiceUpdateInput`, `CreateCard`, `PackagePolicyVars`, `IEpochOverview`, `AuxVM`, `IndexedPolyface`, `OutlineSharedMetricsPublisher`, `FurMulti`, `PrivateEndpoint`, `CollateralRequirement`, `IAppServiceWizardContext`, `SqliteValue`, `UnaryContext`, `TSExpr`, `Tags`, `MessagingDevicesResponse`, `Intermediate`, `ExtensionData`, `CodeGenerator`, `ImGui.DrawList`, `MyObject`, `RouterOutlet`, `requests.ListRouteTablesRequest`, `GenesisBlock`, `Accountability`, `FocusPath`, `BalanceActivityCallback`, `ChatMessageType`, `ErrorReporter`, `BigFloat32`, `SerializeCssOptions`, `RenderElement`, `VirtualContestProblem`, `SoftVis3dMesh`, `NumericType`, `MapState`, `GetGroupResponse`, `KernelConfig`, `InternalServerException`, `PackageService`, `Semaphore`, `VersionId`, `ListReleaseLabelsCommandInput`, `RowSchema`, `MapView`, `LanguageServiceHost`, `FakeHttpProvider`, `IDBCursorWithValue`, `TRWorld`, `ko.Subscription`, `CommitStatus`, `PageBlobClient`, `ArgType`, `ErrorReport`, `ThemeConfiguration`, `Issuer`, `IAngularScope`, `SceneDesc`, `StreamingStatus`, `ControlPoint`, `LLink`, `App.IPolicy`, `AlbumService`, `MXCurve`, `HttpMethod`, `RowProps`, `TradeExchangeMessage`, `HorizontalAlignment`, `JsonRpcId`, `GetRepository`, `KeyIndex`, `ElkLabel`, `GlyphCacheEntry`, `AlertOptions`, `FavoriteGroup`, `MonzoService`, `ConfigurationService`, `SQLeetEngine`, `QueryNodePath`, `VatLayout`, `ListTagsForResourceInput`, `InMemoryConfig`, `ValidateRuleOptions`, `BaseFactory`, `IRootReducer`, `EmployeeViewModel`, `WorkspaceProject`, `SFCScriptBlock`, `ReducerMap`, `IUIMethodParam`, `WrappedProperties`, `Chlorinator`, `IBuilder`, `DecoderFunction`, `CovidData`, `MaterialMap`, `Mocha.Test`, `AnyField`, `HookBase`, `DemoSettings`, `android.support.v7.widget.RecyclerView`, `NgbModal`, `SharedElementSceneData`, `NavigatorState`, `SnackbarContextInterface`, `Directus`, `IDifferences2`, `Op`, `TestTemplate`, `IContainer`, `WindowRect`, `AudioNode`, `JPABaseEmitter`, `Proof`, `UserManager`, `IWrappedEntity`, `UserMusicDifficultyStatus`, `MagickFormat`, `ZIlPayCore`, `VarUsages`, `ConnectedComponentClass`, `PanelsState`, `TheMovieDb`, `HttpErrorHandler`, `ComboFilter`, `TransactionsState`, `SlatePlugin`, `SerializableConstructor`, `StateProps`, `AxisProperties`, `__HttpResponse`, `IServiceConstructor`, `d.ComponentCompilerEvent`, `LocalStorageArea`, `DeploymentOptions`, `AppiumDriver`, `WordcloudViewModel`, `HarmajaOutput`, `OriginAccessIdentity`, `DeclarativeEnvironment`, `NumberListProps`, `SubtitlesCardBases`, `ItemStat`, `ExtraButtonComponent`, `SnackbarMessage`, `MaybeLazy`, `DynamoDB.UpdateItemInput`, `MediatorFactory`, `EmailVerificationToken`, `YallistNode`, `StaticCollider`, `RadarPoint`, `sdk.PullAudioInputStream`, `ImagePickerControllerDelegate`, `DeleteButtonProps`, `CloudWatch`, `SimpleExpression`, `Discord.Channel`, `Rank`, `NumberInputOptionProps`, `IDiagnosticsResults`, `FunctionAppContext`, `Zipper`, `UpdatableChannelDataStore`, `ILeaseState`, `IWaterfallTransaction`, `IExpectedArtifact`, `IExtentModel`, `lf.Predicate`, `ApiKey`, `ResponseInit`, `FlowBranchLabel`, `BundleModule`, `ListInstanceProfilesCommandInput`, `DefinitionFilter`, `THREE.WebGLRenderer`, `AgentQq`, `IRootPosition`, `ThemeOption`, `ExprDependencies`, `NamedDeclaration`, `CloudflareApi`, `FileRepositoryService`, `Pooling3DLayerArgs`, `BYOCLayer`, `CodeWriter`, `InternalUnitRuntimeContext`, `DeepImmutableObject`, `Resilience`, `KeyedSelectorFn`, `NavigationViewModel`, `ArchiveEntry`, `ListViewWrapper`, `SymbolSize`, `BezierCurve`, `CreateNetworkProfileCommandInput`, `anyNotSymbol`, `PowerShellScriptGenerator`, `DebugProtocol.Event`, `MessageMock`, `Decimal`, `ParameterDeclaration`, `SchemaMatchType`, `SavedObjectsIncrementCounterOptions`, `UUIDMetadataObject`, `ScriptThread`, `RegulationHistoryItem`, `DropInPresetBuilder`, `ValidateErrorEntity`, `ControlPanelState`, `Relationship`, `TaskContext`, `AxeResultsList`, `QueryEngineEvent`, `StartOptions`, `SvelteSnapshotManager`, `CharacterSetECI`, `TestClock`, `DeletePolicyVersionCommandInput`, `FileWithMetadata`, `TextTip`, `RBNFInst`, `AnimationKey`, `ComplexExpression`, `ValidationHandler`, `AthleteUpdateModel`, `RankingItem`, `ListProjectsCommand`, `MiddlewareCreator`, `CubeArea`, `StatusBar`, `SceneActuatorConfigurationCCGet`, `JPAResource`, `StyleSanitizeFn`, `ast.WhileNode`, `CaseBlock`, `PluginInitializerContext`, `SimulatedTransactionResponse`, `BuildMatch`, `StaffDetails`, `P2PMessagePacketBufferData`, `QuotaSettings`, `StrongExpectation`, `ParticipantsRemovedEvent`, `IndieDelegate`, `SavedObjectsClosePointInTimeOptions`, `d.CompilerSystem`, `ISdkBitrateFrame`, `FreeBalanceClass`, `DocProps`, `CardConfig`, `CreateRawTxOut`, `ElementPaint`, `DescribeImagesRequest`, `DomNode`, `TokenTransferPayload`, `d.ComponentCompilerStaticProperty`, `Knex`, `PDFFont`, `ArithmeticInput`, `Debugger`, `ReactEditor`, `EmberAnalysis`, `ShorthandRequestMatcher`, `PaginateResult`, `CommitOptions`, `HintManager`, `JestAssertionError`, `ParameterJoint`, `ObjectWithId`, `TabProps`, `FunctionTypeResult`, `LightBound`, `InterfaceWithEnumFromModule`, `IterationUse`, `EChartsOption`, `UnionOrIntersectionTypeNode`, `ExpressionAttributes`, `YamlMappingItem`, `CreateApiKeyCommandInput`, `LinesGeometry`, `OrgEntityPolicyOperations`, `UserEnvelope`, `MempoolTransaction`, `NgModuleType`, `requests.ListProtocolsRequest`, `HTMLIonModalElement`, `ReturnType`, `BeneficiaryDTO`, `FeatureFlagType`, `DependenceGroup`, `ZipOptions`, `ValidationFunction`, `SearchInput`, `AcceptCallbacks`, `d.Screenshot`, `ILineIndexWalker`, `StateObservable`, `QuerySnapshotCallback`, `ComponentPortal`, `LRUCache`, `CommentThread`, `WindowSize`, `CompressedJSON`, `IntegrationTypes`, `PlayerLadder`, `MessageExecutor`, `Robot`, `DlpServiceClient`, `ZoneManager`, `Red`, `Events.pointerenter`, `BlockFormatter`, `ErrnoException`, `ProfileProviderResponse`, `IndexedTrendResult`, `WalletDeploymentService`, `NonFungibleTokenAPI.Options`, `IJetURLChunk`, `NgIterable`, `RenderTarget_t`, `CircleBullet`, `InstructionWithTextAndHeader`, `ClassificationType`, `Buckets`, `ConflictException`, `DialogueTest`, `DataTable`, `Binary3x3x3Components`, `VdmEnumType`, `ElementAst`, `PartyJoinRequestList`, `TranslationFormat`, `SyncStatus`, `ICreateOptions`, `AddTagsToResourceMessage`, `cc.Event.EventKeyboard`, `GetRepositoryCommandInput`, `ZeroXPlaceTradeParams`, `InterfaceAlias`, `AliasName`, `StateNavigator`, `ValveState`, `PageSourceType`, `OAuthExtension`, `CartPage`, `CameraType`, `ButtonLabelIconProps`, `CalculationScenario`, `SFAMaterialBuilder`, `TokenStat`, `Pool.Options`, `RtcpPayloadSpecificFeedback`, `DisplayObject`, `ConfigurationPropertyDict`, `IResourceAnalysisResult`, `TooltipService`, `TItemsListWithActionsItem`, `LovelaceCardConfig`, `CallerIdentity`, `IOptimizelyAlphaBetaTest`, `ArrayLike`, `VFSEntry`, `ICompileService`, `ISubscriberJwt`, `AutoFilter`, `StampinoTemplate`, `SyncMember`, `ApprovalPolicyService`, `SmartHomeApp`, `ListFindingsRequest`, `Ink`, `IPayment`, `mendix.lib.MxObject`, `FormatterParam`, `JobTypes`, `ResolvedOptions`, `AccountSetOpts`, `VoiceChannel`, `SnapshotNode`, `AndroidConfig.Manifest.AndroidManifest`, `DefaultDataServiceConfig`, `WatchBranchEvent`, `PathOrFileDescriptor`, `CopySink`, `RuleMetadata`, `ReconciliationPath`, `AttributeDatabindingExpression`, `ApifySettings`, `SliderGLRenderer`, `LoggerOutput`, `CalcValue`, `DeploymentCenterFormData`, `GlobalTag`, `TemplateStringsArray`, `FoodRelation`, `SavedObjectDescriptor`, `FavoritePropertiesOrderInfo`, `PlanStep`, `Lead`, `ArrayRange`, `ApplicationEntry`, `VaultActive`, `IndexBuffer3D`, `ModelLayer`, `SpatialViewDefinitionProps`, `SourceLoc`, `EditorDescription`, `SessionsActions`, `WebLayer3DBase`, `TypedReflection`, `MultiKeyComparator`, `IAuthState`, `SchemaOverview`, `BaseService`, `EventsMessage`, `PiEditPropertyProjection`, `RequestContract`, `PendingAction`, `DelegatorReward`, `NoteService`, `ParameterOptions`, `ArrayBufferWalker`, `HeapInfo`, `NzMessageRef`, `AccountData`, `ValueSource`, `Serializer`, `ParticipantsJoinedListener`, `DynamicEntry`, `AirGapWallet`, `MangolLayer`, `IStaggerConfig`, `ISeed`, `HostCancellationToken`, `UrlGeneratorsStart`, `TileCoordinates`, `DeferredPromise`, `Client.ProposalResponse`, `ILoggerInstance`, `RootActionType`, `CoreUsageStats`, `GfxRenderPassDescriptor`, `IDomainEntry`, `GroupArraySort`, `Gatekeeper`, `ObjectList`, `TurndownService`, `FileDescription`, `ITreeData`, `VisContainerProps`, `BlogActions`, `ValidationOptions`, `ServiceIdentifier`, `CardsWrapper`, `PolyfaceVisitor`, `Conjugate`, `ContractWhiteList`, `Class`, `ProcessorInternal`, `IDynamicGrammarGeneric`, `SanityChecks`, `SpeakDelegate`, `IScore`, `FilesChange`, `PostsState`, `UsePaginatedQueryOptions`, `EVM`, `core.VirtualNetworkClient`, `ConstantArgs`, `ContactModel`, `LABEL_VISIBILITY`, `WetPlaceholder`, `IParseAttribute`, `FindByIdOptions`, `DeleteDistributionCommandInput`, `MBusTransaction`, `TableFormDateType`, `HammerLoader`, `Schema$Sheet`, `YawPitchRollAngles`, `SlashCommand`, `Express.NextFunction`, `TypeError`, `CrossConnectMapping`, `ProviderRpcError`, `T_0`, `JsonPath`, `RushConfiguration`, `GenericEvent`, `FiberNode`, `zmq.Pair`, `BlockchainTimeModel`, `TrackEventParams`, `GlobalSearchProviderResult`, `Eyeglasses`, `ColorPreviewProps`, `Fish`, `DiagnosticLevel`, `AssignedContentType`, `RowVM`, `CategoricalParameterRange`, `MethodDescriptorProto`, `HumidityControlMode`, `DefinitionRange`, `MagickReadSettings`, `GoalStatus`, `MaterialUiPickersDate`, `FB3ReaderPage.ReaderPage`, `AccessibilityOptions`, `EsErrors.ElasticsearchClientError`, `NextAuthOptions`, `MacroActionId`, `MailStatusDto`, `MdcSlider`, `Node_Enum`, `TestActionContext`, `TokenBucket`, `SkyBoxMaterial`, `ListTournamentRecordsAroundOwnerRequest`, `vscode.CompletionItemKind`, `CdkScrollable`, `DNSLabelCoder`, `SGDOptimizer`, `StringSet`, `ErrorEmbeddable`, `ObjectAssertionMember`, `IcuExpression`, `nsISupports`, `AutoCompleteEventData`, `ModalSize`, `NamedIdentityType`, `interfaces.Bind`, `ColumnDefinitions`, `EventNote`, `GameDataInterface`, `XMLElementOrXMLNode`, `ICloneableRepositoryListItem`, `CommandLine`, `SubscribeCommandInput`, `Polynomial`, `MultisigData`, `InputArgs`, `RequestTemplateReference`, `DurationInput`, `MangoClient`, `CameraRig`, `BooleanExpression`, `MarkdownTable`, `TemplateData`, `EnrichmentPipeline`, `DynamicCommandLineAction`, `ServiceDefinition`, `SwitchKeymapAction`, `CustomerContact`, `VisualEditor`, `EthAddress`, `AlertType`, `BindingAddress`, `HookFn`, `LinkProof`, `EventDestination`, `ITransformResult`, `RenderColorTexture`, `IBoxPlot`, `ColumnProp`, `AirlineService`, `FunctionField`, `SHA512`, `LevelUpChain`, `ButtonText`, `CurrencyMegaResult`, `ts.Decorator`, `WTCGLRenderingContext`, `SxSymbol`, `DelNode`, `SinonSpyCall`, `ActionType`, `ConfigurationManager`, `HSLVector`, `DiscordBot`, `CanvasKit`, `EditDashboardPage`, `SettingsValue`, `FreePoint`, `ManagementDashboardTileDetails`, `BackendError`, `BridgeConfig`, `TimeSeriesMetricDefinition`, `IVector4`, `HandshakeType`, `IVisualHost`, `FormInput`, `StackUtils`, `TypeReferenceSerializationKind`, `IHistorySettings`, `PlasmicLock`, `android.content.Context`, `FoodItem`, `IWorkflowBase`, `Escrow`, `Objects`, `ReleaseProps`, `vscUri.URI`, `Some`, `RootAction`, `ModalNavigationService`, `IAllTokenData`, `RenderTexture`, `FirebaseHostingSite`, `SharedAppState`, `GuildChannelResolvable`, `LiteralExpression`, `VantagePointInfo`, `IModelAnimation`, `PostCSSNode`, `UpdateRequestBuilder`, `GoThemeBackgroundCSS`, `ContextMenuDirection`, `JobRunSummary`, `ArgumentsType`, `StellarCreateTransactionOptions`, `TooltipModel`, `ReshapeLayerArgs`, `FindOneOptions`, `FlowTransform`, `FlexibleAlgSource`, `SignalState`, `GL2Facade`, `UniqueObject`, `AlertConfig`, `ListPager`, `WebhookSettings`, `IBaseRequestAction`, `IFileRange`, `FilterValue`, `chrome.contextMenus.OnClickData`, `SupportContact`, `IDrawData`, `IPeerLogic`, `ElementPropsWithElementRefAndRenderer`, `LineWidth`, `ConfigurationGroup`, `ExtraValues`, `GetRepositoryStatisticsPayload`, `CompositeMapper`, `IMapPin`, `SFieldProperties`, `CLICommand`, `SignCallback`, `IMesh`, `AltStore`, `MorphTarget`, `RequestInterceptor`, `IntType`, `MenuStateModel`, `JSONFormatter`, `OrmService`, `SessionConfiguration`, `CameraFrameListener`, `HALEndpointService`, `ValueMetadataDuration`, `RestoreWalletHandler`, `AuthAndExchangeTokens`, `GlyphData`, `TransitionController`, `HouseCard`, `RegionHash`, `AssetPropertyValue`, `PostProps`, `MarkupKind`, `UNK`, `BillDate`, `InstrumentName`, `EditStatus`, `QueryResultRow`, `DynamoDBStreamEvent`, `ButtonType.StyleAttributes`, `ICircuitState`, `SpekeKeyProvider`, `PlaceAnchor`, `FadingParameters`, `TokensList`, `GossipTimestampFilterMessage`, `mpapp.IPageProps`, `ClipPlane`, `NineZoneNestedStagePanelsManager`, `Principal`, `Highcharts.NetworkgraphLayout`, `VectorTransform`, `PackagerInfo`, `LabelDefinition`, `MDL0Model`, `SchemaCxt`, `BoardBuilder`, `SourceFileSystem`, `OutputProps`, `CustomerService`, `LanguageEntry`, `Push`, `DateParser`, `ViewModelQuery`, `yargs.CommandModule`, `RPCProtocol`, `Reverb`, `XroadIdentifier`, `PropertyDefinition`, `TickResultEnum`, `DetectionMetrics`, `Project.Root`, `GlobalConstraintRegistrarWrapper`, `SymbolIndex`, `DescribeRepositoriesCommandInput`, `React.ComponentType`, `Thunk`, `cloudwatch.MetricChange`, `RelationComparisonResult`, `AnnotationShape`, `CommandBuildElements`, `PubkeyResult`, `DescribeDBClusterParametersCommandInput`, `Json.Property`, `DataCardEffectPersonType`, `ActivityType`, `App.storage.ICachedSettings`, `thrift.TProtocol`, `MaterialAlertDialogBuilder`, `EntityCacheReducerFactory`, `ClusterContextNode`, `Types.Id`, `BeforeCaseContext`, `LabelOptions`, `StopTransformsRequestSchema`, `TypeOrUndefined`, `WebGLResourceHandle`, `ImportSpecifierArray`, `SocketMessages.produceNum`, `Id64Arg`, `SCSSParser`, `OperationResponse`, `FormlyTemplateOptions`, `ISuiteResult`, `PDFDropdown`, `IOAuthTokenResponse`, `PipelineRuntimeContext`, `IOSSplashResourceConfig`, `Decorator`, `DictionaryModel`, `ImportedRecord`, `ChangeVisitor`, `TransposeAttrs`, `GetAccessorDeclaration`, `... 15 more ...`, `SignatureHelpContext`, `AttandanceDetail`, `DataTypeResolver`, `LoadConfigResults`, `ViewManager`, `AsyncSubject`, `LexPosition`, `requests.ListSessionsRequest`, `Annotation`, `MeshComponent`, `ExportDeclaration`, `BinarySensorCCGet`, `FederationClient`, `CodeEdit`, `EmptyActionCreator`, `FirestorePluginOptions`, `TypeConfig`, `estypes.ErrorCause`, `PropTypesMapping`, `GetOpts`, `ActivityTypes`, `TextState`, `HandlerAction`, `UpdateChannelRequest`, `ChannelModel`, `UndoStack`, `HotkeyConfig`, `AppRegistryInfo`, `SubscriptionService`, `OptionGroup`, `BatteryStateEntity`, `Web`, `MediaTags`, `EstimateGasValidator`, `VueTag`, `IGLTFLoaderExtension`, `IWarningCollector`, `PathBuilder`, `IRemix`, `ProgressionAtDayRow`, `RollupCache`, `PriceScale`, `TableModelInterface`, `EnhancedItem`, `SignedTokenTransferOptions`, `CellGroup`, `LabelChanges`, `ProjectedXY`, `Identifiers`, `NBTPrototype`, `HomePluginStartDependencies`, `AstPath`, `TextSelection`, `ImGui.Style`, `SpendingConditionOpts`, `SQLNode`, `ScraperArgs`, `cytoscape.CollectionElements`, `ListAppInstanceUsersCommandInput`, `CompletionItem`, `Mounter`, `GetResourcesCommandInput`, `PainlessCompletionResult`, `ScheduleItem`, `IOrderResult`, `CreateServerCommandInput`, `HealthType`, `DetailViewData`, `ListSecretsRequest`, `MutationFunc`, `RedisAdapter`, `MutationTypes`, `IExecuteFunctions`, `TsxComponent`, `AlphaTest`, `CompareMessage`, `ContainerRepository`, `NefFile`, `BracketTrait`, `VideoPreferences`, `HtmlOptions`, `ProductInformation`, `DeleteMemberCommandInput`, `RemoveOptions`, `TimelineBuckets`, `ModernServerContext`, `DeviceDescriptor`, `BeneficiaryApplication`, `ObstaclePortEntrance`, `EvaluatorUsage`, `MoveType`, `IColorHierarchy`, `NatGateway`, `MongoCron`, `CharData`, `Profiler`, `CertificateResponse`, `FieldMetadata`, `TestHookArgs`, `requests.CreateConnectionRequest`, `GeistUIThemes`, `CommandValues`, `MutableList`, `BaseUAObject`, `TResponse`, `SortField`, `AnimatedValue`, `CompressionTextureTypeEnum`, `ApiPipeline`, `CardRenderDynamicVictoryPoints`, `FloatValue`, `InterpolateExpr`, `AzureWizardPromptStep`, `PersonStatusType`, `Queryable`, `AdmZip`, `EventActionHandlerActionCallableResponse`, `SubqueryProject`, `InjectionKey`, `ValueTypeOfParameter`, `CompletionTriggerKind`, `AnyPatternProperty`, `PaletteThemeConfig`, `DraggableList`, `ParsedProperty`, `CharLevelState`, `Events.precollision`, `EntitySchemaService`, `FileEntry`, `CompiledCard`, `TelemetrySavedObject`, `Nexus`, `ENABLED_STATUS`, `CursorBuffer`, `ScreenEventType`, `ExpenseService`, `CellClassParams`, `DeSerializers`, `StoreChangeEvent`, `TorusStorageLayerAPIParams`, `RelatedRecords`, `BaseAxisProps`, `CategoryDataStub`, `Defunder`, `WorkspaceFolder`, `FrameworkEnum`, `requests.ListKeyStoresRequest`, `StateManagerImpl`, `RegularStep`, `LuaState`, `CrochetCommand`, `AnyRegion`, `ListSnapshotBlocksCommandInput`, `MerchantGameActivityEntity`, `SettingsModel`, `FuzzyScore`, `LayoutDto`, `IArtist`, `BufferLines`, `PartytownWebWorker`, `MyAudioContext`, `ApiConfig`, `GraphPath`, `SourceRenderContext`, `FabricGatewayRegistry`, `JsxSpreadAttribute`, `IUpworkApiConfig`, `Mutator`, `HdPublicNode`, `IOfflineData`, `TemplateFile`, `IWrappedExecutionContext`, `JointOptions`, `RookCephInputs`, `CfnParameter`, `SharePluginStart`, `SyncArgs`, `RSTPreview`, `StackScreenProps`, `VpcConfiguration`, `RadioProps`, `ProcessListener`, `TransportResponse`, `ITableData`, `ReStruct`, `GridReadyEvent`, `ResourceChange`, `SaveFileWriter`, `TestNode`, `PluginsSetup`, `TexFunc`, `ViewFilesLayout`, `DefaultAzureCredential`, `ItemDataService`, `TimefilterSetup`, `ICommandOptionDefinition`, `DatModelItem`, `d.SourceMap`, `LocalizedLabels`, `ParsedMessagePartICUMessageRef`, `CurriedGetDefaultMiddleware`, `TweetMedia`, `FooBar`, `IListener`, `UnionOptions`, `DAL.DEVICE_ID_SYSTEM_TIMER`, `InputHTMLAttributes`, `BarRectangleItem`, `ExtractedAttr`, `SankeyPoint`, `EllipseEditUpdate`, `TidalExpression`, `IProjectData`, `DefaultDataServiceFactory`, `CampaignsModelExt`, `ConceptInstance`, `DerivedKeys`, `Transformer`, `ServiceGetPropertiesResponse`, `DashboardConfig`, `ResourceActionMap`, `CreateRoomRequest`, `SimplifiedType`, `QuantumMove`, `Container`, `PortMapping`, `AnnotatedError`, `SqlTuningTaskCredentialTypes`, `core.ApiRequest`, `ParticipantsLeftListener`, `ProjectStorage`, `EngineResults.ListMigrationDirectoriesOutput`, `LayerConfig`, `ExtractCSTWithSTN`, `vscode.Memento`, `WebClient`, `PrimitiveModeEnum`, `TerminalOptions`, `IToolchian`, `CONTENT`, `ExceptionBreakpoint`, `ErrorsByEcoSystem`, `ListAppsCommandInput`, `DataSetupDependencies`, `ExpBoolSymbol`, `React.FunctionComponent`, `LayoutManager`, `DescribeVpcPeeringConnectionsCommandInput`, `VueConstructor`, `TImageType`, `requests.ListOceInstancesRequest`, `ListJobsCommand`, `ResultInterface`, `DependencyOptions`, `BoundingBox`, `IndexPatternDeps`, `DocViewInput`, `Convolver`, `GeometricElement`, `PageQueryOptions`, `IParam`, `Suggest`, `GfxDeviceLimits`, `AuthenticateDeviceRequest`, `RpcConnectionWriter`, `AwrDbCpuUsageSummary`, `ItemPriceRate`, `BigInt`, `AcctStoreDict`, `bitcoin.Psbt`, `Arweave`, `IAjaxSettings`, `Matrix4x4`, `SerializedConcreteTaskInstance`, `btCollisionShape`, `ArrayProps`, `ODataFunctionResource`, `IGetExportConfigsResponse`, `IModelType`, `ZWaveError`, `IconConfig`, `Rebind`, `RunningGameInfo`, `IApiTag`, `EllipticPair`, `SurveyResultModel`, `GetMembersCommand`, `V1Service`, `XmlNamespacesCommandInput`, `K3`, `AccountFilterParams`, `ZosJobsProvider`, `ICombo`, `B11`, `OpenApiOperation`, `SkinnedMesh`, `IsSkipFeature`, `ToolChoice`, `GetStaticPaths`, `CreateCommentDto`, `ServiceMonitoringServiceClient`, `UnicodeSurrogateRangeTable`, `AnyFn`, `BlockInfo`, `Web3.CallData`, `ioBroker.Object`, `RefLineMeta`, `ITemplateMagic`, `AssignmentStatus`, `StubHelper`, `Highcharts.MapLatLonObject`, `ContentLoader`, `MappableType`, `SuiComponentFactory`, `HTTPMethod`, `FormContextValue`, `PopStateEvent`, `PluginWriteActionPayload`, `TextDocumentContentChangeEvent`, `PluginsServiceSetupDeps`, `NumRange`, `SizeNumberContext`, `MonitorRuleDef`, `ClockFake`, `ex.ExcaliburGraphicsContext`, `IndexRangeCandidate`, `ListVodSourcesCommandInput`, `PopperOptions`, `GetServerSideProps`, `BuildEdgeStyle`, `ChoicesType`, `AuditLog`, `ResolvedLibrary`, `CounterST`, `ReadyPromise`, `PaintServer`, `ANSITerminalStyleRenderer`, `BeanDefinition`, `ScopeSelector`, `ContractAbstraction`, `React.Props`, `InboundMessage`, `MongoManager`, `RawBlockHeader`, `TagExpr`, `Geom.Rect`, `HomeAssistant`, `ImageMimeType`, `PureComponent`, `MetaType`, `IToast`, `IconService`, `tcp.Connection`, `AddToLibraryAction`, `Definition`, `RTCRtpReceiver`, `PropertyNode`, `CustomFormControl`, `TRK1AnimationEntry`, `PluginWrapper`, `mapProperties`, `MangaDetailsFields`, `LogValueArgs`, `ParsedLocator`, `TdpClient`, `ToolAttr`, `ReportData`, `Dir`, `AssetModule`, `ChromeConnection`, `DMMF.ArgType`, `postcss.Rule`, `ExportData2DArray`, `WebElement`, `ResolvedSimpleSavedObject`, `hapi.Request`, `JobStatusResult`, `FileManager`, `RuleResult`, `OneNotePage`, `DidSaveTextDocumentParams`, `InstanceMember`, `PR`, `HsCommonLaymanService`, `RtcpSrPacket`, `IndexSymbolData`, `GeoVector`, `tl.FindOptions`, `AmbientLight`, `Work_Client.WorkHttpClient2_1`, `BrowseCloudDocument`, `apid.EncodeId`, `ClassThatUseDifferentCreateMock`, `Attribution`, `SequelizeModuleOptions`, `AbstractControl`, `OptionName`, `WheelEventState`, `Moltin`, `ListUnspentOptions`, `BulkActionProps`, `AutorestDiagnostic`, `IStdDevAggConfig`, `DataSourceSpec`, `IDynamicOptions`, `MDCRippleFoundation`, `TModel`, `Pitch`, `ManifestData`, `keyboardJS.KeyEvent`, `BrowserWindowConstructorOptions`, `DragEventHandler`, `SnapshotPublicData`, `TaxonomicFilterGroup`, `YellowPepperService`, `PDFWidgetAnnotation`, `BatchCertificateClaim`, `ShapeField`, `ICommandItem`, `GraphQLTaggedNode`, `IDejaDragEvent`, `ITourStep`, `InvoicePromo`, `SubjectDataSetFilter`, `IGitExecutionOptions`, `TransactionWithStatus`, `NetworkSettings`, `CountdownEvent`, `BlockData`, `PresentationManager`, `ParjsCombinator`, `TestData`, `JustifyContent`, `MapLayersService`, `BridgeToken`, `ColumnConfiguration`, `AssociatePackageCommandInput`, `FsFolder`, `mjAlerts`, `ArrayList`, `ChartParameters`, `requests.ListHttpMonitorsRequest`, `CssParser`, `capnp.Orphan`, `ISelectProps`, `ListContactsCommandInput`, `LoopAction`, `ElemAttr`, `jasmine.SpyObj`, `TemplateNode`, `ScannedDocument`, `IGetTimeLogInput`, `CLINetworkAdapter`, `ConfiguredPluginsClient`, `FrameParser`, `RX.Types.DragEvent`, `ObjectMakr`, `EC`, `RPC.KVClient`, `RefForwardingComponent`, `RuleTypeRegistry`, `ts.Block`, `ReadModelRegistry`, `MockAirlineService`, `ConnectState`, `StateChannelExitClaim`, `SimpleASTNode`, `RollupTransaction`, `EmbeddableEditorState`, `CSSResultGroup`, `Ulonglong_numberContext`, `CanvasThemePalette`, `Http3RequestMetadata`, `ICoords`, `SFUISchema`, `DestinationJson`, `TestReader`, `ExpirationDateVerification`, `ReadyType`, `EntityField`, `IndexedClassRewrite`, `InputFieldDefinition`, `ModelOptions`, `Filter`, `Bbox`, `TSelected`, `ColumnChunk`, `PostFrameUpdateType`, `FocusEventHandler`, `ResourceDayHeaderWrapper`, `IDeliveryNetworkResponse`, `ITitusServerGroupCommand`, `RBNFSymbols`, `ListPingProbeResultsRequest`, `GeneratorState`, `ts.LanguageServiceHost`, `MethodNames`, `HdDogePaymentsConfig`, `NotifyArgs`, `IDireflowConfig`, `NgrxJsonApiZone`, `CrochetCommandBranch`, `DirectoryIndexOptions`, `CreatePipelineCommandInput`, `ITransactionIdentifier`, `TinyColor`, `VoidAnyEvent`, `AlainDateRangePickerShortcutItem`, `Hentai`, `GraphQLRequestContext`, `ShareAdditionContent`, `SdkRemoteParticipant`, `QueueSSEService`, `MikroORM`, `ReportFilter`, `WorkspaceExtImpl`, `Submit`, `BookmarkMetadata`, `SetVaultParameter`, `CollisionShape`, `angular.IScope`, `ProcessDataService`, `MentionData`, `serviceDefinition`, `FunctionWithKey`, `UrlForwardingPlugin`, `WebContents`, `HealthCheckResult`, `QueryBus`, `UserMentionEntity`, `OrderStatusReport`, `MagentoProduct`, `EventInfo`, `ChecklistTask`, `JobName`, `IChangeDiscussionItem`, `ReadStorageObjectsRequest`, `UpSetAddons`, `ContractManifest`, `ArrayComparator`, `GenesisProtocolProposal`, `AssociationLifecycleState`, `SavedObjectManagementTypeInfo`, `OmvGeometryType`, `Vector2Like`, `EIP712TypedData`, `ExportFormat`, `OperatorValueFilterDescriptor`, `TxtParentNode`, `CourseActions`, `CountModel`, `MomentDateAdapter`, `LogItemProps`, `GraphQLRequestConfig`, `ParsedExampleTree`, `msRest.Mapper`, `BaseEncryptedPacket`, `DefaultItemType`, `MockMessage`, `ChangeProjectCompartmentDetails`, `InMemoryFileSystem`, `MidiDevice`, `MMOnlineStorage`, `BazelBuildEvent`, `PartialResolvedId`, `StateChannelJSON`, `XPCOMObserverTopic`, `ImageProvider`, `SapphireDbService`, `IMessageFromBackground`, `SharedTreeSummaryBase`, `Hono`, `StopFlowCommandInput`, `DsnComponents`, `DataFactoryClient`, `d.PrerenderStartOptions`, `TypedMessageRendererProps`, `model.domain.DomainElement`, `WebSocketServer`, `ComponentOrTag`, `LoDashStatic`, `Plugin`, `FunctionMap`, `SpeechRecognitionEventArgs`, `FrameResult`, `QueryMiddlewareParams`, `BuildImpl`, `TypedMap`, `WikiPage`, `OhbugMetaData`, `GetterTree`, `HtmlNode`, `GraphQLServer`, `Strip`, `DataLimit`, `GenericTwoValues`, `LRUItem`, `LatLngExpression`, `ErrorListener`, `FailureInfo`, `GluegunAskResponse`, `BodyPixOperatipnParams`, `CollectionDataService`, `EnvironmentVariable`, `DevtoolsPluginApi`, `ReleaseOptions`, `ConfirmationDialogService`, `TodoItemEntity`, `IFormControlProps`, `TopMiddleBottomBaseline`, `LogBuilder`, `Rpc`, `AggregatedResult`, `MetricServiceClient`, `LGraphNode`, `RadarrSettings`, `TreeSeriesNodeItemOption`, `DeviceAccess`, `IndexAliasData`, `jsPDFDocument`, `TapGesture`, `IPlayer`, `ProjectId`, `DatedAthleteSettingsModel`, `ModuleConfiguration`, `RemoteService`, `TwingTokenStream`, `ExprWithParenthesesContext`, `BitbucketAuthTokenRepository`, `SobjectResult`, `THREE.Light`, `PaginationResult`, `CommonPrefix`, `ApiResult`, `TService`, `MacroKey`, `PolyDrawing`, `KillRingEntity`, `FlagsT`, `PDFAcroRadioButton`, `PropTypes`, `PatternLibrary`, `IEditorStore`, `IMacroBuffer`, `CodeLensParams`, `LineMetrics`, `RetryConfigState`, `SchemeObject`, `InlineControl`, `GraphQLCompositeType`, `ParserOptions`, `DissociatePackageCommandInput`, `OperationRequestDetails`, `MovementType`, `FeedPost`, `MultiChannelAssociationCCSet`, `MockErc20Token`, `AccountingTemplateService`, `IBuffer`, `DeferredDefinition`, `DatabaseStatus`, `ApiOperation`, `IErrorInfo`, `PropTypeFinder`, `IProtocolConstructor`, `Bodybuilder`, `DefaultOptionType`, `IMeetingRepo`, `StateFor`, `TestEnvironment`, `d.JsonDocsEvent`, `SymbolSet`, `AppStore`, `CalendarCell`, `PortablePath`, `XMLBuilderContext`, `WorkingHour`, `VisualizeEmbeddableConfiguration`, `TouchingElementInfo`, `OrganizationPoliciesConfig`, `StringEncodedNumeralFormat`, `FunctionDefinitionNode`, `IProposal`, `FieldsConfig`, `SpeakersState`, `HdDogePayments`, `ApplicationContainerState`, `PageScrollService`, `StrokeProtocol`, `DefaultKernel`, `JsonVisitor`, `numericRootOfPolynomial`, `TaskCallback`, `ChannelItem`, `V`, `ChooseImageSuccessCallbackResult`, `execa.Options`, `EventKind`, `DeployHelper`, `DFS_Config`, `UserFormValues`, `JWK.Key`, `Walker`, `ImportBlock`, `TupleData`, `CombatStateRecord`, `PythonPathResult`, `LRParser`, `ShapeT`, `CpuUsage`, `DeleteChannelBanCommandInput`, `Bip32Options`, `ServerlessAzureConfig`, `AccessorEntry`, `JiraColumn`, `MessageConfig`, `SendTx`, `IncrementDirection`, `MetricsPublisher`, `DeployedPlugin`, `CalculatePvService`, `Union`, `DecodedAddress`, `WritableStreamDefaultWriter`, `IntervalSet`, `MultProof`, `EmbeddableStart`, `FunctionalUtilities`, `IRowAPI`, `PlexMetadata`, `MockSelector`, `ComboBoxGroupedOption`, `InanoSQLTable`, `UpdateLongTermRetentionBackupParameters`, `Articulations`, `ECR`, `AnyId`, `ProjectInitializerConfig`, `requests.ListUserGroupMembershipsRequest`, `HttpPrefixHeadersCommandInput`, `OpticsContext`, `fun`, `StandardContentToolsProvider`, `JoinOptions`, `MrujsPluginInterface`, `MetaProps`, `PasswordHistoryView`, `IGceHealthCheck`, `fs.PathLike`, `WinstonLogger`, `UpdateProjectDto`, `FeedbinConfigs`, `SVString`, `ModelObject`, `ResourceKind`, `VirgilPublicKey`, `Survey.JsonObjectProperty`, `TutorialSchema`, `HelpError`, `CalloutArrow`, `VpcContextQuery`, `IBinaryDataConfig`, `ts.ExportAssignment`, `ConstantState`, `K.ExpressionKind`, `PointCloudOctree`, `WrapperLayerArgs`, `WaveformItem`, `InferGetStaticPropsType`, `DiffResultMessage`, `ConfigMetaFormat`, `CocSnippetPlaceholder`, `DescribeOrderableDBInstanceOptionsCommandInput`, `HelpCenterArticleService`, `BoolValue`, `LuaFiledCompletionInfo`, `PutConfigurationSetReputationOptionsCommandInput`, `CHR0_NodeData`, `SubschemaArgs`, `TSESTree.CallExpression`, `SelectionRangeParams`, `WexBimProduct`, `QueueNode`, `StorageFieldItem`, `NpmPackageManipulator`, `BinaryPaths`, `CreateGlobalClusterCommandInput`, `LanguageModelCache`, `LightGroupCircuit`, `GetUpdateConfigParams`, `RollupOptions`, `MockSocket`, `TreeCheckboxStateChangeEventArgs`, `ContextMenuRenderer`, `LaunchOption`, `DrawerHelperOptions`, `LatLngBounds`, `MsgRevokeCertificate`, `TimeRanges`, `InputAndOutputWithHeadersCommandInput`, `IHeaderState`, `ScalarTypeDefinitionNode`, `Collateral`, `i18n`, `ReadTransaction`, `TypeType`, `RangeSliderProps`, `IRuleConfig`, `StateMachine.State`, `ProfileStates`, `DrawerProps`, `SavedObjectsOpenPointInTimeOptions`, `VocabularyCategory`, `FormArrayState`, `ResponseReceivedEvent`, `QuadrantType`, `THREE.Mesh`, `RegistryDocument`, `PostgresClient`, `DescribeCertificatesCommandInput`, `ListSchema`, `IRemoteRoom`, `FabFilesObject`, `WithGenericsSub`, `BaseRenderer`, `RenderFlex`, `PmsiListType`, `InterfaceTypeWithDeclaredMembers`, `Phaser.Input.Pointer`, `ServerTreeItemPageObject`, `BSQRegex`, `TemplateWrapped`, `OperationStack`, `IAnyExpectation`, `BinaryStream`, `Node.Event`, `google.maps.MouseEvent`, `MigrateResolve`, `YfmToc`, `TrackedHasuraEventHandlerConfig`, `VulnerabilityAssessmentName`, `NodeGroup`, `FACE`, `Prefixer`, `Denomination`, `IFile`, `NextCommandOptions`, `PouchFactory`, `IArea`, `SeriesDataSortingOptions`, `StmtDiff`, `SoundService`, `ChainType`, `EventBus`, `AnimationInfo`, `Hooker`, `ScryptParams`, `Tenant`, `STComponent`, `ServiceEndpointPolicyDefinition`, `EmbeddableStartDependencies`, `ArticleList`, `TokenAmount`, `ManagementDashboardSummary`, `ObjectProperty`, `PipelineStatus`, `InternalApplicationSetup`, `PerformanceObserver`, `StateDecorator`, `TypeCheck`, `HapiResponseAdapter`, `DelayFunction`, `DynamicRepository`, `QueryExpressionBodyContext`, `ClrQuickListValue`, `LookupDescriptor`, `NamedMatchMediaProps`, `XmlComponent`, `PrunerPiece`, `Luna`, `IOrchestratorState`, `MangolState`, `ConfigurationPropertyValue`, `IAnalyticsService`, `Boost`, `Discord.Message`, `ComponentConfiguration`, `Remirror.CommandDecoratorOptions`, `MockResponse`, `TransactionInput`, `IDiagnosticsRow`, `Errorable`, `TimestampFormatHeadersCommandInput`, `ReadonlyVec4`, `CompositionTypeEnum`, `PossiblyAsyncOrderedHierarchyIterable`, `d.CssToEsmImportData`, `ImageFiltering`, `TasksStore`, `PhantomWallet`, `ModifyDBSubnetGroupCommandInput`, `VirtualDirectory`, `ChannelPermissionOverwrite`, `NamedArrayBufferSlice`, `d.TestingConfig`, `HttpsAgent`, `IMergeFile`, `BackgroundReplacementVideoFrameProcessorObserver`, `CreateRegexPatternSetCommandInput`, `ExpectedResponse`, `NodeRange`, `RequireStatementContext`, `SetupFunc`, `OnFailure`, `TouchEventHandlerType`, `DBType`, `GraphQLArgument`, `Chart.CallbackFunction`, `SmallLicense`, `NormalMod`, `requests.ListTopicsRequest`, `AuthCore`, `BaseAppearanceService`, `NumberInput`, `ITelemetryErrorEvent`, `ProjectRisk`, `DeployedWallet`, `Completion`, `Apply3`, `I18NService`, `AuthenticationProvider`, `FilterCondition`, `PushResponse`, `ISearchStart`, `FnU3`, `InsertionType`, `GridPattern`, `Study`, `EngineArgs.MarkMigrationRolledBackInput`, `HandleElement`, `SegmentRange`, `BorderStyleProps`, `CoreEditor`, `S`, `BasicObstacleSide`, `MetadataPackage`, `VtxLoaderDesc`, `EntryObject`, `CollisionDirector`, `RawCard`, `GetInviteCommand`, `fs.Stats`, `BackwardScanner`, `CipherAlgorithm`, `SlideUIEvent`, `IHttpService`, `LocaleMap`, `StockData`, `HaveIBeenPwnedApiResponse`, `RoadmapType`, `ClientItemViewModel`, `instantiation.IConstructorSignature4`, `Quote`, `ts.TypeChecker`, `IFiles`, `CellInfo`, `BlockAction`, `BezierCurve3d`, `LaunchTemplateSpecification`, `CreateAppOptions`, `IMetricListener`, `Loader`, `ReserveData`, `TimelineRowStyle`, `Actor`, `ListNamespacesCommandInput`, `ActiveSpeakerPolicy`, `CSSDesignToken`, `GenericStatusModel`, `BandFillColorAccessorInput`, `AppCommitment`, `FetchMock`, `SectionProps`, `UserGroupList`, `ExpandPanelAction`, `ResponseStatus`, `UpdatePhotoDto`, `IContentSearchResponse`, `JudgeClientEntity`, `RestModelEntry`, `ViewElement`, `MathViewProps`, `AgentConfigOptions`, `ITextModel`, `Preflight`, `RouteRecognizer`, `StynRule`, `StrokeCountMap`, `PageTitleService`, `EntryType`, `CursorConnectionType`, `GetMemberCommandInput`, `ListModelsCommandInput`, `MigrationStates`, `RouterSpec`, `InitializeMiddleware`, `TSerDeOptions`, `XmlBlobsCommandInput`, `LgQuery`, `dStage_stageDt_c`, `ErrorReporterConstructorContract`, `SaplingNativePlugin`, `Handshake`, `FabricEnvironmentRegistry`, `tags.Table`, `Cohort`, `TemplateManifest`, `IRecordedDB`, `ThemeSettings`, `DeleteAppInstanceAdminCommandInput`, `DMMF.SchemaArg`, `HomeOpenSearchDashboardsServices`, `ComponentMeta`, `TokenPair`, `ReferenceDirection`, `MatchedMiddleware`, `requests.ListDbHomePatchesRequest`, `ITreeNode`, `SVGSVGElement`, `ChartActionContext`, `PolicyDocument`, `PadModel`, `DisplayValueSpec`, `requests.ListVmClusterUpdateHistoryEntriesRequest`, `StoreGroupLike`, `preference.Set`, `MarvinImage`, `NgAddOptions`, `ReadableByteStreamController`, `DevtoolsInspectorProps`, `DevtoolsBackend`, `TriggerId`, `Tab`, `d.ModeStyles`, `RelativeBandsPadding`, `AdapterFindOptions`, `requests.ListAutonomousExadataInfrastructuresRequest`, `MDCTabDimensions`, `AnalyzedStyle`, `KeyStrokeOptions`, `ShowOptions`, `d.OutputTargetCopy`, `ThyScrollService`, `ISearchEventDataTemplate`, `AppContextService`, `TagResourceCommandInput`, `AnnotationLayer`, `WidgetRegistry`, `ShareContextMenuPanelItem`, `LetAst`, `Studio.App`, `ExclamationToken`, `LibrarySeriesSeasonEpisode`, `EthereumLedger`, `Box2`, `ViewerParameters`, `DefinitionParams`, `CollisionGroup`, `TagsBase`, `EC2`, `ItemList`, `DoorLockCCConfigurationReport`, `TRuleResolver`, `ThyFullscreenRef`, `TranslationDictionary`, `TagListMessage`, `FilterFn`, `ModItem`, `IResultSetUpdate`, `FileChange`, `Assert`, `MethodMaterial`, `DBClient`, `Iterate`, `DeviceManagerClient`, `IncrementalNode`, `MoveOptions`, `ListPackagesRequest`, `Auditor`, `GraphQLRequestContextWillSendResponse`, `FullPageScreenshotDataOptions`, `AppLogger`, `TracerConfig`, `TextBuffer`, `AsBodilessImage`, `AppComponent`, `SharedValue`, `ResourceLines`, `Boss`, `TypeSystemPropertyName`, `ConnectionOptions`, `TestAwsKmsMrkAwareSymmetricKeyring`, `UrlLoader`, `IMrepoDigestConfigFile`, `React.DetailedHTMLProps`, `moneyMarket.overseer.CollateralsResponse`, `EntityMetaData`, `Applicative`, `LazyResult`, `PropertyDeclaration`, `TaggedNumericData`, `Sheets`, `IContainerContext`, `ServiceConfigs`, `IDestination`, `FileBuffer`, `ListDomainDeliverabilityCampaignsCommandInput`, `DispatchFunc`, `parse5.Element`, `ExpressionServiceParams`, `FounderConfig`, `ICompanionElement`, `SpotifyApi.CurrentUsersProfileResponse`, `BaseFee`, `StitchesProps`, `RetryPolicy`, `Classification`, `SessionPort`, `DescribeDBClusterEndpointsCommandInput`, `Alert`, `Pojo`, `VersionRange`, `InternalRequestParams`, `ClientRequestResult`, `ErrorRes`, `DropTargetOptions`, `Complex`, `ServeD`, `ContractDecoratorKind`, `OnUpdate`, `common.Keybinding`, `Department`, `FieldResolver`, `OsdServer`, `ContentService`, `ExtendedCanvasRenderingContext2D`, `S2CellType`, `ZoneInfo`, `IKeyboardDefinitionAuthorType`, `NewsItemModel`, `FileChunkIteratorOptions`, `GitCommitLine`, `AssetID`, `tabBrowser`, `TronSignedTransaction`, `DayStressModel`, `BMDObjectRenderer`, `NodeSubType`, `RpcMessage`, `DevcenterService`, `FeatureOptions`, `ResponseIssue`, `WebElementPromise`, `EChartsType`, `EpochTracker`, `ContentControl`, `Battle`, `ModifyDBClusterParameterGroupCommandInput`, `TitleVisibility`, `UserIdentity`, `ts.TaggedTemplateExpression`, `AvailabilityDomain`, `H5GroveEntityResponse`, `EthereumTransactionOptions`, `jasmine.CustomMatcher`, `DeepMapResult`, `Create`, `DaffCompositeProductItemOption`, `... 12 more ...`, `NSAttributedString`, `RemoteVideoStreamState`, `UpdateApplicationCommandInput`, `CompositeReport`, `SnippetsMap`, `CreateContextOptions`, `CodeGenFieldConnection`, `IAzExtOutputChannel`, `BarGeometry`, `requests.ListExportsRequest`, `kbnTestServer.TestElasticsearchUtils`, `EventType.onInit`, `ChainTransaction`, `SeparableConvParams`, `MatchProps`, `ModelsTreeNodeType`, `SubscriberRepository`, `TMouseEventOnButton`, `Socket`, `NonTerminal`, `Storage`, `FocusTrapInertStrategy`, `d.E2EProcessEnv`, `AnyQuery`, `PropertyContext`, `IUnlisten`, `Key3`, `OneIncomingExpectationRepository`, `CollectMultiNamespaceReferencesParams`, `MemberService`, `DownloadStreamControls`, `GitlabAuthResponse`, `DescribeConfigurationRevisionCommandInput`, `IDimensions`, `GraphicsItem`, `Times`, `ServiceOptions`, `Value2D`, `UI5Class`, `HTMLAttributes`, `INormalAction`, `CommonTokenStream`, `Http3QPackDecoder`, `MimeBuffer`, `ShaderityObject`, `JSXAnalysis`, `CompletionsCollector`, `UpdateGroupCommandInput`, `PitchShifter`, `NzModalService`, `BlockDisk`, `NavigationGuard`, `NodeData`, `TargetTypeMetadata`, `FileCommitDetails`, `PlotLineOptions`, `ElementFlags`, `BuildArtifacts`, `aws.s3.Bucket`, `InternalStack`, `OnTabReselectedListener`, `FsWriteResults`, `FilterCategory`, `TextEditorElement`, `TaskInfoExtended`, `ODataPropertyResource`, `EmissionMaterial`, `Platform`, `SingleObjectWritableStream`, `BoundingRect`, `ActorAnimKeeperInfo`, `OAuth2Service`, `T.ID`, `HTMLTemplateElement`, `WidgetView.IInitializeParameters`, `ModeRegistration`, `StatementContext`, `ArticleItem`, `FrameRateData`, `filterSymbols`, `PropertyAccessExpression`, `SCNNode`, `NgModuleTransitiveScopes`, `RpcResponseAndContext`, `RetryConfig`, `LikeNotification`, `CacheListener`, `BearerTokenResponse`, `OrderedId64Iterable`, `SetValueOptions`, `UpdateGlobalSettingsCommandInput`, `Motion`, `EnumTypeDefinitionNode`, `QueryState`, `IEventStoreData`, `ManifestInfo`, `INodeDef`, `TradeResponse`, `IndyWallet`, `MsgType`, `TemplateValidatorOptions`, `SubStmt`, `SavedObjectDashboard`, `MiscellaneousField`, `IArrivalTimeByTransfers`, `PageInfo`, `PadchatRpcRequest`, `TypeSystemEntity`, `ActionImpl`, `FrameTree`, `Shading`, `solG2`, `requests.ListVaultsRequest`, `requests.ListNatGatewaysRequest`, `T18`, `IGherkinDocument`, `CmdletParameters`, `ExitStatus`, `CodeExecutionEmitter`, `DeliveryOptions`, `SelectionModel.ClearMode`, `FileSystem`, `IStaticMeshComponentState`, `EditState`, `LogicalElement`, `com.google.firebase.firestore.Query`, `ReadFn`, `FullNote`, `PointerDragEvent`, `MoonbeamCall`, `DescribeIndexCommandInput`, `StatusChartStatusMesh`, `Resort`, `ApolloQueryResult`, `LineChartProps`, `UnitValue`, `QuerySubState`, `LoggingOptions`, `ITelemetryData`, `DaffCartLoading`, `ServerConfiguration`, `CompilerEventBuildStart`, `GX.KonstColorSel`, `PropagationResults`, `UseStylesProps`, `SuperExpression`, `ServerAccessKeyRepository`, `CreateDBParameterGroupCommandInput`, `SharedContentInfo`, `LeafletMouseEvent`, `Cluster`, `ViewPortItem`, `NodeCryptoCreateCipher`, `requests.UpdateJobRequest`, `RLANAnimation`, `WorkItemQuery`, `NavigateToPath`, `PouchDatabase`, `GenericResource`, `EndOfLine`, `LeafletContextInterface`, `FirebaseFirestore.DocumentReference`, `Mp4BoxTree`, `RequestParams`, `Preprocessors`, `ViewerOptions`, `TypeSelectionProps`, `NgScrollbarBase`, `CssAstVisitor`, `BluetoothRemoteGATTServer`, `OrgType`, `IDynamicStyleProperty`, `HdTronPaymentsConfig`, `CmsEntryPermission`, `HsLayerFlatNode`, `ItemsList`, `IntNumber`, `InterpolationType`, `ParsedConfig`, `ItemUUID`, `EasyPzCallbackData`, `LogicalCpuController`, `VertexAttribute`, `WorkspaceState`, `JsonlDB`, `OutputsType`, `EnumValues`, `TileInputs`, `MediaStreamAudioDestinationNode`, `GraphWidget`, `FontWeight`, `TAuthor`, `ListOperations`, `BackblazeB2File`, `WidgetManager`, `UserSubscriptionsInfo`, `ElementOptions`, `ConsoleMessageLocation`, `CompilerSystemWriteFileResults`, `IImposer`, `PyteaOptions`, `DejaTilesComponent`, `DraymanComponent`, `DatabaseItem`, `LayerStyle`, `CallSignatureDeclaration`, `SerializableState`, `ListModelConfig`, `unchanged.Unchangeable`, `IReversibleJsonPatch`, `PathHash`, `Route`, `RegistryVarsEntry`, `SfdxFalconResultRenderOptions`, `NodeCG`, `requests.ListDbHomesRequest`, `TsGenerator.Factory.Type`, `HTMLProps`, `KernelProfile`, `DrawConfig`, `MockedFunctionDeep`, `PlacementProps`, `SymbolAccessibilityResult`, `d.Logger`, `MethodResponse`, `ExceptionHandler`, `ColumnAnimationMap`, `MessageMatcher`, `ExecInspectInfo`, `ThyTreeService`, `EventTypeMap`, `IAsyncParallel`, `ConnectableObservable`, `ProgressTracker`, `SortPayload`, `RTCIceParameters`, `Announcement`, `MiddlewareOverload`, `FixtureSetupDeps`, `GlyphElement`, `UserDetails`, `DynamicGrammarBuilder`, `EventMetadata`, `DepthModes`, `Living`, `WatchOfConfigFile`, `GfxDebugGroup`, `FreezerInstance`, `ParsingMetadata`, `QueueService`, `DocumentType`, `ElementRenderer`, `PinOverrideMode`, `MapObjActorInitInfo`, `DirectiveType`, `SavedObjectsFindResult`, `PropertyKey`, `IRules`, `ComponentMetadata`, `ParameterizedContext`, `RootConnection`, `VisitorContext`, `MuteRoomTrackRequest`, `ItemDataType`, `ModelIndexImpl`, `ChannelResult`, `AsyncTask`, `CookieStorage`, `IUserSession`, `serviceRequests.GetJobRequest`, `ObservableDbRef`, `RtkQueryMonitorState`, `XPathData`, `DateBatch`, `PutSessionCommandInput`, `ControllerAction`, `DateProfileGenerator`, `ActionFunction1`, `requests.ListContainerDatabasePatchesRequest`, `DeleteExperimentCommandInput`, `GroupIdentifier`, `DAGDegrees`, `DryRunPackagePolicy`, `d.JsonDocsComponent`, `PropertyToValues`, `DropDownElement`, `OutStream`, `DragRefInternal`, `DealRecordsConfig`, `ResultTreeNode`, `ReakitTabInitialState`, `MaxHeap`, `SQLQuery`, `AccountGameCenter_VarsEntry`, `SendPayload`, `UpdateIntegrationCommandInput`, `ViewCompiler`, `RelocateNodeData`, `DecorationRenderOptions`, `GetCertificateResponse`, `SfdxTask`, `NormalizedEntrypointItem`, `RecurringBillId`, `FileMap`, `GeocoderQueryType`, `SerializationContext`, `IViewModel`, `CountryCode`, `Mongoose`, `NavNodeInfoResource`, `BaseShape`, `Cocoen`, `ElevationRangeSource`, `IPortfolio`, `StringTypeMapping`, `ConditionGroup`, `CustomSprite`, `PxtNode`, `StageCrewMember`, `ListExportsRequest`, `Permission`, `NoteName`, `AlertClusterStatsNode`, `XMLHttpRequest`, `TrackEventType`, `ProblemEntity`, `RestManagerRequestData`, `BackwardIterator`, `AddSourceIdentifierToSubscriptionCommandInput`, `ScrollToOptions`, `AsyncStorageHandler`, `EmitOptions`, `ControlFlowGraph`, `RectL`, `DocFn`, `Float32Array`, `WarpPod`, `FileReader`, `PluginManifest`, `HasLocation`, `SceneExport`, `CrossTypeHost`, `BlockbookBitcoin`, `BlockClass`, `ClassificationResult`, `IndexNode`, `Atom.Range`, `IndexPatternPrivateState`, `INamedVector`, `DetailListService`, `BasePathCoverage`, `InstallationsFile`, `MailSettings`, `IAuthUserWithPermissions`, `ISearchState`, `RenderNode`, `Iso`, `FiltersCreationContext`, `UpdateDomainCommandInput`, `AttributeToken`, `AuthStatus`, `MenuBuilder`, `StepperState`, `NetNode`, `Sky`, `IFilterInfo`, `Modal`, `SelectContainerProps`, `HsvaColor`, `PluginStreamActionPayload`, `ParsedInterface`, `NineZoneStagePanelsManager`, `AESKey`, `RegistrationType`, `IPrimitiveExpression`, `GPUTextureView`, `MemoizedSelectorWithProps`, `TreeNodeWithOverlappingSubTreeRoots`, `TStoreName`, `DeleteApplicationCommandOutput`, `CharUnion`, `ToastActions`, `TEffects`, `NavigationEnd`, `FragmentableArray`, `RRule`, `FileTransfer`, `XmlRecording`, `LicenseType`, `messages.Source`, `GameObjectGroup`, `DaffCategory`, `UInt32Value`, `WebviewEvent`, `WidgetOpenerOptions`, `ReceiverEstimatedMaxBitrate`, `DataPin`, `React.KeyboardEventHandler`, `WorkerPool`, `ApolloCache`, `MockProviders`, `JsonSchemaRegisterContext`, `GroupData`, `GraphExecutor`, `StateType`, `android.view.LayoutInflater`, `BoxPlotPoint`, `UIPageViewControllerImpl`, `BitcoinSignedTransaction`, `SetOptions`, `EmitOutput`, `DefinedSmartContract`, `UrlObject`, `UploadState`, `KayentaCredential`, `JobMetadata`, `Fig.Generator`, `DatepickerDialog`, `IStandardEvent`, `Turmoil`, `IStatisticSum`, `DukBreakPoint`, `DotenvLoadEnvResult`, `SessionResponse`, `IStructuredSearch`, `IOrchestrationFunctionContext`, `ParserAstContext`, `ProposalMessage`, `Upgrades`, `SignupRequest`, `ScanMetadata`, `NotificationList`, `STPAPIClient`, `vscode.SymbolKind`, `El`, `PlayerList`, `RegistryPackage`, `BlockchainContext`, `BotFilterFunction`, `PresentationPreviewAttribute`, `Separated`, `LoanMasterNodeRegTestContainer`, `CurrentUserType`, `SystemVerilogContainerInfo`, `IImageFile`, `FluentDOM`, `eventHandler`, `FoundationElementRegistry`, `ObjectAssertion`, `SceneObjectBehavior`, `EvaluatedStyle`, `RateType`, `IAudio`, `RBTree`, `ts.PropertyAssignment`, `HoverInput`, `PointString3d`, `InvalidatorSubscription`, `CurveLocationDetailArrayPair`, `PDFContext`, `MDCChipSetAdapter`, `RectangleConstruction`, `ICSVInConfig`, `IEmployeeUpdateInput`, `NotificationTemplateRepository`, `QueryCacheKey`, `PaymentRequest`, `Conic`, `HttpServiceBuilderWithMetas`, `KeyFunc`, `FluentRuleCustomizer`, `Channels`, `ButtonToggleComponent`, `KeyframeAnimationInfo`, `messages.PickleTable`, `IGetActivitiesInput`, `SQLiteTableDefinition`, `IModelIdArg`, `PathProxy`, `LayerDescriptor`, `StatementListNode`, `SpecQuery`, `AccountRegistry`, `PropertyDescriptorMap`, `RouteRecordNormalized`, `SubscriptListResult`, `DndService`, `ClubEvent`, `MutationListener`, `PathInfo`, `Json.StringValue`, `NameInfoType`, `I18nEntries`, `WalletSigner`, `BigNumber.Value`, `CircularDependency`, `ConnectionCredentials`, `RouteParams`, `ServerCertificateRequest`, `RequireContext`, `StringTableEntry`, `Distributes11`, `NativeContractStorageContext`, `RailsDefinitionInformation`, `GeneratorCore`, `ILinkedListItem`, `ReflectionKind`, `RolePermission`, `RedBlackTreeStructure`, `UILabel`, `PropertyEditorProps`, `VpnServerConfiguration`, `Pools`, `RnM2Node`, `Parse`, `HTMLScWebglBaseChartElement`, `YColumnsMeta`, `DeclarationFlags`, `TabLayoutNode`, `OpenCVConfig`, `AbsoluteSizeSchema`, `BotTimer`, `Now`, `DateInputFormat`, `ExternalServiceIncidentResponse`, `E1`, `Limits`, `TSDocConfiguration`, `ConstructSignatureDeclaration`, `TypeFormatFlags`, `CacheProvider`, `ScrollData`, `GridsterItem`, `UserCourseModel`, `PointList`, `Conv3DInfo`, `ElementAccessExpression`, `MeshColliderShape`, `OrderDTO`, `ClockMock`, `DaffRouteWithDataPath`, `IBookmark`, `LoadedEnv`, `KnotVector`, `ParaType`, `AnnotationChart`, `DebugLogger`, `LabeledScales`, `DecompileResult`, `PostfixUnaryExpression`, `SavedQueryMeta`, `UnauthorizedErrorInfo`, `HdTronPayments`, `ODataConfiguration`, `Snippet`, `IContextProvider`, `TimeInstant`, `NestedPayloadType`, `RTCRtpTransceiver`, `PipelineProject`, `requests.ListManagementAgentInstallKeysRequest`, `V1RoleBinding`, `TargetResourceType`, `GetSemesterTimetable`, `IComparer`, `RollupResult`, `Positions`, `SagaMiddleware`, `Hookable`, `AttributeService`, `SetOptional`, `Id64Array`, `ProfileServiceAPI`, `SetStateCommitmentJSON`, `InviteMemberCommand`, `Common`, `LocalFluidDataStoreContext`, `WalletContext`, `WriteResult`, `Lineup`, `KeyringPair`, `ValidationConfig`, `TaskName`, `TextWriter`, `StepResultAfterExpectedKey`, `CdkDialogContainer`, `ImportSteamFriendsRequest`, `AliasedFeature`, `AutorestArgs`, `IAppVersion`, `ReactiveController`, `TNSImageAssetSaveFormat`, `GXRenderHelperGfx`, `SearchMode`, `OutputAsset`, `Apply2`, `d.ComponentCompilerMeta`, `GroupDocument`, `WorkingDirectoryFileChange`, `CommandClasses.Basic`, `StoreProvider`, `DeploymentCenterData`, `BitcoinNetworkConfig`, `Peer.DataConnection`, `AccidentalMark`, `ProviderResource`, `GetLoggingConfigurationCommandInput`, `AuthResourceUrlBuilder`, `DeltaChangeContext`, `LinkRenderContext`, `FunctionRunner`, `MapEventsManagerService`, `RequestTypes`, `Archives`, `IStepDefinition`, `RangeSelector`, `WorkspaceResourceName`, `SettingsPriority`, `EntityWithEquipment`, `ArrayLiteralExpression`, `AstMetadataApiWithTargetsResolver`, `GetTraceSummariesCommandInput`, `ComplexBinaryKernelImpl`, `IReferenceLayer`, `CorrelationsParams`, `SponsoredAuthorization`, `IndicatorNode`, `IINode`, `ApiDefForm`, `EntityQuery`, `IKeyState`, `OperatorLogPoint`, `GfxrRenderTargetDescription`, `ICreateChildImplContext`, `RequestQueryParamsType`, `Appender`, `ParsedElement`, `TVSeason`, `ValidatePurchaseGoogleRequest`, `ISeinNodeExtension`, `LogDescription`, `Types.ObjectId`, `MsgCreateBid`, `WebRequestMethod`, `LoadableComponent`, `Toc`, `AuthenticateOptions`, `AttachVolumeCommandInput`, `MockDocumentFragment`, `RoxieService`, `EntityCollection`, `Evidence`, `double`, `ProposalTransactionJSON`, `Fontkit`, `CacheRecord`, `LensMultiTable`, `StandardFontEmbedder`, `VisibilityFilters`, `SuiSelectOption`, `ExiftoolProcess`, `IEntity`, `NestView`, `SourceDescriptionItem`, `SendResponseParams`, `CONFIG`, `IGroupDataArray`, `Quad`, `Dependencies`, `SMTIf`, `CombinedVueInstance`, `t.ObjectExpression`, `TSPropertySignature`, `PluginFunctions`, `PrimitiveTypeKind`, `BankAccountService`, `requests.ListVcnsRequest`, `CanvasPinRow`, `StableVer`, `RunService`, `N7`, `RemoteVideoStream`, `ObservableParticle`, `Quantifier`, `React.MouseEvent`, `RequestQueryBuilder`, `RuleViolation`, `ReadonlyESMap`, `AnalysisDataModel`, `CosmosDBManagementClient`, `ChainManifest`, `WatchDog`, `ParticipantsAddedListener`, `StructureLink`, `KeyframesMap`, `SourceTypes`, `TaskFolder`, `BoundElementPropertyAst`, `ContextTransformInfo`, `NpmPublishClient`, `SymbolDataVisibility`, `CurrencyId`, `GitConfig`, `TransactionEventBroadcaster`, `ExtendedChannel`, `FormOptions`, `MutableMatrix44`, `RCloneFile`, `Turn`, `PlatformContext`, `TestContextCustom`, `ITaskWorker`, `MethodNext`, `IParamSignature`, `TSVideoTrack`, `PutRecordCommandInput`, `EnumDescriptorProto_EnumReservedRange`, `Commander`, `BigNumberish`, `ZonedMarker`, `SubnetDescription`, `AccessorCreators`, `VennDiagramProps`, `Travis`, `IRootScopeService`, `WalletName`, `Dialogic.DefaultDialogicOptions`, `TechniqueDescriptor`, `ResourceSettings`, `dGlobals`, `WritableStreamDefaultController`, `ForwardedRef`, `TBase`, `ScreenName`, `ApiParameter`, `NotificationMessage`, `IMouseEventTrigger`, `ErrorExpressionCategory`, `QueryParserListener`, `IProvisionContext`, `CustomMaterial`, `ScraperOptions`, `IIndexPattern`, `MovimientoModel`, `GX.TexGenSrc`, `DefinitionNode`, `AnalyzerNodeInfo`, `ThisParameterType`, `DaffCategoryFilterRangeNumeric`, `VRMBlendShapeGroup`, `RNNCell`, `FieldFormatsSetup`, `SocialTokens`, `PatternClassArgumentNode`, `LaunchConfiguration`, `messages.Envelope`, `LinterMessage`, `UserQuery`, `IModelReflectionData`, `MacroAction`, `HappeningsInfo`, `WorkRequestClient`, `vscode.ExtensionContext`, `EntityManager`, `TokenProps`, `WordMap`, `vscode.Terminal`, `ScopedKeybinding`, `INodeUi`, `StoryMenuItemProps`, `MailerService`, `Helper`, `EventSubscriptionCallback`, `OperatorUser`, `BottomNavigationTab`, `SurveyLogicType`, `request.SuperTest`, `RootParser`, `IConfigService`, `FabricEvent`, `ModelConfig`, `Payment`, `StellarRawTransaction`, `OpenYoloCredentialHintOptions`, `Utilities.EventWrapperObject`, `QueryValue`, `StructName`, `SuiteWithMetadata`, `MergeCSSProperties`, `LinkedContracts`, `ListenerHandler`, `ElementArrayFinder`, `NamespaceMember`, `ParsedParameters`, `PrimitivePropertyValueRenderer`, `TelegramBot`, `IMdcCheckboxElement`, `PropertiesMap`, `CreateEmailTemplateCommandInput`, `AnimationRange`, `IRuleApiModel`, `ISegment`, `SpecPage`, `InjectorService`, `Script3D`, `InitializeResult`, `Roots`, `XUploadNode`, `Result`, `ClientKeyExchange`, `DeleteAppInstanceCommandInput`, `VaultActivity`, `PathNodeItem`, `KeplrSignOptions`, `ScaleType`, `Module1`, `NumberWidget`, `DMMF.Field`, `RequestBodyMatcher`, `SOClient`, `keyComb`, `GraphQLOutputType`, `Models.CommandInput`, `ModuleBuilder`, `SlashArgRecord`, `UpdateGroup`, `NavigationStart`, `DatastoreType`, `StripeShippingMethods`, `ESLint`, `HeatmapData`, `CommentEntity`, `SelectMenuProps`, `RTCDataChannelEvent`, `TimestampsToReturn`, `ParsedResponseHeaders`, `EntitySystem`, `RecordingStream`, `IpRangeKey`, `DOMParser`, `LastError`, `DynamicDialogRef`, `CircleDatumAlternative`, `NodeBank`, `NamedCurveAlgorithms`, `GetCustomVerificationEmailTemplateCommandInput`, `XmlElement`, `ImageMetadata`, `NextRouter`, `BScrollConstructor`, `_STColumn`, `MatchmakerMatched_MatchmakerUser`, `IFaction`, `theia.Uri`, `SchemaRootKind`, `DChoice`, `DocumentMapper`, `RangeProps`, `PropertyRecord`, `ReturnStatement`, `CallAst`, `EncodedPart`, `LayerNormalizationLayerArgs`, `DeclarationParams`, `System_Array`, `WatchCompilerHostOfFilesAndCompilerOptions`, `KmsClientSupplier`, `ClaimedMilestone`, `ASTWithSource`, `OutputTargetDocsCustom`, `Scenario`, `SavedObjectsClientContract`, `KuduClient`, `Shape.Base`, `TagMapping`, `displayCtrl.IShowConfig`, `ProductTranslation`, `CaseStatuses`, `ConstraintSet`, `ServiceDecorator`, `UpdateReplicationConfigurationTemplateCommandInput`, `OrganizationProp`, `s.Node`, `SlackHook`, `AttributeModel`, `ForceGraphNode`, `RowItem`, `IFilm`, `Embedding`, `GreenhouseJobBoardJobNode`, `TextLayoutParameters`, `IGlTFExtension`, `ClickParam`, `ExpressionType`, `AddressState`, `Scheduled`, `KEYS`, `requests.ListAvailabilityHistoriesRequest`, `AsyncStorage`, `t.TETemplate`, `Web3Wrapper`, `ActionForRender`, `AdminIdentity`, `AnimeFields`, `TimeoutID`, `ConfigurableProfilePermissions`, `SagaIterator`, `HEvent`, `AbstractType`, `TE`, `UTXO`, `ConfigModel`, `BlobContainer`, `SendOptions`, `TSESLint.RuleContext`, `LighthouseBudget`, `PromiseConstructor`, `Wrapped`, `FuncVersion`, `TransformerProps`, `ServerSocket`, `TimefilterService`, `QuestionToken`, `IKactusState`, `StacksMessage`, `DisconnectReason`, `EditorPosition`, `AggregatePriceRepository`, `Literal`, `SFieldDescribe`, `Plane`, `JSONSchema7Definition`, `WritableOptions`, `FormErrors`, `PP`, `IGLTFExporterExtensionV2`, `SpreadStorableMap`, `DatabaseSubType`, `__HttpHandlerOptions`, `MethodDefinition`, `EditablePolygon`, `TriumphNode`, `ethers.BytesLike`, `ISPListItem`, `ControllableLabel`, `GetMeshSourceOptions`, `PoiBuffer`, `DistributeArgs`, `UnknownObject`, `IServerConfigModel`, `SearchResultProps`, `RoleManager`, `NgxTranslations`, `ParameterPath`, `ObjectRenderer`, `EventSubscription`, `UINavigationItem`, `VercelResponse`, `CloneRepositoryTab`, `juggler.DataSource`, `WexBimShapeMultiInstance`, `GradConfig`, `TriggerEngine`, `ModelCallbackMethod`, `VNodeLocation`, `ExpressionFunction`, `SomeCV`, `Heatmap`, `UninterpretedOption`, `UserMusicResult`, `DropdownMenuProps`, `MDCTextFieldLineRippleAdapter`, `SentryUser`, `QueryMode`, `Reminders`, `FieldName`, `StockItem`, `HydratedFlag`, `CallOverrides`, `RenameMap`, `ICustomClassUIMethod`, `Command`, `Path6`, `SessionWorkspace`, `AlphaConfig`, `HistoryLog`, `PlaceTradeDisplayParams`, `DataEventEmitter.EventDetail`, `ConvertedDocumentFilePath`, `GlobalTime`, `InjectionMap`, `CustomFont`, `DkrLevel`, `ListAccountsCommandInput`, `ToggleButton`, `IGroupSharingOptions`, `Vault`, `HelpCenterService`, `To`, `DeletePipelineCommandInput`, `CourseTask`, `Calibration`, `d.CompilerJsDoc`, `ZoneOptions`, `IQueryParameters`, `SetMap`, `IOperand`, `TimerState`, `AgentPubKeyB64`, `DAL.KEYMAP_KEY_DOWN_POS`, `Wall`, `SignalingClientEvent`, `requests.ListWorkRequestsRequest`, `TleParseResult`, `ParseTreePatternMatcher`, `requests.ListNetworkSourcesRequest`, `ClusterResource`, `peerconnection.Data`, `Content`, `messages.PickleTag`, `Emitter`, `ListRoutesCommandInput`, `AccessControl`, `ITransportConstructor`, `FolderRequest`, `Detail`, `d.PackageJsonData`, `FlowAssignment`, `TableItemState`, `ExpressRouteGateway`, `ObjectCriteriaNode`, `RBNode`, `TRK1`, `Nodes.DocumentNode`, `TileTestData`, `d.HydrateFactoryOptions`, `PolyIntEdge`, `SourceMapConsumer`, `EquipmentInfo`, `ComputedEnum`, `ExpNumIndex`, `LockHandle`, `UserStoreProperty`, `AndroidConfig.Resources.ResourceXML`, `Order3Bezier`, `ParamValue`, `ExpressionVariable`, `Funding`, `Bindings`, `HTMLTableDataCellElement`, `YAMLParser`, `DynamicFormControlModel`, `GetProjectResponse`, `ListElement`, `SelectionRange`, `StatusResult`, `IOSNotificationAttachment`, `Chai.ChaiUtils`, `BaseSession`, `DescribeReplicationTasksCommandInput`, `BadgeInfo`, `ProtocolEventMessage`, `RealtimeVolumeIndicator`, `BlockHeaderWithReceivedAt`, `Gem`, `ProgramObjects`, `QueryBucket`, `EntryInfo`, `Gain`, `IComment`, `requests.ListRemotePeeringConnectionsRequest`, `NgModuleProviderDef`, `TextMessage`, `IImageData`, `WebContainer`, `GithubBranch`, `Consumer`, `MyType`, `WordArray`, `ForgotPasswordRepository`, `Timefilter`, `SliderEditorParams`, `StationService`, `Disembargo`, `JsonSchemaOptions`, `MetricsSourceData`, `ServerSession`, `PoliticalAgendasData`, `PathFunction`, `HistoricalDataItem`, `AuxBotVisualizer`, `Authentication`, `ObservableQueryProposal`, `FileDescriptor`, `EntryTypes`, `LogPanelLayout`, `DebugProtocol.InitializeResponse`, `ts.PropertyDeclaration`, `OptionsSync`, `Bullet`, `Cypress.ConfigOptions`, `DeploymentSubmission`, `MutableGridCategory`, `ISnapshotTree`, `RenderValue`, `WitnessScopeModel`, `MutationOptions`, `ViewTemplate`, `CachedMetadata`, `StarterOption`, `MembersState`, `ModuleResolutionHost`, `TaskActionsEvaluator`, `ServiceExtension`, `StatisticAverageBlockTime`, `Toaster`, `SeriesItemsIndexesRange`, `ContextValues`, `CreateWebhookCommandInput`, `SegSpan`, `ImportWithGenerics`, `SharedServiceProvider`, `SelectorsMatch`, `BodyContent`, `Nat`, `AccessorFn`, `GfxRenderTargetP_GL`, `RpcMessageBuilder`, `RandGamma`, `UpdateJobDetails`, `LoggerLevelAware`, `XCascadeNode`, `ErrorDetails`, `ApiType`, `Tsoa.Type`, `ApplicationSettingsService`, `TimeInterval`, `SourceNotFoundFault`, `JoinedEntityType`, `EditorSettings`, `DirEntry`, `HomePluginSetupDependencies`, `ResolveStore`, `CombinationConstraint`, `OnClickData`, `OutputEndpointData`, `PluginData`, `IpcMessage`, `TevStage`, `DataField`, `GlobalEvent`, `DBConnectionConfig`, `HTMLSelectElement`, `Web3EventService`, `RelayRequestAny`, `IEnvironment`, `VoiceProfile`, `DogeBalanceMonitorConfig`, `GeneratorNode`, `ReadModelPool`, `NSType`, `PluginClass`, `Reportable`, `GradientPoint`, `IServiceContainer`, `ThrowStatement`, `Hex`, `ActionsType`, `Register16`, `ISearchQuery`, `StateRef`, `MatSortHeaderIntl`, `ReactionHandleOptions`, `ListDatabasesCommandInput`, `BackgroundReplacementOptions`, `TimeoutJobOptions`, `ScopeHook`, `DescribeApplicationsCommandInput`, `ChartPoint`, `theia.Range`, `SymbolInformation`, `WheelmapFeature`, `NativeSystemService`, `DecryptParameters`, `TimeGridViewWrapper`, `MultiSegmentArena`, `DataGridColumn`, `WithdrawByoipCidrCommandInput`, `BlockchainSettings`, `AutoTranslateResult`, `HTMLSpanElement`, `GetCertificateAuthorityCsrCommandInput`, `MockCSSStyleDeclaration`, `CreateDatasetCommand`, `ComposableFunctionArgs`, `UniqueNameResolver`, `CeloTx`, `Deposit`, `ElasticsearchModifiedSource`, `OMapper`, `APIOrder`, `ProfileProvider`, `PublicMilestone`, `Combined`, `ConditionInfo`, `NodeDict`, `ListLoggingConfigurationsCommandInput`, `Upload`, `UserModel`, `FileBoxInterface`, `QueryExpressionContext`, `MessageKeys`, `DocSection`, `AbstractRegion`, `d.StyleDoc`, `SpriteRenderer`, `paneType`, `TemplateToTemplateResult`, `IGenericField`, `AcceptInviteCommand`, `BaseProps`, `AnyModel`, `ShadowRoot`, `TImportError`, `AllocationDoc`, `ShelfFieldDef`, `SecurityGroupRuleLocation`, `SystemUnderTest`, `DiscoverFieldDetailsProps`, `BlockBlobURL`, `IToastAttrs`, `ts.System`, `RepositorySummary`, `LocalDatabase`, `IDocumentService`, `SmsCookie`, `ChannelUser`, `protos.common.SignaturePolicyEnvelope`, `StageData`, `TEX1_Sampler`, `WebDependency`, `CryptoEffectFrom`, `ControlsService`, `RoleService`, `SourceTarget`, `ContentApiService`, `IApi`, `GetMessagesFormatterFn`, `MatchmakerMatched_MatchmakerUser_NumericPropertiesEntry`, `NavigationRoute`, `DoubleMap`, `BeneficiaryUpdateParams`, `IMobileTarget`, `OrigamiControlValueAccessor`, `MeshInstance`, `ZipFileOptions`, `TContainerNode`, `StakingData`, `UserName`, `CalendarHeatmapDataSummary`, `IPerson`, `IFluidHandle`, `WebpackDevServer`, `HttpResponseInternalServerError`, `CodeFile`, `ModMetaData`, `PairsType`, `FeatureSetup`, `LoggerLevel`, `WebBinding`, `ILoggerOptions`, `UISize`, `PointRef`, `PDFOptionList`, `ThumbnailSize`, `ContextParameters`, `IBlockchainQuickPickItem`, `Bangumi`, `BlobItem`, `ServerRequestModel`, `DescribeDatasetRequest`, `IAutocompletionState`, `ClusterSettingsReasonResponse`, `TPT1`, `SerializedTypeNode`, `NamedCurveKeyPair`, `py.ScopeDef`, `ExtendableEvent`, `ApplicationConfig`, `AnalyticUnitId`, `RangeSelector.RangeObject`, `RemoteNode`, `ITests`, `DashboardId`, `MarkdownString`, `ParsedAcceptHeader`, `SettingsProperty`, `ResolvedDependencies`, `CallErrorTarget`, `PLSQLSymbolKind`, `DefaultOptions`, `Shader_t`, `Events.preframe`, `Sequelize`, `Scene`, `ResolvedRoute`, `BeanObserver`, `BackwardRef`, `FilamentSpool`, `IMatrix33`, `WriteableStream`, `EntityRemote`, `ComponentSingleStyleConfig`, `UsersServiceTest`, `OpenOrCloseListener`, `UpdateModelDetails`, `EventPluginContext`, `DataStream`, `INumberColumn`, `EntryModule`, `PrereleaseToken`, `AdaptFuncT`, `FreeStyle`, `TmpfileOptions`, `TestDtoFilter`, `CipherWithIds`, `ControllerEvent`, `SuiModal`, `KVStore`, `AttachmentRequest`, `IGetTimeLogReportInput`, `EventAggregatorService`, `types.UMLClassMember`, `MapMesh`, `Cookie`, `ITree`, `CollisionParts`, `GroupLocalStorage`, `ApplicationCommandData`, `ConsoleService`, `GoogleTagManagerService`, `EntityComponent`, `DIALOG`, `DropdownState`, `SNSNoAuthorizationFault`, `ContactLightweight`, `TodoStore`, `PopoverInitialState`, `PouchdbDocument`, `UniqueSection`, `d.OptimizeJsResult`, `CompletionEntryData`, `ValidationComposite`, `IFindQuery`, `PaginationComponentOptions`, `WalletInfo`, `FileEditActions`, `ScopedDeployment`, `AccessRule`, `PortalManager`, `ListRoomsRequest`, `MessageRecord`, `TransportStream`, `BackgroundColor`, `EthereumSignatory`, `IAgreementConnector`, `ResTable`, `FortaConfig`, `MockWindow`, `OperationGroup`, `NormalItalic`, `AddressService`, `ListDatasetsRequest`, `TilemapData`, `TransactionService`, `OrganizationEmploymentType`, `Getters`, `MalSeq`, `TFile`, `StreamerConfig`, `BattleModel`, `Endianness`, `Armature`, `UpdateArgs`, `RationalArg`, `CharacteristicSetCallback`, `UserProfileFactory`, `OptionInfo`, `FormData`, `Animatable`, `UIColor`, `AnimatorSet`, `StatFilter`, `Codec`, `UpdateResponderRecipeResponderRule`, `JavaScriptRenderer`, `ManagementAgentPluginAggregation`, `GetFreeBalanceStateResult`, `BuildVideosListQueryOptions`, `BindingElement`, `RegionInfoProviderOptions`, `EditableTextBase`, `PageInfoListItem`, `AnnotationsOptions`, `DeviceConfigIndex`, `CategoryService`, `RO`, `DailyApiResponse`, `NodeJS.EventEmitter`, `CompletionStatus`, `Stretch`, `OverpassElement`, `Association`, `SimpleChartDataType`, `DaffCategoryFilterEqualOptionFactory`, `JSON`, `RouteHandlerMethod`, `ListDeviceEventsCommandInput`, `PageLayout`, `FunctionLikeDeclaration`, `CommandPath`, `SQS.Message`, `React.ReactInstance`, `Constructable`, `WifiConfigureRequest`, `ChannelProperties`, `SvelteDocument`, `SecurityHub`, `PredicateWithIndex`, `JsonComposite`, `ListDomainsForPackageCommandInput`, `types.IDynamicOptions`, `BlockCompiler`, `ArgError`, `STPPaymentMethod`, `GoGovReduxState`, `MetricTypeValues`, `ButtonInteraction`, `IPartialLocaleValues`, `BreadcrumbsOptions`, `TabLocation`, `SurveyConfig`, `RequestMethods`, `EngineArgs.DiagnoseMigrationHistoryInput`, `MSITokenResponse`, `ShaderOptions`, `LanguageServiceContainer`, `GetDeploymentResponse`, `Criterion`, `LoggerWithErrors`, `StringArray`, `CreateSchemaCustomizationArgs`, `IPlaylist`, `ParserException`, `DataRequestDescriptor`, `BreadcrumbsNavProps`, `PuppetASTContainerContext`, `MapFunc`, `DefaultVideoStreamIdSet`, `SbbNotificationToastRef`, `ApiMetadata`, `requests.ListIamWorkRequestErrorsRequest`, `HeatmapTable`, `InputData`, `TargetResponderRecipeResponderRule`, `B.JsNode`, `DateRangeKey`, `GeolocationPositionError`, `TaskList`, `EventResponse`, `ARDimensions2D`, `HeaderType`, `ListPageSettings`, `ExpNumNumel`, `IResourceExpression`, `UserInfoInterface`, `IActionsProps`, `WebSocketService`, `MachineConfig`, `RandomNumberGenerator`, `Loadbalancer`, `DesignerLibrary`, `FetchFinishedAction`, `FormatDefinition`, `PluginsAtomType`, `PiPostAction`, `NgModuleDef`, `ConfigContent`, `TemporaryStorage`, `Developer`, `ABI`, `IconifyJSON`, `EventConfig`, `Agent`, `DescribeProjectCommandInput`, `undefined`, `CodeSource`, `RouteChain`, `CreateProcedureOptions`, `UniOption`, `SP`, `BrowserHeaders`, `StagePanelsManagerProps`, `TrackCallInfo`, `ScopeTreeRow`, `AnyEventObject`, `RestService`, `ContextLogger`, `Web3ClientInterface`, `ActionCreatorWithPreparedPayload`, `CompiledSchemasArray`, `JsonDecoratorOptions`, `RRES`, `ts.InterfaceDeclaration`, `RxTerms`, `DescribeJobRunCommandInput`, `SessionIdentifier`, `IGetDeviceResult`, `TargetDefinition`, `LineData`, `OperatorSummary`, `DomController`, `UserCredentialsRepository`, `FaunaString`, `ChainEventSubscriberInterface`, `LegacyOperation`, `FormulaBuilder`, `CombinedItemPriceInfo`, `vscode.StatusBarItem`, `StatedBeanMetaStorage`, `EmojiCategory`, `XYZValuesObject`, `ArrayShape`, `URIComponents`, `VirtualNetworkGatewayConnection`, `IMarkmapFlexTreeItem`, `CodeFixContextBase`, `IYamlItem`, `SMTType`, `IApiCallback`, `Blockly.Block`, `CallbackStore`, `TestErc20`, `AppConfig`, `MinimalFS`, `vscode.Position`, `TestSuiteResult`, `HKTFrom`, `ScrollService`, `ScaleConfig`, `AssetParts`, `IPoContent`, `TooltipController`, `AbstractRule`, `RequestFunction`, `OAuthUser`, `ExtendedIColony`, `IDBRequest`, `OnPreResponseResult`, `Task`, `ts.Declaration`, `InternalStacksContext`, `MaxAnalysisTime`, `esbuild.OnLoadResult`, `AutoAcceptCredential`, `Schematic`, `RequestHandlerContextProvider`, `BalmScripts`, `MessageReader`, `viewEngine_NgModuleRef`, `MatchmakerAdd_StringPropertiesEntry`, `OpDef`, `BindingSetting`, `Hobby`, `SRT0`, `LineShape`, `HTMLTableSectionElement`, `RSASigningParams`, `TypedAxiosRequestConfig`, `MagickSettings`, `t_a25a17de`, `RpcKernel`, `MxObject`, `KeybindingItem`, `DatasourceStates`, `AWS.S3`, `MetadataStorage`, `Chars`, `AllowsNull`, `XMLCharState`, `ColorMode`, `DaffCategoryPageMetadataFactory`, `SwaggerOperation`, `ListObjectsV2Output`, `DefaultDeSerializers`, `CombinedScanResults`, `NameObjRequestArchivesFunc`, `NumberBase`, `IFilterValue`, `IStoreOffer`, `ProviderCallback`, `httpm.HttpClientResponse`, `UseRequestConfig`, `Film`, `HeaderItemProps`, `SkillMap`, `MetadataValue`, `UiGridColumnDirective`, `ThisType`, `ComponentSlotStylesPrepared`, `Express.Request`, `LocalReference`, `RushConfigurationProject`, `ListModelsResponse`, `ShareTransferStorePointer`, `MotorcycleDomSource`, `AngularFireStorageReference`, `Piscina`, `MemoryFileSystem`, `SourceRange`, `SwapTransition`, `ISuperdesk`, `Island`, `SetupCommitment`, `MoneyBase`, `ImportNode`, `AudioFormat`, `PollingPerformanceObserverTaskQueue`, `ISearchLocation`, `QMParam`, `IAnyModelType`, `RuntimeService`, `MetaDataRequest`, `enet.INetEventHandler`, `PointCandidate`, `AudioClip`, `IGlobOptions`, `C_Point`, `types.ScrollData`, `ofAp`, `WizardContext`, `PreviewComponentProps`, `AaiOperationTraitDefinition`, `CompilerSystemRemoveDirectoryResults`, `FilterQueryBuilder`, `TimeSpec`, `MatDateFormats`, `ProcessConfigurationOptions`, `IntBuffer`, `EventToken`, `IHttpConfig`, `DebugProtocol.EvaluateResponse`, `AbstractKeymapData`, `SyncedDataObject`, `CATransform3D`, `TPlayItem`, `ProtoCtx`, `RankingEntry`, `BoxSide`, `AdapterConfig`, `UtilsService`, `DiagnosticSeveritySetting`, `Transform`, `JSDocTag`, `NzResizeObserver`, `DbStxEvent`, `InputMethod`, `SeedReference`, `ILoadBalancer`, `CellArgs`, `RectScrollFixed`, `IDeviceInformation`, `MonacoFile`, `ResolvedReflectiveProvider`, `BufferSize`, `KCDHandle`, `MasterDataObject`, `ResourceSummary`, `IORouter`, `RawTestResult`, `EThree`, `ParseOptions`, `JSCodeshift`, `SyncDoc`, `BlockComponent`, `UnpackNestedValue`, `React.SFC`, `Authorization`, `InputDefinitionBlock`, `SDKConfiguration`, `DeployedReplica`, `PatternPreset`, `FibaroVenetianBlindCCReport`, `GRUCellLayerArgs`, `Grammar`, `ForcedRetryErrorInfo`, `Konva.Layer`, `NodeWithChildren`, `PreProcessedFileInfo`, `AnimationReferenceMetadata`, `MessageFormat`, `RustLog`, `AnnotationsProvider`, `MediaMarshaller`, `CardTypes`, `MemoryWriteStream`, `ResponseTiming`, `ESTree.AssignmentExpression`, `IBpmnModeler`, `Atoms`, `DeployStackResult`, `ts.ParenthesizedExpression`, `PackageDetail`, `ConcreteClass`, `LongestNudgedSegment`, `IMechanicsQuery`, `DiscordEmbed`, `ILabelConfig`, `CloudFunction`, `IRequestApprovalFindInput`, `HoverParams`, `ResultFilter`, `_TypedArrayConstructor`, `FfprobeData`, `IQueryListRendererProps`, `AccuracyEnum`, `ResolvedModule`, `Shake`, `FieldExpr`, `_https.RequestOptions`, `RedisInterface`, `PbEditorElementPluginArgs`, `requests.ListIdentityProviderGroupsRequest`, `PropertySet`, `CreatePhotosDto`, `TNoteData`, `GetAppCommandInput`, `IOperationType`, `requests.ListConsoleHistoriesRequest`, `AssignStatementContext`, `Quat`, `React.Key`, `StarknetWindowObject`, `PrecalculatedBot`, `ResourceGroupXML`, `ViewerContext`, `TOCMenuEntry`, `IStateDB`, `Interpolator`, `ExperimentDocument`, `BlobURL`, `NavResponse`, `CivilTCR`, `ISWATracker`, `SxParserConfig`, `JsState`, `ReadonlyColor`, `TypeGraph`, `HookData`, `LevelLogger`, `HighlightResult`, `ResponsePath`, `ListWorkRequestLogsResponse`, `FrontendApplication`, `Conflicts`, `PayloadActionCreator`, `ReplicationState`, `UIContextProps`, `BotCalculationContext`, `DisplayAccessKey`, `StackPanel`, `ParseError`, `MockERC20`, `CtxAndConfigRepository`, `TokenStream`, `SequentialTaskQueue`, `CardPile`, `ITimer`, `ArrOf`, `shareComicFace`, `ProvidersInfoService`, `requests.GetVolumeBackupPolicyAssetAssignmentRequest`, `dataType`, `DirectiveResult`, `IMidwayFramework`, `thrift.IThriftField`, `FuseNavigationService`, `DocumentId`, `ParentBid`, `PuppetASTObject`, `AnnotationDomainType`, `SelectStep`, `IG6GraphEvent`, `PrimitiveTarget`, `CertificateFilter`, `ApplyPendingMaintenanceActionMessage`, `ToastPackage`, `SecurityScheme`, `AugmentedDiagnostic`, `ProtocolParameters`, `MsgCreateDeployment`, `RpcPeer`, `DaffCategoryFilterRequestEqualFactory`, `AssociationType`, `Diagnostics`, `BaseWatch`, `lsp.Hover`, `NLClassifierOptions`, `FindRelationOptions`, `IHeftJestDataFileJson`, `PublicKey`, `IAdminUser`, `Deploy`, `FontType`, `BinarySet`, `FeaturedSessionsState`, `Bitrise`, `BedrockServiceConfig`, `RestObject`, `DateSegments`, `AAA`, `IconifyIcon`, `mongoose.Error`, `WritableAtom`, `ConfigParams`, `MessageBus`, `EventTracker`, `SearchResultItem`, `ColumnInstance`, `UpdateEndpointCommandInput`, `Reporter`, `DejaPopupAction`, `VisualizationToolbarProps`, `ClientRequest`, `IPredictableSupportCode`, `IntelliJ`, `momentNs.Moment`, `RootThunkResult`, `Finished`, `MediaObject`, `PiUnitDescription`, `Ignore`, `TaskRunner`, `TaskExplorerDefinition`, `IHomeViewState`, `NzMentionComponent`, `bank`, `Dataset`, `MenuIDs`, `android.content.res.Resources`, `SetSettingEntry`, `Polymorphic`, `ODataPagedResult`, `DOMUtils`, `TreeServiceTest`, `CssImportData`, `FIRQuery`, `IStackFrame`, `StandardSkillBuilder`, `ConfigStruct`, `TNode`, `RedirectRequest`, `OPCUAClientOptions`, `TProto`, `GasPriceOracle`, `Boundary`, `IDataContext`, `BaseRequestOptions`, `GetByKeyRequestBuilder`, `CustomInputArgs`, `DraggableStateSnapshot`, `DescribeEventCategoriesMessage`, `DependencyGraph`, `SocketState`, `ChangePasswordInput`, `MXAnimatedIconData`, `DynamoDB`, `Lifecycle`, `HsCoreService`, `MessageOptions`, `TypedAction`, `FormTypes`, `ChangeOptions`, `CombatantTypes`, `PartialAsyncObserver`, `STPPaymentContext`, `SlaveTimelineState`, `iAst`, `MalMap`, `HsLayoutService`, `PriceSpecGroup`, `V1Servicemonitor`, `MockMAL`, `PluginConfigItem`, `SyncType`, `ControllerUIProp`, `CallableFunction`, `TreeChild`, `OctokitResponse`, `FabricNode`, `CircleCollider`, `AxisPositions`, `SettingsSpec`, `ReadonlyAtom`, `DescribeTableCommandInput`, `MimeContent`, `TemplateRoot`, `MonoTypeOperatorFunction`, `Wallet`, `Cast`, `CryptoEffects`, `RequestExt`, `OnBoardConfig`, `ACP.SuggestionsRequestedEvent`, `RegistryItem`, `ReactiveDBException`, `ServiceLocator`, `Extractor`, `IXLSXExtractOptions`, `TeardownLogic`, `MsgHandler`, `IHistoryRecord`, `RuleConfig`, `NodeService`, `PlanValidationOutcome`, `HTMLInputOptions`, `ApiTypes.Feed.Hide`, `SectionMarker`, `ContactDto`, `GeometryValue`, `ReflectionCapabilities`, `ImageScanner`, `MdcTab`, `LinkedAttachment`, `WatchCompilerHostOfConfigFile`, `FM.DllFuncs`, `BaseMsg`, `Disembargo_Context`, `IPropertyComponentProps`, `Keyed`, `IListRecipient`, `WorkspaceSeed`, `IColours`, `BatchDeleteImageCommandInput`, `painless_parserListener`, `BackgroundFilterVideoFrameProcessorObserver`, `GroupLevel`, `ListJobTemplatesCommandInput`, `NimAppState`, `OutliningSpan`, `ActionStepType`, `UiSettingsCommon`, `HTTP`, `IProxyContext`, `SiteVariablesPrepared`, `KafkaSettings`, `AbstractSqlPlatform`, `React.StatelessComponent`, `MessengerClient`, `ISharedContent`, `SpaceBonus.PLANT`, `HandlerStep`, `BiquadFilterNode`, `SavedComments`, `FacsimileStorage`, `Artefact`, `PlaceholderEmbeddableFactory`, `SourceFileStructure`, `NewE2EPageOptions`, `CreatureType`, `SeparableConvLayerArgs`, `AssetTotal`, `TaskFunctionCallback`, `DescribeRecipeCommandInput`, `UnstakeValidatorV1`, `ColliderComponent`, `Highcharts.VMLRenderer`, `UIEvents`, `BaseTable`, `RenderedChunk`, `Dic`, `CanActivate`, `ModuleID`, `XYCoord`, `Constraint2DSW`, `ObjectAny`, `IBounds`, `WaitForOptions`, `Designer`, `ScrollDirection`, `TBigNumber`, `requests.ListTagDefaultsRequest`, `MssPackage`, `AssignmentExpression`, `CompactdState`, `CallState`, `IActionSet`, `BigNumberValue`, `NodeScene`, `UiActionsStart`, `HttpBatchLinkHandler`, `IChildNode`, `unchanged.WithHandler`, `PointOptions`, `ExternalModuleReference`, `ApmConfiguration`, `ValueGetterFunction`, `FormatDiagnosticsHost`, `GpuState`, `SharedMap`, `Iteratee`, `ICustomizations`, `VideoComponent`, `fabric.Image`, `StyleFunctionProps`, `DidKey`, `StripePaymentIntent`, `GfxRenderPipelineP_WebGPU`, `LabExecutionService`, `ClientService`, `ContractJSON`, `RequestSuccessCallbackResult`, `AcceptInvitationCommandInput`, `CISource`, `requests.ListWafRequestsRequest`, `ConfirmHandlerCallback`, `ImagePickerResult`, `CustomOptions`, `MatTooltipDefaultOptions`, `SPHttpClient`, `CollectionDefinition`, `NamedNode`, `MutationInput`, `Params`, `AppointmentUnwrappedGroup`, `UninstallMessage`, `TemplateItem`, `GameSagaContextPlayers`, `LanguagePackage`, `NovaResources`, `FirstColumnPadCalculator`, `HTTPHeaders`, `MappingBuilder`, `CircuitDesigner`, `GuildBasedChannel`, `RectGrid`, `InstancedBufferAttribute`, `BasicTypeDefinition`, `DSColumnType`, `SpectatorDirective`, `MIRConceptType`, `MovimientosService`, `RollupSourceMap`, `IPod`, `ParsedRequestParams`, `AssemblyBlockContext`, `ListDevicesCommandInput`, `SpendingCondition`, `IDBObjectStore`, `d.RollupAssetResult`, `NodeIndex`, `RegExpOne`, `ScryptedInterfaceProperty`, `PendingTestFunction`, `NodeFilter`, `AppVersion`, `IFramework`, `IBApi`, `ODataVersion`, `TerminalVersion`, `BaseEntity`, `ParseFn`, `ApiSection`, `IPage`, `IPolygonGeometry`, `IKeyResultUpdate`, `SubState`, `WriteLeaderboardRecordRequest_LeaderboardRecordWrite`, `TelemetryNotificationsConstructor`, `UniqueSelectionDispatcher`, `SweepContour`, `IExtractedCode`, `ResponderExecutionModes`, `TupleAssignmentNode`, `EffectHandler`, `ir.Expr`, `MDCMenuSurfaceFoundation`, `IOObject`, `PubSub`, `AbortIncompleteMultipartUpload`, `HdStellarPaymentsConfig`, `ManyToManyOptions`, `RequestSchema`, `OncoprintWebGLCellView`, `request.Options`, `ConditionType`, `FunctionPlotDatum`, `BatchItem`, `ServicePropertiesModel`, `Amount`, `NextApiRequest`, `SerializeCxt`, `EdmxActionImport`, `DefaultClient`, `esbuild.Metafile`, `IFlowItem`, `React.WheelEvent`, `AnyColumn`, `HopeElement`, `SitePropsIndex`, `IWorkerMessage`, `VElement`, `ManyToOneOptions`, `ApplicationCollection`, `StylingFunction`, `SecurityIdentity`, `StringSymbolWriter`, `core.PathDescription`, `NLUOptions`, `RowViewModelFactory`, `AutoTranslateGoogleService`, `DateEntry`, `IPage.IRequest`, `LF`, `TriggerInternal`, `LiveActor`, `DeploymentTargetsOperationIO`, `FlagFixPoints`, `NotesRange`, `MdcElementPropertyObserver`, `ISensorProps`, `IPluginModule`, `Animal`, `NumberSet`, `CratePackage`, `InitialOptionsTsJest`, `FindResult`, `TagValueParser`, `ProcessedFile`, `TransformHelper`, `Proposal`, `StopChannelCommandInput`, `ColorChannelControl`, `ApiItemReference`, `CreateJobCommandOutput`, `NoInputAndNoOutputCommandInput`, `SweepEvent`, `ChildComponent`, `ModuleScope`, `LogCorrelationContext`, `BaseData`, `IListQueryInput`, `FlowNodeTypeResult`, `INodeCredentialsDetails`, `LibraryComponentImpl`, `NgGridRawPosition`, `CharacteristicType`, `messages.PickleStep`, `PatternParams`, `MbLayer`, `DialogButton`, `FetchCache`, `ISimpleAction`, `GetModelsCommandInput`, `FakeHTMLAnchorElement`, `MockPeerCertificate`, `IntSet`, `ToRefs`, `UIImageRenderingMode`, `TextDocumentWillSaveEvent`, `GetMetricDataCommandInput`, `AsyncIterableObservable`, `OAuthProvider`, `FRAME_SVG_POLYLINE`, `PaginatedQueryFetchPolicy`, `ReXer`, `Binding`, `SubscribeParams`, `BehaviorTreeNodeInterface`, `Room`, `MetadataAccessor`, `MapContext`, `AdjacentZones`, `Get`, `ts.NewExpression`, `i18n.IcuPlaceholder`, `ICommandDefinition`, `IKeyboard`, `Checkpoints`, `VerifiedHierarchy`, `EllipseEditOptions`, `tl.VariableInfo`, `AccountInfo`, `PluginResourceSettings`, `GesturesObserver`, `ethers.providers.FallbackProvider`, `ICandidateUpdateInput`, `ApplyAssetContext`, `UiButton`, `AnnotationState`, `NineZoneStagePanelPaneManager`, `CollisionScaleType`, `Graph2`, `SpatialCache`, `ThyDragHandleDirective`, `DataTableEntry`, `Finding`, `JavaDownloadRelease`, `PluginDescriptor`, `CreateResolversArgs`, `Timestamped`, `interfaces.Factory`, `MessagePort`, `MintGenerativeData`, `HydrateCacheOptions`, `PadCalculator`, `ElementType`, `teacher`, `TernarySearchTreeNode`, `Setter`, `OutgoingResponse`, `RunnerOption`, `ChatClientState`, `HTMLUListElement`, `PutRequest`, `WorkerManager`, `IRandom`, `ReadFileFailCallbackResult`, `PrimaryExpression`, `ShareTransferStore`, `BufferComposer`, `RenegotiationIndication`, `WebSiteManagementClient`, `SMTEntityDecl`, `DatatableColumn`, `PassThrough`, `Algebra.RootNode`, `ShipPlugin`, `EventService`, `styleProps`, `ExpressionLoader`, `FrameworkConfiguration`, `DeleteParams`, `FormatTypeFlags`, `TypesModule`, `ICurrency`, `Right`, `SimpleRecordInput`, `IHealthCheckResult`, `ParsedItem`, `ECInstancesNodeKey`, `DeleteConnectionResponse`, `Vector`, `ModuleSpecifier`, `EvaluatedScript`, `SslSupport`, `IonRouterOutlet`, `apid.VideoFileId`, `RGB`, `SnackbarAction`, `EdmxParameter`, `HistogramBucketAggDependencies`, `TextureSourceLoader`, `requests.ListDrgsRequest`, `ILocalValue`, `SetupContext`, `DialogflowMiddleware`, `MatDialog`, `FastifyInstance`, `TypeParameter`, `CanvasSystemIcon`, `BooleanLike`, `UiState`, `Unlisten`, `SVGDOMElement`, `MinMaxNormArgs`, `SecurityContext`, `FormBuilder`, `CommonWalletOptions`, `ICXMakeOffer`, `_PresignUploadRequest`, `IAllExecuteFunctions`, `d.PrerenderHydrateOptions`, `DataConverter.Type`, `p5.Vector`, `CallAdapterState`, `StructFieldInfo`, `InitConfig`, `SharedControlConfig`, `KeyValueCollection`, `ListServicePipelineProvisionedResourcesCommandInput`, `Bid`, `SVInt`, `coreClient.RawResponseCallback`, `DeclarativeCall`, `SFCStyleBlock`, `ISettingAttribute`, `ShapeViewModel`, `CreateMeetingCommandInput`, `Init`, `SupCore.RemoteClient`, `StaticDataView`, `DOMRectList`, `UpgradePolicy`, `DescriptorTypeResult`, `FindProsemirrorNodeResult`, `TreeOption`, `DebugProtocol.DisconnectResponse`, `GraphicOptions`, `IntCodeComputer`, `Vector3d`, `SpriteSheetSpacingDimensions`, `SelectListItem`, `IPermission`, `File`, `DefUse`, `XMLNode`, `TestLegacyLoanToken2`, `DynamicFormControlEvent`, `CompressedPixelFormat`, `TypeBase`, `ThemeBuilder`, `FormActionType`, `test.Test`, `requests.ListDrgAttachmentsRequest`, `IEthUnlock`, `RefreshTokenDto`, `HsvColor`, `Quakeml`, `Bound`, `AccountDoc`, `TranslateService`, `WizardForm`, `ClientUser`, `ReactSource`, `UniformRandom`, `AbiOwnershipTransaction`, `RTCSessionDescriptionInit`, `InterpolationStep`, `NodeResult`, `IParameter`, `JsonRpcPayload`, `Dialogic.State`, `BubleDataType`, `ResourceProps`, `PNG`, `AppHandler`, `ImageTileEnt`, `AudioProcessingEvent`, `SymmetricCryptoKey`, `XPCOM.nsXPCComponents_Classes`, `LitecoinSignedTransaction`, `GitLabFixtureClient`, `IUserWithRoles`, `ISourceNode`, `DefaultContentNode`, `DemoVariable`, `ObjectLiteralElementLike`, `NdArray`, `ValueProvider`, `MainState`, `CannonRigidbody3D`, `SchemaEnum`, `SaleorThemeColors`, `ISpecModel`, `paper.PointText`, `EuiValues`, `UrlType`, `UniqPrimitiveCollection`, `JwtHelperService`, `IFormItemTemplate`, `ContainerWithState`, `Instance_t`, `RheaEventContext`, `Geoset`, `ZoneLocator`, `TransactionContext`, `DsProcessorService`, `CredentialTypesClass`, `IAtomMvhd`, `ListViewCell`, `ScrollStrategy`, `Args`, `RedisCacheAdapterContext`, `DescribeEnvironmentsCommandInput`, `BeanProvider`, `ASTVisitor`, `ArticleEntity`, `ChatMessageWithStatus`, `VersionDataService`, `bigInt.BigInteger`, `SubstrateExtrinsic`, `Mocked`, `IsEqual`, `Signal`, `ICell`, `IFetchParams`, `UriMatchType`, `AdditionalDetailsProps`, `NbDialogRef`, `PosBin`, `NzTreeNode`, `DescribeDBParametersCommandInput`, `DBArg`, `Credential`, `GrantIdentifier`, `d.DevServerContext`, `UnitFormService`, `MUserWithNotificationSetting`, `Mysql`, `ParseConfigFileHost`, `PvsProofCommand`, `UnsubscribeSnapshot`, `DeleteFleetCommandInput`, `requests.ListSteeringPolicyAttachmentsRequest`, `AnimatedAddition`, `AttachmentOptions`, `TransferListOptionBase`, `AlertController`, `StaticJsonRpcProvider`, `EndPoint`, `PaginatedList`, `TaskOptions`, `LibraryItem`, `ThunkResult`, `StringMap`, `SavedMultisigEntry`, `CancelRequest`, `NavigationViews`, `SpaceID`, `FILTERS`, `ResponderDimension`, `ProductCategory`, `ExcaliburGraphicsContext`, `LoadedVertexLayout`, `TransferState`, `GetConfigurationSetCommandInput`, `btVector3`, `OperationInstance`, `NetworkType.Mainnet`, `IAlbum`, `ControlledProp`, `BooleanResponse`, `CSSProps`, `CreateTodoDto`, `FilterExpressionNode`, `GetPrTimelinePayload`, `RPC`, `ArgResult`, `IMenu`, `EntityEffects`, `MessageHandlerContext`, `DaffAddress`, `TickSignal`, `UpdatePipelineCommandInput`, `TSInterfaceDeclaration`, `PythonPreview`, `Conv2DTranspose`, `ILogParseHooks`, `HitCircle`, `USBDevice`, `Hint`, `PrivateApiImpl`, `TimetableSession`, `TeslaStyleSolarPowerCard`, `SRWebSocket`, `sdk.VoiceProfileClient`, `IDocumentSnapshot`, `DataValue`, `ScannedPolymerProperty`, `CreateApplicationCommand`, `EmbeddablePersistableStateService`, `TiledTSXResource`, `TableService`, `KeyInKeyof`, `TableConfig`, `MongoClientConfig`, `SchemaNode`, `PivotQuery`, `ChatCompositeProps`, `IThemedToken`, `ReviewerEntity`, `TaskTypeDictionary`, `IsometricGraphic`, `TestRaster`, `EnvironmentRecord`, `Compute`, `CompilerOptions`, `RobotsByNameMap`, `ProtocolPeerInfo`, `VoilaGridStackWidget`, `ThyDialog`, `HeaderTransformer`, `bigInteger.BigInteger`, `JupyterFrontEnd`, `CalculateBoundsOptions`, `ApplicationCommandRequest`, `WexBimGeometryModel`, `CSR`, `A8`, `PerpV2Fixture`, `DocumentRange`, `common.EventData`, `ITool`, `TestDTO`, `KMSKey`, `OscillationState`, `IColorV`, `TypeVarMap`, `DeltaType`, `NotSkeletonDeep`, `DeleteStudioCommandInput`, `StringAttribute`, `SankeyDiagramDataView`, `VnetInfoResource`, `TriDiagonalSystem`, `DemoBlockType`, `ProxyAccessor`, `DecimalSource`, `RecordModel`, `CommitData`, `BetterMap`, `IThrottlerResponse`, `ManagerConfig`, `DemoExecutor`, `F1TelemetryClient`, `ts.Diagnostic`, `AuthMachineEvents`, `StateAccount`, `GridItemEvent`, `AllDecorators`, `RenderedItem`, `StatusFieldProps`, `TEElement`, `Models.IPositionStats`, `DirectoryTree`, `DaffCartAddress`, `IProducer`, `OperationArgs`, `ForwardDefinition`, `DocumentWrapper`, `Alternatives`, `IPlDocTemplate`, `RouterNavigation`, `HoveredResult`, `SetStateAction`, `ListenDecorator`, `Activation`, `EncryptedMessage`, `CreateChannelParams`, `ColumnConfigArg`, `ISharedObjectRegistry`, `SuperResolutionConfig`, `EfsMetricChange`, `ComponentVariablesPrepared`, `LendingReserve`, `PutFileContent`, `ImportedConfiguration`, `IPNResponse`, `SelectionOptions`, `IRECAPIClient`, `ResourceSpans`, `WriteLeaderboardRecordRequest`, `IFormSectionData`, `SetupFunction`, `TestTree`, `TokenFetchOptionsEx`, `IC`, `NineStar`, `VercelRequest`, `Physics2DDirectBodyStateSW`, `ElasticsearchClient`, `IMetric`, `CdkStepper`, `_OIDCConfiguration`, `authors.Table`, `BrowseDescriptionLike`, `Assignment`, `TestComponentBuilder`, `PlayerInstant`, `RegionType`, `EntitiesState`, `ResourceNotFound`, `HsAddDataOwsService`, `HttpErrorContext`, `AbstractMesh`, `ApplicationSummary`, `MatSidenav`, `DescribeRegionsCommandInput`, `AllTokens`, `Drawer`, `PolicyBuilderPaths`, `VisEventToTrigger`, `VNodeData`, `CallbackList`, `MatSort`, `FlattenedXmlMapCommandInput`, `DiscordMessageActionRow`, `ConditionalTransferCreatedEventData`, `SavedObjectMetaData`, `XUL.chromeDocument`, `DslQuery`, `MonitoringContext`, `HmrContext`, `SimpleUnaryOperation`, `TransactionParams`, `HMAC`, `ChildProcessByStdio`, `ResponseToolkit`, `IChangeTarget`, `CohortRepresentation`, `TypeConditionRestriction`, `ReshapePackedProgram`, `DBCoreTable`, `ILibraryRootState`, `PolicyViolation`, `LightGroupState`, `DaffCartOrderReducerState`, `Authenticate`, `TPluginSettingsProps`, `SingleKey`, `TextRenderParameters`, `TensorLike1D`, `IPed`, `SidePanelProps`, `SubmissionObjectEntry`, `GetArgs`, `TypeErrors`, `TSchema`, `MaxPooling2D`, `LiteralValue`, `AnnotationObject`, `IListenerRuleCondition`, `Events.pointerdragenter`, `XUL.browser`, `EnumValueDescriptorProto`, `Tlistener`, `ModelCtor`, `OperationNotPermittedException`, `ComicDownloaderService`, `AggsItem`, `IRoundState`, `DataRequestContext`, `QueryConstraint`, `TreeView`, `DockerImageName`, `FargateTaskDefinition`, `RenderableProps`, `SpellList`, `AudioMixObserver`, `IFunctionTemplate`, `NodeCache`, `WidgetAdapter`, `AssetState`, `OrderInfo`, `TraceCallback`, `DeleteObjectRequest`, `AttributeFlags`, `DownloadProgress`, `SlsConsoleFile`, `ReplyPackage`, `IMediatorMapper`, `VirtualWAN`, `Evaluation.Response`, `Replacement`, `MbMap`, `CreateAppInstanceUserCommandInput`, `BooleanSchema`, `IntermediateTranslationFormat`, `CLIOptions`, `LegendData`, `DpcMgr`, `IncompleteFormatStringSegment`, `ASTValidationContext`, `AnchorMode`, `SimpleState`, `AutoSuggestData`, `PathEndCoordinates`, `ManagedBackupShortTermRetentionPolicy`, `WebVRSystem`, `EngineResults.SchemaPush`, `BasicPoint`, `PatientService`, `StringInput`, `ForgotPasswordAccountsValidationResult`, `Villain`, `HTMLSuperTabButtonElement`, `UICollectionViewCell`, `InfraConfigYaml`, `FunctionInfo`, `IBrew`, `MyWindow`, `PicassoConfig`, `RouterTask`, `FlexLength`, `EPeopleRegistryState`, `Clickable`, `GetBranchCommandInput`, `DecimalPipe`, `SetIpAddressTypeCommandInput`, `ResourceDataGridWrapper`, `FunctionTemplate`, `IMatrix44`, `TransactionError`, `Docfy`, `sdk.BotFrameworkConfig`, `UpdateRoomCommandInput`, `collectSignaturesParams`, `Favor`, `ReplaySubject`, `InterfaceWithoutReturnValue`, `IStyleCollection`, `HsAddDataLayerDescriptor`, `DynamicFurParam`, `requests.ListVmClusterPatchesRequest`, `IncompleteUnescapedString`, `IPeer`, `SortedSetStructure`, `IHud`, `TreeNodesType`, `requests.ListManagementAgentPluginsRequest`, `GpuStats`, `FabricEventBase`, `CookiecordClient`, `ResultInfo`, `OrgEntityPoliciesPlan`, `DisposableCollection`, `ImageViewerState`, `IParseResult`, `SwaggerPath`, `DescribeAccountLimitsCommandInput`, `AutoRestExtension`, `NotificationEvent`, `ProviderProps`, `B0`, `TransformKey`, `WithElement`, `TEventType`, `ContractsService`, `Q.IPromise`, `ISO8601Date`, `MActorSignature`, `QueryObject`, `VPosition`, `SubstrateNetworkParams`, `Breakpoints`, `PathTransformer`, `ValidateArgTypeParams`, `BufferFormatter`, `CryptoFunctionService`, `MeasureStyle`, `vscode.WebviewView`, `RuleDescription`, `KeyEvent`, `DropInfo`, `VertexData`, `cdk.Construct`, `GfxRenderPipeline`, `AnimationCurveKeyframe`, `VirtualCell`, `socketIO.Server`, `EventProperties`, `A11ySettings`, `requests.ListCatalogPrivateEndpointsRequest`, `RenderPassId`, `IImportedArmy`, `Replacer`, `LayerId`, `UITextField`, `FormatErrorMetadata`, `PathfindingGraph`, `SQLError`, `S1Sale`, `ITimezoneOption`, `SavedReport`, `Node`, `JwtVerifier`, `ToastyService`, `YearToDateProgressPresetModel`, `IndexPatternField`, `AxisStyle`, `ethers.ContractTransaction`, `DashboardContainerFactory`, `IDateRangeActivityFilter`, `ResultPath`, `TriggerProps`, `ThLeftExpr`, `LengthPrefixedList`, `DragManager`, `LocationState`, `ServerSideEncryptionConfiguration`, `AnalysisEnvironment`, `ShadowTarget`, `ParticleSystem`, `ComposibleValidatable`, `GrowableBuffer`, `SinglelineTextLayout`, `CategoryCollectionStub`, `ResourceAction`, `displayCtrl.IInitConfig`, `MembersActions`, `React.Dispatch`, `DocumentSnapshot`, `DeploymentType`, `ProjectServer`, `Setup`, `TimedParagraphItem`, `AccountMeta`, `ast.ClassDeclaration`, `SessionAuthService`, `Symmetry`, `CVDocument`, `TypographyOptions`, `ContextCarrier`, `SecurityCCCommandEncapsulation`, `LayerProperties`, `CbExecutionContext`, `Id64String`, `Mod`, `Remarkable`, `DaffAccountRegistrationFactory`, `Decoder`, `TaskLibAnswers`, `FieldAccessor`, `GetOwnPropertyDescriptors`, `SurveyLogicItem`, `FileWatcherEventKind`, `SemVer`, `InjectionValues`, `INavFourProp`, `Original`, `BadgeSampleProps`, `PluginInitializer`, `InterpreterOptions`, `PiInterface`, `NavigableMap`, `ObstaclePort`, `WriteItem`, `NodeContext`, `TiledLayer`, `Grid3D`, `requests.ListListingsRequest`, `TrackList`, `ScaffoldType`, `ITagUi`, `TypeFacts`, `LoginEntity`, `UpdateArticle`, `ParsedCode`, `DescribeDataSourceCommandInput`, `sst.App`, `RelativePath`, `SerializedPrimaryKeyOptions`, `ClusterProvider`, `UISettingsStorage`, `IndexedMap`, `Resolver`, `ForwardingStatus`, `fpc__ProcessName`, `msRest.OperationQueryParameter`, `ng.IHttpProvider`, `OverflowT`, `PageBoundingBox`, `PostModel`, `TEasingFn`, `AnalyzerLSPConverter`, `DBCore`, `JavaMethod`, `VisualizeTopNavProps`, `IAccessInfo`, `MappingFactor`, `EndOfLineState`, `GatsbyConfig`, `ListDevicesRequest`, `PrivateProps`, `ICommandParsed`, `MarkerClustererOptions`, `SelectAmount`, `ChatConverseState`, `StringStream`, `Repl`, `ActionByType`, `ProtocolMessage`, `InputField`, `GfxBufferUsage`, `TweetResolvable`, `Bin`, `Mjolnir`, `NodePath`, `GrainPlayer`, `ColorService`, `NgOption`, `tr.commands.Command`, `CustomEndpointDetails`, `SecureCookieOptions`, `BarChartBarMesh`, `VectorSource`, `WorkingDirectoryInfo`, `ExampleRecord`, `ControlFormItemSpec`, `AlgPartDecoration`, `Fields`, `TestImageProps`, `DeviceFormPostData`, `CSharpNamespace`, `ApplicationTypes`, `EmailConfirmation`, `LoadDataParams`, `RequestAction`, `VirgilCrypto`, `ImportLookup`, `Attributes`, `HydrateComponent`, `PromiseSettledResult`, `PartitionLayout`, `EmbeddableFactoryProvider`, `ICnChar`, `IMinemeldConfigService`, `SyntaxCheck`, `FileSystemError`, `StringContent`, `Piece`, `HypermergeNodeKey`, `IDriverType`, `MDCSelectFoundation`, `GitAPI`, `AuthenticationStrategy`, `egret.TouchEvent`, `Utilities`, `TemplatePositionContext`, `MDCTextFieldLabelAdapter`, `StitchesComponentWithAutoCompleteForJSXElements`, `Hermes`, `CidConfig`, `IEventListener`, `UITabBarItem`, `SafeHTMLElement`, `ExternalData`, `Ptr`, `JitsiRemoteTrack`, `GameModel`, `RadixAtomObservation`, `MDCShadowLayer`, `ObserverActionType`, `NotifyOptions`, `GfxRenderHelper`, `ParsedUrl`, `NonNullExpression`, `messages.PickleStepArgument`, `VariableTable`, `TestStepResult`, `RelationInfo`, `UniversalCookies.Options`, `Addressable`, `SocketCustom`, `ColorRef`, `KeyframeNodeList`, `ShaderData`, `LCDClient`, `PartyPromote`, `LoggerConfigType`, `EasJsonReader`, `NameValuePair`, `FileSet`, `AssemblerQueryService`, `ApiMockRoute`, `RadioButtonComponent`, `NodeItem`, `GroupProblemData`, `ElementContainer`, `IParser`, `MovieDAO`, `VersionInfo`, `BackendContext`, `Stack.Props`, `TokenData`, `ApiEditorUser`, `CircuitMetadataBuilder`, `LSTMState`, `KeyRowEvent`, `changeCallback`, `MathBackendCPU`, `Voice`, `ParsedCommand`, `SetAccessorDeclaration`, `CLI_COMMAND_GROUP`, `NormalizedOutputOptions`, `OverviewSourceRow`, `PluginBuilderLens`, `CommandRole`, `XhrFactory`, `PresetMiniOptions`, `ElementInlineStyle`, `Merger`, `DAL.DEVICE_ID_RADIO_DATA_READY`, `SecuredSubFeature`, `DeleteEmailIdentityCommandInput`, `RawBuilder`, `VueFilePayload`, `cheerio.Cheerio`, `BindingContext`, `RenderableStylesheet`, `NodeMap`, `ShareArgs`, `SearchInterceptorDeps`, `ProperLayeredGraph`, `NodeTag`, `Coder`, `LocationItem`, `ListWorkflowsCommandInput`, `RollupCommonJSOptions`, `RepoError`, `DiagnosticChangedEventListner`, `PresSlide`, `LodashDecorator`, `CreateStudioCommandInput`, `PreviouslyResolved`, `TimeType`, `ChromeExtensionService`, `WindowComponent`, `LocationService`, `_THREE.Vector3`, `DatabaseSchemaImpl`, `WeightsManifestGroupConfig`, `SearchSourceOptions`, `AppServiceRegistration`, `APIGatewayEvent`, `LineProps`, `StoredTx`, `ExecFileException`, `HunspellFactory`, `CancelJobRequest`, `pxt.PackageConfig`, `SeparationInfo`, `TimeRangeBounds`, `StoreBase`, `RevalidateEvent`, `TrackEvent`, `ConcatInputs`, `d.Diagnostic`, `sst.StackProps`, `MappedField`, `PredicatePlugin`, `RemoteEndpointConfiguration`, `JobConfig`, `IndicesOptions`, `fetch.Response`, `CoreTypes.dip`, `PeopleSearchScroller`, `types.IActionInputs`, `LintMessage`, `HTMLLIElement`, `StudentBasic`, `IUserUpdateInput`, `GenerateFunctionOptions`, `NativeAppStorage`, `Mixin`, `JsxExpression`, `DataViewsService`, `SpringSequenceStep`, `ServiceConfig`, `GXMaterialHacks`, `PluralType`, `ISqlRow`, `NativeEventEmitter`, `Multicall`, `ListPatternType`, `IslandsByPath`, `xyDatum`, `FirebaseMachineLearningError`, `CustomConfigurationProvider1`, `ITextAndBadge`, `FlagValue`, `RecoilValue`, `KvPair`, `MapEntry`, `TaskOperations`, `SchemaFormOptions`, `SchemaDefinition`, `ICAL_ATTENDEE_STATUS`, `GroupPanel`, `TestArgs`, `FluidObjectSymbolProvider`, `NodePoolPlacementConfigDetails`, `FieldDescriptorProto`, `ReadableFilesystem`, `IEmeraldVault`, `ResolverMethodOpts`, `DocumentRef`, `DeviceConfigService`, `IFieldInfo`, `EventQueue`, `XyzaColor`, `RuleAttribute`, `FSMState`, `UpdateApplicationRequest`, `CoinSelectInput`, `ITableOfContents`, `TourStep`, `AlternativesSchema`, `UsageCollectionSetup`, `ClassPartObject`, `TransferEvent`, `BehaviorTreeBuilder`, `RtlScrollAxisType`, `Circle`, `Revision`, `JsonaProperty`, `TooltipAndHighlightedGeoms`, `SessionID`, `IUserIdentity`, `CasCommand`, `OptionElement`, `TraverseOptions`, `AzureWizard`, `EditableHippodrome`, `IValues`, `TransitionSettings`, `MyEpic`, `SubscribeFunction`, `VariablesManager`, `ApplicationSubmission`, `DeleteReportDefinitionCommandInput`, `MtxGroup`, `DataHolder`, `CKB`, `IBinaryTreeNode`, `KeyboardLabelLang`, `BoardService`, `GfxTexFilterMode`, `ReflectedType`, `Streamer`, `BuilderState`, `RpcSocket`, `Wechaty`, `CardRenderer`, `GetDomainRecordsRequest`, `SessionId`, `EntityId`, `ParsedSearchParams`, `CurrentUser`, `cback`, `RolandV8HDConfiguration`, `IRange`, `DataModifier`, `SpringSequence`, `SavedState`, `IIdentifier`, `ScryptedDevice`, `GraphQLRequestEnvelope`, `ExecutionArgs`, `IReq`, `TimeService`, `_TimerCondition`, `CustomEditor`, `ReactTestInstance`, `NoExtraProps`, `DateType`, `ThStmt`, `patch_obj`, `schema.Entity`, `CheckFunc`, `PlanetApplication`, `IParameterValuesSource`, `ForumAction`, `ITriggerPayload`, `FireClient`, `MemoryStream`, `BleepGeneric`, `IEventDispatcher`, `DeleteJobRequest`, `PiEditor`, `LastValueIndexPatternColumn`, `BitcoinCashBalanceMonitorConfig`, `requests.CreateProjectRequest`, `IDockerComposeOptions`, `WastePerDay`, `IProviderOptions`, `NullLogger`, `NpmConfig`, `EventsClientConfiguration`, `Brand`, `IEscalation`, `StatefulDeviceManager`, `SearchFilterState`, `WarriorLoader`, `AppStateStore`, `AccountRefresh_VarsEntry`, `ITicks`, `ESTreeNode`, `LMapper`, `ConfigDefinition`, `RumPublicApi`, `ITimeLogFilters`, `IApolloServerContext`, `TerminalProviderSeverity`, `UseSRTP`, `ApiAction`, `USBInTransferResult`, `StoreState`, `BandViewModel`, `CLI`, `LogAnalyticsSourceExtendedFieldDefinition`, `NormalizedOption`, `NewExpression`, `ConfigBundle`, `FormContextValues`, `MockElectron`, `PortRecord`, `EtcdOptions`, `MacroMap`, `VerifierOptions`, `HexLiteralNode`, `BluetoothError`, `LessParser`, `ConfigSetExecutionGroup`, `PathlessInputOperation`, `CliFlags`, `Tracker`, `EnvironmentAliases`, `RedisTestEntity`, `NugetPackage`, `GroupNode`, `ProgressCb`, `ViewTest`, `JsxAttributeLike`, `MotionValue`, `ToggledFiltersState`, `HTMLTextAreaElement`, `CSSInterpolation`, `ISendingUser`, `MockBackend`, `AST.ArrayAST`, `RTCIceCandidate`, `HierarchyRequestOptions`, `IFileEntry`, `HTMLAudio`, `DefaultEditorSideBarProps`, `AuthSettings`, `TodoListApplication`, `UseStore`, `ExecAsyncResult`, `IFilePane`, `IResultSetValue`, `ServiceConfigDescriptor`, `FiltersBucketAggDependencies`, `NotificationRepository`, `FindTaskQuery`, `ComparisonFunction`, `NetworkEndpointType`, `glTF.glTFNode`, `FacemeshConfig`, `RedisModules`, `UseFilterManagerProps`, `FormatRange`, `FontVersion`, `OutputSelector`, `TestTerminal`, `DeployedWithoutEmailWallet`, `GraphState`, `IDynamicValues`, `IResolvers`, `OutputStream`, `obj`, `INavigationFeature`, `LegendSpec`, `RelayerUnderTest`, `ThemeCreator`, `RecipientAmountCsvParser`, `IThunkAction`, `StatusBarItemsManager`, `RawConfigFile`, `ThemeLoadOptions`, `HEventType`, `CodedError`, `ComponentNode`, `SavedQueryService`, `Harmony`, `IExecutableContext`, `TableOfContents`, `MdDialogConfig`, `DocumentedError`, `DynamicAlternative`, `JPattern`, `StringKeyOf`, `MutationFn`, `DiezTypeMetadata`, `ReadValue`, `UIGestureRecognizer`, `CommandControlMessage`, `GuaribasAnswer`, `StyleMapping`, `SystemRequirement`, `EventDetails`, `UnionAccumulator`, `TypeOrmModuleOptions`, `IInsertInput`, `MiddlewareOptions`, `CardSpace`, `SongBundle`, `SlideElement`, `PropertyMap`, `DiscoverServices`, `IChangedArgs`, `KxxRecordBalance`, `VirtualFileInterface`, `DateRangePickerProps`, `SvgDebugWriter`, `social.InstancePath`, `DayGridWrapper`, `ManagerOptions`, `RemoteArtifact`, `SerializationStructure`, `LayoutRectangle`, `Border`, `GetIntegrationResponseCommandInput`, `GPGPUContext`, `BigDecimal`, `UpdateUserCommand`, `ComputedRef`, `IFormFieldValue`, `PluginStreamAction`, `AbstractViewer`, `DeleteRegexPatternSetCommandInput`, `PushTransactionArgs`, `JobMessage`, `SpaceFilter`, `AsyncPipeline`, `StringLiteralUnion`, `PrefetchIterator`, `QueryError`, `SearchConfigurationService`, `TaskManagerDoc`, `SAXParser`, `BlockNumberUpdater`, `MouseUpEvent`, `AnimatorRef`, `KPuzzle`, `HelmetData`, `ToggleProps`, `SentPacket`, `WebApiConfig`, `oicq.Client`, `CombinedText`, `IAutorestLogger`, `util.StringEncoding`, `logger.Logger`, `transcodeTarget`, `T`, `GithubClient`, `IFileBrowserFactory`, `alt.Vehicle`, `UseMetaStateOptions`, `OptionalIdStorable`, `ModuleJSON`, `IMaterialPbrMetallicRoughness`, `RuleScope`, `OutputBundle`, `ISubsObject`, `SortOptions`, `ProxyController`, `DownloadedBinary`, `IJSONSchema`, `AlignValue`, `OnEventCallback`, `SignKeyPair`, `OutputTargetDistLazyLoader`, `OptionType`, `ISharedMap`, `SCondition`, `IDocumentAttributes`, `pxtc.CompileResult`, `ConditionalTransaction`, `DownloadedFiles`, `TargetGraphQLType`, `IOneClickAppIdentifier`, `ControllerHandlerReturnType`, `EMailProcessingStatus`, `ComponentOpts`, `NgModuleFactory`, `AjvFactory`, `MediaDescription`, `UVSelect`, `PublishData`, `OperationSupportMatrix`, `ServerError`, `IStyledComponent`, `ExperimentSnapshotDocument`, `DiezType`, `ChooseActionStateMachine`, `LED`, `StopJobCommandInput`, `ArgsDescriptions`, `ToolbarTheme`, `ContractCaller`, `NormalizedTxBitcoin`, `GenericParameter`, `ESTree.Node`, `CacheObject`, `CompilerWorkerTask`, `XPlace`, `HandleActionSharedParams`, `JobRun`, `CdkStep`, `PlacementOptions`, `ReviewComment`, `Org`, `ImportPath`, `ReferenceCallback`, `BlockBlobClient`, `CustomPropertySetUsage`, `ResourceTimeGridWrapper`, `DriveManagerContract`, `CatchupToLatestShareResult`, `firebase.User`, `WithIndex`, `CancelTokenSource`, `CategoriaProps`, `NbThemeService`, `ISuite`, `BasicPizzasProvider`, `AuthenticationType`, `FlamelinkFactory`, `NumberSystemType`, `ImageStore`, `LuminanceSource`, `WithNode`, `S3Location`, `RtspSession`, `AttributeValue`, `Teacher`, `IZ64Main`, `FieldQuery`, `ts.TypeReference`, `LimitLine`, `ICamera`, `PubRelease`, `GetInfoResult`, `MockImportRegistry`, `IChannelDB`, `ApiRecord`, `CardListItemType`, `TemplateDeserialized`, `GitPullRequest`, `IGitManager`, `TypeDeclaration`, `NSVElement`, `WebDNNWebGPUContext`, `SankeyDiagramSettings`, `GridItemData`, `UdpTransport`, `TempStats`, `GridOptions`, `LogParser`, `CldFactory`, `VideoStreamRendererViewState`, `RowContext`, `FileLocationQuery`, `GoalSettingsService`, `ParjsResult`, `ITokenRequestOptions`, `CellRange`, `SmallMultipleScales`, `StepResultGenerator`, `WithPromise`, `ts.server.PluginCreateInfo`, `TextBox`, `ProjTreeItem`, `glTF1`, `Checkout`, `NavigationContainer`, `PathExpression`, `ProtoKeyType`, `ConstantsService`, `IQueryFeaturesOptions`, `InitiateAuthResponse`, `TextureSource`, `GX_Material.GXMaterialHacks`, `VisualizeServices`, `model.TypeName`, `DragDropRegistry`, `SortKeyRule`, `PTestNode`, `IKeyCombo`, `ScanResult`, `TranslationItem`, `BinaryOperatorToken`, `TypeIdentifier`, `ECDH`, `uint32`, `StyleBuilder`, `InlineVariable`, `OperationTypeNode`, `PTPDataView`, `SingleValueProps`, `GX.BlendMode`, `MutableImageRef`, `VariantAnnotationSummary`, `CatService`, `StatsNode`, `HALLink`, `BaseSourceMapTransformer`, `UserTie`, `FakePromise`, `LiteralShape`, `RSAPublicKey`, `SendMessageFn`, `ImageUrlTransformationBuilder`, `PromiseRes`, `Applicative4`, `ApplyGlobalFilterActionContext`, `TimefilterConfig`, `IPageProps`, `MessengerTypes.Message`, `UploadResult`, `requests.SearchListingsRequest`, `DoorLockCCConfigurationSet`, `GenericTestContext`, `AppManager`, `GameState`, `ImportMode`, `ViewCommon`, `Crawler`, `LastFmApi`, `pingResponse`, `ISearchStrategy`, `IPositionCapable`, `WirelessMode`, `ResultSet`, `LogConfig`, `SortedArray`, `PluginName`, `JsCodeShift`, `ITaskContainer`, `ObjectContaining`, `SizeConfig`, `BodyDefinition`, `MkDirOptions`, `CycleDimension`, `GetInstanceProfileCommandInput`, `IPluginData`, `DeleteStorageObjectId`, `Occurrence`, `RequestDetailsProps`, `ColorPickerService`, `GraphQLInputFieldMap`, `PointStyleAccessor`, `TypeConstructionContext`, `ITeam`, `TensorWithState`, `Web3Service`, `SubmitHandler`, `io.Socket`, `AreaUI`, `ListEndpointOptions`, `ListMemberAccountsCommandInput`, `IModule`, `Box3`, `CPlusPlusRenderer`, `RawNavigateToItem`, `ShareCallbackFunction`, `CompositeMetric`, `AtomicAssetsContext`, `LabelStyle`, `MultiRingBuffer`, `GetExperimentCommandInput`, `QueryList`, `CreateBucketRequest`, `CustomDomComponent`, `Monad1`, `requests.ListIdentityProvidersRequest`, `WordCache`, `GLTFResource`, `AuditAssertion`, `SongData`, `UserProps`, `UUID`, `RouterLoaderOptions`, `ESTree.MethodDefinition`, `HistoricalEntityData`, `KyselyPlugin`, `CompletionItemData`, `SchemaField`, `EffectDef`, `Array`, `IHDPreviewState`, `FileFlatNode`, `HierarchyDefinition`, `ActionsSdkConversation`, `IAppVolume`, `SoundChannel`, `MockCustomElementRegistry`, `UpdateVolumeCommandInput`, `ModalContextProps`, `RigConfig`, `MyItem`, `ICoordinates3d`, `BindingHelpers`, `CLM.ExtractResponse`, `CommandClassDeserializationOptions`, `Worker`, `DataTransferEvent`, `CubeTexture`, `DeployProxyOptions`, `ErrorMark`, `GeoPath`, `IndexedCollectionInterval`, `DataVariable`, `Truffle.Contract`, `Tasks`, `AccountConfig`, `TimelineTrack`, `Event24Core`, `Renderable`, `GanttUpper`, `SteeringPolicyAnswer`, `API.IMiscInfos`, `ChannelBytes`, `CompletionInfo`, `DownloadedImage`, `GridStackModel`, `CfnExperimentTemplate`, `ValidatorResult`, `InstanceConfiguration`, `TestClassesVariant`, `LanguageClient`, `HOC`, `Tipset`, `GX_VtxDesc`, `ApiTreeItem`, `AlreadyExistsException`, `SSM`, `Offer`, `OptionDetails`, `protocol.FileLocationRequest`, `PubkeyInfo`, `InjectorContext`, `IInspectorRow`, `ImagePipe`, `LineBatch`, `AlertResult`, `InputRule`, `EditorState`, `MiddlewareConsumer`, `JsPsych`, `SandDance.VegaDeckGl.types.VegaBase`, `AuthUtilsService`, `JacksonError`, `GeneratePrivateKey`, `DiagramMaker`, `ConstantAst`, `Angulartics2IBMDigitalAnalytics`, `SystemModule`, `RuleGroup`, `DateFormatterFn`, `MatchPairsOptions`, `UtilityNumberValue`, `WorldObject`, `CreditCard`, `MessagesBag`, `Buff`, `FileOverwriteOptions`, `ScanOptions`, `StringFormat`, `AccessLog`, `ExpoConfig`, `requests.ListDrgRouteTablesRequest`, `X12FunctionalGroup`, `USBEndpoint`, `integer`, `HotkeysEvent`, `Getter`, `TestInstance`, `SafeSignature`, `DefaultEditorControlsProps`, `BuildingState`, `PaginateQuery`, `Mongoose.Model`, `StringLookupMap`, `CssDimValue`, `WindowsLayout`, `ButtonDefinition`, `DoneFn`, `GroupId`, `EngineArgs.SchemaPush`, `CreateTestRendererParams`, `LegacyCompilerContext`, `ServerSyncBufferState`, `AppAPI`, `SnackbarContext`, `Knex.Config`, `EventActionHandlerCallableState`, `ToastButton`, `IEmployeeStatisticsHistoryFindInput`, `GfxMipFilterMode`, `InteractionEvent`, `BeforeInstallPromptEvent`, `IOdataAnnotations`, `PointerType`, `NavLink`, `Export`, `GlobalUserData`, `Octant`, `StandardEvents`, `ValuesStoreParams`, `RequestMatcher`, `RPCClient`, `MotionData`, `DataProxyErrorInfo`, `MessageAction`, `IComponentComposite`, `ReportBuilder`, `HashConstructor`, `GitTag`, `LinkComponent`, `AssertionError`, `IPropertyTypeValueDescriptor`, `IModelAppOptions`, `SortingOption`, `DocumentHighlight`, `GooglePlus`, `ECClass`, `ReadModelMetadata`, `IGetPaymentInput`, `MediaUploadForm`, `ISerialFormat`, `SurfaceLightmapData`, `ArticleProps`, `JobTrigger`, `AbstractValue`, `PixelLineSprite3D`, `TransitionSpec`, `MDL0_NodeEntry`, `PreQuestInstance`, `SceneStore`, `Compartment`, `WithId`, `FactRecord`, `BitBuffer`, `ThroughputSettingsGetResults`, `JsDocAndComment`, `ACLCanType`, `ControllerData`, `IViewPort`, `ActionDefinition`, `PageBlobGetPageRangesResponse`, `ApplicationEventData`, `PrivateApi`, `ReactiveEffectRunner`, `AutoScalingConfigurationSummary`, `BSPBoxActor`, `IEnhancer`, `StackGroupPath`, `ScalarType`, `InputConfig`, `Consultant`, `ContentDimensions`, `Arg0`, `AudioPlayer`, `ConnectionUI`, `UpdateFn`, `BackgroundPageStyles`, `ARUIViewOptions`, `DefaultInspectorAdapters`, `SettingsOptions`, `BindingInfo`, `RollingFileContext`, `ItemSection`, `HttpResponseBase`, `JsonRpcParams`, `ListPicker`, `DynamoDB.BatchGetItemInput`, `FileSystemResolver`, `InvariantContext`, `RemoteResource`, `IKeypair`, `DeviceConfigIndexEntry`, `BottomNavigationItem`, `CommentStateTree`, `BatchResponse`, `CustomLocale`, `GeolocationPosition`, `Pin`, `IRestApiResponse`, `NPCActorItem`, `HierarchyNode`, `FenceContext`, `CanvasView`, `TReturnType`, `ISelectOption`, `ITokenParser`, `FaunaTime`, `FlowTreeTopicNode`, `ReactPDF.Style`, `LiteralReprAll`, `ModelState`, `KeysToCamelCase`, `BoardDoc`, `IntrospectionInputValue`, `TabInstance`, `DispatchByProps`, `WglScene`, `CountService`, `ColorSwitchCCGet`, `IWinstonData`, `Wins.RankState`, `SparseMatrix`, `KeyBindingProps`, `MagitChange`, `ReportingCsvPanelAction`, `ScaledUnit`, `ICommands`, `HsAddDataUrlService`, `d.CollectionManifest`, `AnalyzerEntry`, `TabItemSpec`, `SankeyLink`, `textViewModule.TextView`, `CharacterClass`, `GeometryContainmentRequestProps`, `CanvasEngine`, `VcsAccountDatabase`, `getSubAdapterType`, `WidgetDef`, `IDataFilterInternal`, `BinanceWebsocket`, `ModelPrivate`, `VisConfig`, `BluetoothScale`, `TypeHierarchyItem`, `requests.ListVolumesRequest`, `StoredEncryptedWallet`, `NoteResouce`, `MultipleClassDeclaration`, `ConvCommitMsg`, `BufferContainer`, `ArrayBindingPattern`, `FileFormat`, `ArrayObserver`, `LogAnalyticsLabelDefinition`, `OafService`, `ZoneState`, `IExpressServerOptions`, `BUTTON_SIZE`, `AccessoryTypes`, `ConsumerContext`, `UpdateServiceRequest`, `ColumnSettings`, `ITransformHooks`, `RealtimeChannelInfo`, `ContentTypeProps`, `IDocumentSystemMessage`, `TreemapSeriesData`, `ChangesetProps`, `MaterialInstanceState`, `MarkType`, `SprottyWebview`, `NineZoneState`, `SVGPathElement`, `Curl`, `CostMetric`, `ISequence`, `DispatchPattern`, `Arithmetic`, `AccountBalanceService`, `HistoryStore.Context`, `DeterministicDeploymentInfo`, `ITranslationService`, `FakeUsersRepository`, `AnimeDetailsFields`, `ApmSystem`, `ITextFieldProps`, `Dashboard`, `EdmxFunctionImportV4`, `NormalExp`, `SurveyObjectProperty`, `LintConfig`, `Linker`, `VisualGroup`, `op`, `InputChangeEvent`, `B3`, `InvalidRequestException`, `VideoStreamRendererView`, `GraphFrame`, `SonarrSettings`, `WrappedComponentType`, `RangePartType`, `OpenAPIObject`, `CreateAccountsRequestMessage`, `Arena`, `AwsService`, `DateAdapter`, `App.webRequest.IRequestMemory`, `PortalWorldObject`, `Paragraph`, `SequentialLogMatcher`, `IPagingTableColumn`, `PluginLoader`, `DesignerNode`, `IterableExt`, `GraphQlQuery`, `VarSymbol`, `A1`, `SignerFetchRpc`, `GenerateTypeOptions`, `PoseNetOperatipnParams`, `Camera`, `CardActionConfig`, `IBlocksFeature`, `SupEngine.Actor`, `AsciiOperatipnParams`, `ISetupFunction`, `TabsState`, `DecodedRouteMode`, `PositionObject`, `Yendor.BSPNode`, `d.TypesImportData`, `IHttpClientOptions`, `ProgressOptions`, `SwaggerBaseConfig`, `ObservableInput`, `TestRenderer`, `WorkloadType`, `ExercisePlan`, `TypeEnvironment`, `K7`, `LanguageMode`, `PromiseAndCancel`, `BlockExport`, `ChatClient`, `FetchHeaders`, `MemberName`, `VideoStreamDescription`, `InMemoryCache`, `PolicyDetails`, `ProblemIndication`, `OutputOptions`, `BertNLClassifierOptions`, `IncomingWebhookSendArguments`, `PROTOCOL_STEPS_ID`, `IObserverHandle`, `MagicExtensionError`, `ValueID`, `SliderOpt`, `OpenFileFilter`, `ReportTarget`, `DocumentNode`, `UpdateConnectionResponse`, `TransformedData`, `CurrencyService`, `DebtRegistryEntry`, `RateLimitState`, `AbstractOptions`, `CornerMarker`, `PipeDef`, `UITransform`, `SchedulerPromiseValue`, `EntityTypeProperty`, `CommitOrderCalculator`, `ResizeGripResizeArgs`, `Observable`, `Group.Point`, `IDeploymentTemplate`, `RoundingModeType`, `DataPublicPluginSetup`, `Inventory`, `ILinkedClient`, `MeetingParticipant`, `CircularLinkedListNode`, `PoiTable`, `ILoaderOptionsPipe`, `vec2.VectorArray`, `AnalyticsDispatcher`, `ConfigurationProps`, `MasternodeBlock`, `AggDescriptor`, `TransactionalFileSystem`, `SwiftVirtualNetwork`, `ElementKind`, `BackupData`, `PageComponent`, `KinesisFirehoseDestination`, `DataModel`, `CallResult`, `InputProps`, `TemplateParameters`, `PreferenceChange`, `FunctionFiber`, `vscode.CodeLens`, `ToastData`, `IContractWrapper`, `d.ResolveModuleIdOptions`, `IEcsTargetGroupMapping`, `OutputTargetStats`, `SFUISchemaItemRun`, `SearchResults`, `IGLTFNode`, `StyleProp`, `CredentialRecord`, `__HeaderBag`, `AsyncOrderedIterable`, `TupleTypeNode`, `NVM3Page`, `requests.ListTaggingWorkRequestLogsRequest`, `UserLoginResource`, `EventListeners`, `IChannelSigner`, `SetValue`, `Global`, `TarTransform`, `IResultTab`, `MagicSDKAdditionalConfiguration`, `GetUserCommandInput`, `ErrorAlertOptionType`, `FakePrometheusClient`, `ANodeExpr`, `TDataGroup`, `Discord.TextChannel`, `BubbleChartData`, `T4`, `requests.ListMetricsRequest`, `btCollisionObject`, `Party`, `RemoteData`, `MorphTargetManager`, `NzGraphDataDef`, `DukDvalueMsg`, `PaneProps`, `RuntimeError`, `RemoteTokenCryptoService`, `DomEventArg`, `OOPTypeDecl`, `SelectCard`, `QueryParamsType`, `ParseTreeMatch`, `TriggerPosition`, `ManagementClient`, `ReferenceRenderHandler`, `ProjectMetadata`, `ModuleWithProviders`, `HttpException`, `KeyType.rho`, `TheoryItem`, `GraphLayoutType`, `EventDescriptor`, `DeleteOrganizationCommandInput`, `FactoryIndex`, `ReactHarness`, `IResolvedQuery`, `JobChannelLink`, `SequenceNumber`, `TextureType`, `ThunkType`, `ProcessRepresentationChainModifier`, `AppThunkDispatch`, `PyteaService`, `DetachPolicyCommandInput`, `_resolve.AsyncOpts`, `PrunerConfig`, `ObservedDocument`, `TrackFormat`, `DependencyGraphNodeSchema`, `IPermissionSearchFilters`, `DomainItems`, `MapSearchCategory`, `CreateProcedureWithInput`, `CanaryAnalysisConfiguration`, `DeleteLeaderboardRecordRequest`, `GradientVelocity`, `SpringRequest`, `GetWrongDependenciesParams`, `StateAccessor`, `JestProcessRequest`, `TemplateListItem`, `LoggerFunction`, `MessageBundle`, `IEvent`, `IdentityProvider`, `SteemiaProvider`, `FieldsService`, `AssertionLevel`, `ContactConstraintPoint`, `Tweenable`, `UpdateProfileRequest`, `WaterfallChartData`, `gameObject.Battery`, `GfxCoalescedBuffersCombo`, `MerchantGoodsEntity`, `ICUToken`, `MatchDataSend`, `LogWrapper`, `XlsxService`, `MetadataClient`, `VisualizeAppStateTransitions`, `WorkDoneProgressReporter`, `RequestOptionsArgs`, `React.AnimationEvent`, `DraggableLocation`, `extendedPingOptions`, `CurveType`, `Ranking`, `FilePropertyReader`, `IdentifiedReference`, `ExitCode`, `ParameterListDetails`, `IEntrypoint`, `SnsDestination`, `IEntityRef`, `YDefinedFn`, `AbortMultipartUploadCommandInput`, `MockUser`, `JsonRpcError`, `AlignmentTypes`, `BaseCursor`, `StateChangeEvent`, `ColumnDefinition`, `SavedObjectsUpdateObjectsSpacesOptions`, `Alias`, `TTree`, `GraphicsGroup`, `AwaitedMessageEntry`, `i18n.Placeholder`, `GenericObject`, `NotifyParams`, `RematchDispatch`, `MockHTMLElement`, `OnboardingItem`, `Bip32Path`, `TKeyboardShortcut`, `CallEndReasons`, `ListRange`, `monaco.CancellationToken`, `StreamLabs`, `CSSDocument`, `KeyResultService`, `SObject`, `SavedObjectsClientCommonFindArgs`, `TransformOriginAnchorPosition`, `vscode.ProviderResult`, `ITokenModel`, `SteeemActionsProvider`, `EvmNetworkConfig`, `Snackbar`, `IArray`, `CustomAction`, `MenuInner`, `ComputedShapeParams`, `AppDispatch`, `OutputTargetCustom`, `Container3D`, `DataSourceItem`, `ExprContext`, `EventRegisterer`, `RARC.RARCFile`, `TLinkedSeries`, `RoutingTable`, `Credit`, `V0RulesService`, `QueryCapture`, `LitParser`, `FieldSetting`, `RolesEnum`, `ColorBlindnessMode`, `JsonObject`, `STAT`, `NetworkRequest`, `ICompileProvider`, `CurlCode`, `HeaderMapType`, `ConstructorDeclaration`, `ImportOptions`, `ApiScope`, `GLuint`, `AccountFilterData`, `EditDialogData`, `ClassNameStates`, `NodeHeaders`, `PredictableSupportCode`, `LoadingEvent`, `algosdk.Transaction`, `IDocumentInfo`, `TestMaskComponent`, `GlobalPooling2DLayerArgs`, `AdminService`, `IImageExtended`, `FilterizrOptions`, `RobotStateAndWarnings`, `ServiceErrorType`, `NativeActivation`, `PersistedLogOptions`, `FeedbackShowOptions`, `DynamicTreeCollisionProcessor`, `n`, `CalendarProps`, `GunNode`, `SubMesh`, `PlayerBattle`, `UpgradeSchemeWrapper`, `ICustomData`, `ODataModelEntry`, `CreateSessionCommand`, `Kernel.IOptions`, `MicrosoftComputeExtensionsVirtualMachineScaleSetsExtensionsProperties`, `VertexAttributeDefinition`, `UseTournamentRoundsState`, `LambdaHandler`, `SavedSearchTypes`, `NgZone`, `ElementFactory`, `ManagementAgentGroupBy`, `StatedFieldMeta`, `ScalingPolicy`, `DateProfile`, `Input.Gamepad`, `RequestConfiguration`, `BaseImageryMap`, `GithubConfiguration`, `Position`, `FunctionTypeFlags`, `Extra`, `FunctionMutability`, `BreakStatement`, `ClanAggHistoryEntry`, `InternalConfig`, `TestProvider`, `ts.ConditionalExpression`, `d.ResolveModuleIdResults`, `Backup`, `CommandInstance`, `BaseSymbolReference`, `ChangeType`, `IGrid`, `InterfaceWithConstructSignature`, `IIconSubset`, `Converter`, `UtilConvertor`, `BaseIncrementOptions`, `InterpolationPart`, `PatchRequest`, `EnumerateVisualObjectInstancesOptions`, `IExchange`, `FtpNode`, `UnregisteredAccount`, `MediaQueryList`, `FModel.LoadSettings`, `IFoo`, `IORouterRegistry`, `BitBucketCloudPRDSL`, `StyleMapLayerSettings`, `ICtx`, `Jimp.Jimp`, `ServerPlatform`, `M3ModelInstance`, `OAuthScope`, `ICoordinateData`, `GradientSize`, `IDejaDropEvent`, `TypeBuilder`, `Display`, `NormalizationHandler`, `CodeModDefinition`, `TranslationsType`, `UdpTally`, `FigmaPaint`, `DocMetadata`, `SfdxFalconProject`, `IWithComputed`, `DocumentHighlightParams`, `UIWaterStorage`, `TestEmitter`, `SimpleTemplateRunner`, `OptionsInterface`, `ResolveReferenceFn`, `PotentialEdgeInfo`, `PDFDict`, `IMapItem`, `IHsl`, `InternalModifiers`, `EndpointOptions`, `OrderData`, `BasePackageInfo`, `ExtendedCompleteItem`, `LayoutConfigJson`, `WriteBatch`, `SingleSelectionHandler`, `LoaderFn`, `IProperty`, `SuggestionsService`, `FinalizeHandlerArguments`, `SpecConfiguration`, `OPENSEARCH_FIELD_TYPES`, `DocumentRequest`, `SysMenu`, `IDataSlice`, `DataSourceSettings`, `CyclicTimeFrame`, `IPipeFn`, `VertexEvent`, `ISolutionExplorerService`, `mssql.config`, `RulesPosition`, `Injector`, `jsmap`, `EditProps`, `vscode.MarkdownString`, `BabelChain`, `ExperimentInterface`, `StackResult`, `CalculatedIndicatorValues`, `GridMaterial`, `WheelEvent`, `sdk.SpeechConfig`, `Float`, `ActiveDescendantKeyManager`, `PDFPageTree`, `VcsItemRef`, `MetaTagState`, `AuthPipe`, `p5ex.p5exClass`, `XTheme`, `HostKind`, `TagValidation`, `SyncProtocol`, `IpcMainInvokeEvent`, `CreateSecurityProfileCommandInput`, `M3Model`, `IRuleSpec`, `TProviders`, `RegionService`, `IHttp`, `ActorPath`, `ActionReducerMap`, `IRegisteredPlugin`, `JointComponent`, `FormattedBuilderEntry`, `CreateFunctionCommandInput`, `NzNotificationDataOptions`, `cxapi.CloudFormationStackArtifact`, `K5`, `RuleCatalog`, `SelectionInterpreter`, `IVorbisPicture`, `MenuComponent`, `GasModePage`, `ScalarsEnumsHash`, `FormOutput`, `SubmitKey`, `L1L2`, `BFBBProgramDef`, `Ship`, `GetDeploymentCommandInput`, `VLIEOffset`, `CapDescriptor`, `CodeActionProvider`, `Gif`, `TOut`, `LocationChangeListener`, `DataEventEmitter.EventCallback`, `DaffContactState`, `TArray`, `IAMCPCommand`, `LngLatAlt`, `OrganizationEditStore`, `StateMachineTargets`, `ISite`, `AnimatorChildRef`, `PlasmicTagOrComponent`, `ObjectQuery`, `MStreamingPlaylist`, `AsyncHierarchyIterable`, `TFolder`, `GovernorOptions`, `TableSelectionArea`, `TransactionWalletOperation`, `ConsoleExpression`, `TopicSubscription`, `ManifestCacheProjectAddedEvent`, `TargetLayoutNode`, `KeycodeCompositionFactory`, `IColor`, `RequestHeader`, `Ticker`, `Preference`, `RemoteFileItem`, `ExpressionListContext`, `HassEntities`, `ts.Statement`, `PromiseResult`, `NoticeService`, `DescribeReservedElasticsearchInstanceOfferingsCommandInput`, `UiActionsSetup`, `ThemesDataType`, `DeleteRoomRequest`, `ComponentFramework.Context`, `ChildMessage`, `yubo.RecordOptions`, `PluginCreateOptions`, `TextPlacement`, `StyleGenerator`, `DeploymentFileMapping`, `fixResults`, `DebeBackend`, `CalendarViewEvent`, `ContactService`, `ExtensionProps`, `VaultOptions`, `CommentDocument`, `GluegunCommand`, `ScopedObjectContextDef`, `AbiEvent`, `postcss.Root`, `PropertyMeta`, `ShuftiproKycResult`, `PDFRef`, `Dot`, `MultiChannelAssociationCC`, `ChatThreadPropertiesUpdatedEvent`, `FullLink`, `INgWidgetSize`, `KeysData`, `sdk.SpeechRecognitionResult`, `DisplayProcessor`, `ContentObserver`, `Generator`, `DeprecatedButtonProps`, `MutableControlFlowEnd`, `MoneyAmount`, `CreateProcedureWithoutInput`, `RegisterCertificateCommandInput`, `ICommandWithRaw`, `i128`, `BaseView`, `RelativeFunction`, `ExactC`, `IConstruct`, `VerticalAlignment`, `DatePicker`, `RuleFilter`, `TradeHistoryAccount`, `RetryOptions`, `Scoreboard`, `QueryData`, `RegisteredServiceAttributeFilter`, `MatSelectChange`, `VariableDefinitionContext`, `ListNodegroupsCommandInput`, `Parser.ASTNode`, `CurrentItemProps`, `StyledTextNode`, `TableListParams`, `WordcloudSpec`, `GridTile`, `IPageInfo`, `MongoCommand`, `ParentType`, `IAssetSearchParams`, `RuntimeExtensionMajorVersions`, `PadchatMessagePayload`, `RenderContext`, `ListRegexPatternSetsCommandInput`, `TransformationContext`, `JsonBuilder`, `OutfResource`, `RoomTerrain`, `PrivateCollectionsRoutes`, `MatchHandler`, `PartialValues`, `CLM.Condition`, `CompositeGeneratorNode`, `requests.ListVolumeAttachmentsRequest`, `Paging`, `Identifiable`, `PongMessage`, `IHomebridgeUiFormHelper`, `GraphQLEnumValue`, `Coords3D`, `Blockly.WorkspaceSvg`, `IGitResult`, `GridModel`, `RequestBodyObject`, `DAVObject`, `FullIconCustomisations`, `Additions`, `StyleIR`, `Extension`, `RxLang`, `SourceData`, `NoteRepository`, `OrganizationAccount`, `PointMesh`, `FeatureModule`, `RequestEntry`, `SyntheticPointerEvent`, `SearchOption`, `ChainableComponent`, `SnapshotFragmentMap`, `CreateGatewayCommandInput`, `DigestCommandOptions`, `TorrentDAO`, `BaseDataOptionType`, `ScopeNamer`, `ExclusiveDrawerPluginConstructor`, `ProjectUploader`, `ThemeStore`, `RegistrationService`, `SyncService`, `AdaptContext`, `SimulateOptions`, `ChannelResource`, `SortColumn`, `UIClass`, `DocBlockKeyValue`, `WindowModule`, `ISkillInfo`, `ImageItem`, `ExplicitPadding`, `SDKError`, `TokenPricesService`, `ActionDefinitions`, `MapControls`, `SingleOrArray`, `IEstimation`, `GfxCompareMode`, `Re_Exemplar`, `ConnectionCallback`, `MergedCrudOptions`, `WaterInfo`, `IXMLFile`, `CloudBuildClient`, `SwaggerDocument`, `BoxOptions`, `ParsedQs`, `GeoSearchFeature`, `MegalodonInterface`, `PutConfigurationSetDeliveryOptionsCommandInput`, `ISharePointSearchQuery`, `BasicCCGet`, `DriverContext`, `TrackByFunction`, `InboundStream`, `QueryObjOpts`, `DaffCartItemFactory`, `TreeviewFlatNode`, `EncodingType`, `Seconds`, `ResourceConfig`, `DiscoverPlugin`, `RouterStub`, `Interceptor`, `AdminJS`, `LocationSource`, `ExternalSubtitlesFile`, `LSTMCell`, `HttpInterceptord`, `STData`, `RepoOptions`, `Sources`, `ISignaler`, `UpdateBuilder`, `ParseCssResults`, `Seam`, `IEntityOwnership`, `ImageLike`, `BSplineSurface3dH`, `SfdxFalconError`, `ValueFormatterParams`, `GamepadButton`, `AmmConfig`, `ProjectModel`, `TypographyVariant`, `Automerge.Diff`, `QuestionMapType`, `ChildProcess.ChildProcess`, `WechatMiniprogram.CanvasContext`, `ListPublicKeysCommandInput`, `LiteralLikeNode`, `BuddyBuild`, `IAmAnotherExportedWithEqual`, `PrismaClientValidationError`, `TilePathGroup`, `ListStreamsRequest`, `RegExp`, `TransactionResponseItem`, `DeleteApplicationReferenceDataSourceCommandInput`, `ComponentInstruction`, `requests.ListSoftwareSourcePackagesRequest`, `UsedSelectors`, `PyJsonDict`, `TPT1AnimationEntry`, `BaseOperation`, `ResolvableCodeLens`, `DLabel`, `IndentedWriter`, `Session.IModel`, `AnkiOperationSet`, `MatrixModel`, `Explanation`, `CheckoutAction`, `StackLineData`, `ExportNodeProperties`, `AccessPolicy`, `IReCaptchaInstance`, `Relation`, `SecurityPluginSetup`, `requests.ListQuickPicksRequest`, `PubGroup`, `SettingName`, `PrincipalPermissions`, `MapType`, `IParentNode`, `AddressInfo`, `ParameterMetadata`, `IGarbageCollectionState`, `THREE.WebGLCapabilities`, `NoiseServer`, `ChangeAuthMode`, `MdastNodeMapType`, `PiExpression`, `HierarchyCircularNode`, `server.IConnection`, `apid.GetRecordedOption`, `IProject`, `BasicDataPropertyForAdvice`, `i.PackageInfo`, `CW20Addr`, `UsageInfo`, `SessionKeySupplier`, `LayerNormalization`, `ComponentDefinition`, `GetDetailRowDataParams`, `DemoteGroupUsersRequest`, `OrOptions`, `AdaptMountedPrimitiveElement`, `HttpsCallable`, `UseMutationReturn`, `ShowProgressService`, `SlotTreeItemBase`, `EveError`, `LineElement`, `CraftDOMEvent`, `IconElement`, `DOMHighResTimeStamp`, `AutoScalingConfiguration`, `RequirementFn`, `GetLifecyclePolicyCommandInput`, `SFC`, `LinearScale`, `ElementRefs`, `ComputerPlayer`, `GenericDispatch`, `ButtonStyle`, `TagAttributes`, `Syntax`, `puppeteer.ElementHandle`, `ListWorkRequestErrorsResponse`, `TestActions`, `Substream`, `UsableDeclaration`, `WowContext`, `FactReference`, `ExecutionError`, `MemoryShortUrlStorage`, `UseHydrateCache`, `YamlMapping`, `LabelUI`, `IDateRangeInputState`, `DescribeJobLogItemsCommandInput`, `TypeScriptType`, `TransactionHash`, `KeyAgreement`, `Marble`, `ServerErrorResponse`, `CephPoint`, `fhir.Patient`, `ImagePreviewProps`, `IReference`, `Mine`, `JOB_STATE`, `WalletTreeItem`, `FrontstageDef`, `CopySource`, `ControllerFactory`, `PoolMode`, `Gravity`, `ContextConfig`, `OpenSearchSearchHit`, `InsightInfo`, `UnescapedString`, `MessageFileType`, `PartyAccept`, `UpdateLaunchConfigurationCommandInput`, `ManifestActivity`, `StorageKey`, `MonsterProps`, `MigrationOptions`, `ParserFactory`, `DiscoverFieldProps`, `RegisterReq`, `HttpSetup`, `Knex.QueryBuilder`, `FrequencySet`, `ClassOrFunctionOrVariableDeclaration`, `MapperForType`, `SvelteComponentDev`, `DirectionalLight`, `IJwtPayload`, `TimePickerComponentState`, `BrowserController`, `RSAKeyPair`, `MetricFilter`, `t.Errors`, `FixedTermLoanAgency`, `MySQLClient`, `ZoomState`, `Twilio`, `MessageState`, `CompilationParams`, `InteractionStore`, `Pets`, `Q`, `KeyframeAnimation`, `DeviceVintage`, `FieldValues`, `ServerClosure`, `TypeAssertion`, `GeometryPartProps`, `TableCellProps`, `TagResourceResponse`, `PropertyOperation`, `WWA`, `NodeTypesType`, `AddTagsCommand`, `FindProjectQuery`, `TypedMutation`, `SavedVisState`, `ResourceConfiguration`, `Http3ReceivingControlStream`, `FileDto`, `DatosService`, `IAssetInfo`, `IndexPatternSpec`, `AnimationBuilder`, `HistoryAction`, `IQuickeyOptions`, `ThyButtonType`, `JsonSchema.JSONSchema`, `DOMAPI`, `ActionFactory`, `ListIdentityProvidersCommandInput`, `DescData`, `D`, `ModuleResolutionCache`, `TriplesecDecryptSignature`, `MapboxMarker`, `IWorkflowExecuteHooks`, `ResponsiveAction`, `WorkerAccessor`, `NumericF`, `HSD_TExpList`, `ArgSchemaOrRolesOrSummaryOrOpt`, `HostFileInformation`, `OpenSearchDashboardsReactContextValue`, `OutputParametricSelector`, `DbTx`, `TActor`, `Creep`, `BitstreamFormatDataService`, `WorkerMainController`, `MsgUpdateProvider`, `ITableColumn`, `IResolveResult`, `Particle`, `IFluidSerializer`, `HighlightSpan`, `VerifierConfig`, `CommerceTypes.ProductQuery`, `FeatureSource`, `CommandLinePart`, `ColorSwitchCCSet`, `OutputTargetDistGlobalStyles`, `BufferAttribute`, `ExtendedHttpTestServer`, `DescribeAlgorithmCommandInput`, `Dialogue.Argv`, `AccountEntity`, `InspectorEvents`, `SuiAccordionPanel`, `Margin`, `Span_Link`, `TransitionState`, `ILocationProvider`, `BaseInput`, `BaseRender`, `Patterns`, `IOrganizationContact`, `IconItem`, `SArray`, `TwitchServiceConfig`, `ISmsOptions`, `IErrorPositionCapable`, `BirthdayService`, `Matrix3`, `WorkspaceEntry`, `ReadonlyUint8Array`, `RequestHandler0`, `StyProg`, `AggArgs`, `CollidableLine`, `FilePathStore`, `d.OutputTargetDistLazyLoader`, `EnhancementRegistryDefinition`, `MountAppended`, `TSelectActionOperation`, `Impl`, `DeploymentNetwork`, `NextApiHandler`, `SelectBaseProps`, `Runtime.MessageSender`, `OrderFormItem`, `Foxx.Request`, `ValueOrFunction`, `AdministratorName`, `PeriodKey`, `DbObject`, `ExtendedSettingsDescriptionValueJson`, `SourceEntity`, `TestAwsKmsMrkAwareSymmetricDiscoveryKeyring`, `GLfloat`, `PaperInputElement`, `ExecutionEnvironment`, `SignatureKind`, `SchedulerApplication`, `GetApplicationCommandInput`, `EntityRecord`, `Frame`, `TodoItemNode`, `DraggingPosition`, `LibraryType`, `SlatePluginDefinition`, `PreferencesStateModel`, `IExecutionResponse`, `P8`, `DialogResult`, `RepositoryFacade`, `ZoomStore`, `UrlGeneratorsDefinition`, `MockNode`, `DeferredValue`, `RoomVisual`, `CameraService`, `DataSourceState`, `StatsModuleReason`, `WebhookOptions`, `GroupDataService`, `RendererInfo`, `MeasuredBootEntry`, `GroupsPreviewType`, `InputConfiguration`, `SharedPropertyTree`, `PutLifecyclePolicyCommandInput`, `StudioServer`, `tape.Test`, `TopicOrNew`, `MeterCCReport`, `ImplicitParjser`, `Override`, `RawConfigurationProvider`, `MeshAnimationTrack`, `CreateSubscriberCommand`, `KeyedAccountInfo`, `ILanguageRegistration`, `fabric.IEvent`, `RecordC`, `NoteDoc`, `VisualizationData`, `DataKind`, `RawNode`, `ThrottledDelayer`, `UpdateServiceCommandInput`, `ContentOptions`, `IMasks`, `RouteFilter`, `OrmConnectionHook`, `RadixTokenDefinition`, `ChildProcessWithoutNullStreams`, `Extrinsic`, `requests.ListAnnouncementsPreferencesRequest`, `MakeSchemaFrom`, `ProvideCompletionItemsSignature`, `ImageStyleProps`, `ConfigHandlerAndPropertyModel`, `CheckpointsOrCheckpointsId`, `BroadcastEventListener`, `DirectiveOptions`, `SequenceInterval`, `PSIVoid`, `OpenAPIV3.Document`, `DomElement`, `LeaveRequest`, `UntagResourceCommandOutput`, `RefetchOptions`, `JSDocTypeReference`, `IOrganizationContactCreateInput`, `PrismaClientFetcher`, `GraphQLResolveInfo`, `ResourcePackWrapper`, `ComponentWithAs`, `OptionParams`, `ModelMapping`, `requests.SearchSoftwarePackagesRequest`, `TypeAcquisition`, `SubjectSetConstraint`, `LockFileConfigV1`, `PredicateOperationsContext`, `Notifier`, `Web3`, `ScheduleConfiguration`, `RecordProvide`, `DeleteAppRequest`, `Axes`, `IDeviceWithSupply`, `BrowserInterface`, `ItemMetadata`, `RoosterCommandBarButtonInternal`, `api.Span`, `StatusUnfollow`, `IssueTree`, `KeyValueChangeRecord`, `ChangePart`, `Benchee.Benchmark`, `IndexOptions`, `IObservableValue`, `Meal`, `DefinitionResult`, `ast.ExternNode`, `League`, `SubjectKeyframes`, `Swagger2`, `IBoxPlotColumn`, `HappeningBreakpoint`, `Builtins`, `Composer`, `LazyDisposable`, `Stream.Readable`, `RouteComponentProps`, `CallMemberLikeExpression`, `Web3ProviderType`, `debug.IDebugger`, `TabInfo`, `FieldFormatEditorFactory`, `ServerMode`, `PacketParams`, `tfc.Tensor`, `mozEvent`, `IncomingMessage`, `ObservableSetStore`, `Input`, `TypeAlias`, `RouterAction`, `ParsedEnumValuesMap`, `EffectFallbacks`, `ReferencedSymbol`, `CircuitGroupState`, `SetConstructor`, `u32`, `UpdateDatasetCommandInput`, `Severity`, `Cwd`, `PathFilterIdentifier`, `Human`, `AdvertiseByoipCidrCommandInput`, `URLTransitionIntent`, `IElementRegistry`, `OrphanRequestOptions`, `BattleFiledData`, `PerformOperationResult`, `SpriteFontOptions`, `RootContext`, `CommunicationIdentifierKind`, `Protocol.ServiceWorker.ServiceWorkerVersion`, `RouterEvent`, `ObsidianLiveSyncSettings`, `ButtonWidth`, `RegisteredConnector`, `AnimKeyframe`, `FFT`, `BuildNode`, `RequestInformationContainer`, `SRTFlags`, `SettingModel`, `ESTree.Class`, `EstimateGasEth`, `apid.UnixtimeMS`, `ShouldSplitChainFn`, `DaffCart`, `TwingNodeType`, `SelectTool`, `AgentService`, `CategoryDescription`, `d.OutputTargetDist`, `ImageAlignment`, `SearchParameters`, `IVirtualDeviceResult`, `TestAudioBuffer`, `UnwrapNestedRefs`, `BVHNode`, `PropertyDetails`, `NamedImportBindings`, `RepoBuilder`, `TreeConfig`, `DataChunk`, `ToastrService`, `NotFoundErrorInfo`, `Stats`, `RenderInfo`, `UpdateChannelCommandInput`, `Network`, `EntityDispatcherDefaultOptions`, `MockCanvas`, `PurchaseProcessor`, `IMatrixConsumer`, `Chorus`, `GetRevisionCommandInput`, `TextProperty`, `CommandData`, `CallLikeExpression`, `IAccessToken`, `EntityDefinitionService`, `ConstantQueryStringCommandInput`, `AbstractMessageParser`, `WebpackWorker`, `ExecSyncOptions`, `IOSNotificationCategory`, `ImageLocation`, `TagScene`, `AcMapComponent`, `SFUManager`, `FactoryUser`, `ts.Symbol`, `SocketClass`, `IElementStyle`, `HttpFetchOptionsWithPath`, `PackagerAsset`, `VariableContext`, `Parameters`, `EventHit`, `GeomNode`, `BuildResults`, `sharp.Sharp`, `RangePointCoordinates`, `JSDocReturnTag`, `Config.InitialOptions`, `TObj1`, `SavedObjectsCreatePointInTimeFinderOptions`, `datetime.DateTimeData`, `FleetStatusByCategory`, `Transformed`, `ListManagementAgentPluginsRequest`, `SceneNode`, `UnionOrIntersectionType`, `FormModel`, `Stripe.PaymentIntent`, `PatchType`, `RecoveredSig`, `MODNetConfig`, `IORedis.RedisOptions`, `Models.CurrencyPair`, `CERc20`, `Hash`, `TInjectItem`, `ModelStoreManager`, `JoinTournamentRequest`, `HistoryRPC`, `ILabel`, `UnlitMaterial`, `Warning`, `ItemGroup`, `LogsEvent`, `SortedReadonlyArray`, `ConstantTypes`, `InvalidArgumentException`, `IStoreService`, `StacksConfigRepository`, `keyboardState`, `WebSocket.ErrorEvent`, `CreateApplicationResponse`, `TargetDisplaySize`, `TypeLiteralNode`, `ScreenshotDiff`, `LogMethod`, `ResolverClass`, `TaskWrapper`, `MapMaterialAdapter`, `NextConfig`, `ViewsWithCommits`, `AbstractCrdt`, `LazyIterator`, `CancellationTokenSource`, `Electron.IpcMainInvokeEvent`, `CodeType`, `QueryBeginContext`, `CombatantViewModel`, `IDebugResult`, `SupCore.PluginsInfo`, `ComponentDef`, `MediaQueryListEvent`, `SQLiteDb`, `OrganizationSlug`, `Assertion`, `DescribeEnvironmentManagedActionHistoryCommandInput`, `MemBank16k`, `OfflineSigner`, `GeneralObject`, `SemanticsFlag`, `SnotifyToastConfig`, `ButtonGroupProps`, `TensorArrayMap`, `ListRecipesCommandInput`, `PrerenderConfig`, `ListAutoScalingConfigurationsCommandInput`, `vscode.TextEditorDecorationType`, `StreamEmbedConfig`, `MarkSpec`, `OAuthConfig`, `DevicesButtonProps`, `UiActions`, `UriService`, `ExperienceBucket`, `InterceptorContext`, `requests.ListCertificatesRequest`, `ExternalSourceAspectProps`, `TouchControlMessage`, `HistoryEnv`, `ServiceFlags`, `IStringStatistics`, `IOEither`, `ToastMessage`, `ComponentCompilerWatch`, `MemoryX86`, `W7`, `SourceState`, `UITableView`, `Mail`, `InferenceFlags`, `AttributeValueSetItem`, `IManifest`, `EmployeeAppointment`, `Items`, `CostMatrix`, `Material`, `UploaderBuilder`, `TransportRequest`, `Nibble`, `SubInterface`, `CombinedReportParameters`, `Callback`, `HookName`, `GeoUnits`, `MultiIndices`, `CompletionMsg`, `estypes.SearchResponse`, `responseInterface`, `UserIdentifier`, `GoAction`, `CustomerRepository`, `LSPConnection`, `CellValue`, `MapOfClasses`, `CrowdinFileInfo`, `FormatCompFlags`, `AlarmSensorType`, `DeveloperExamplesSetup`, `CFCore`, `UpdateNote`, `THREE.Scene`, `ItemSpec`, `TdDataTableService`, `UpdateServerCommandInput`, `TextFont`, `ConfigArgs`, `DiscoverSetupPlugins`, `HttpService`, `JSDocAugmentsTag`, `FoamFeature`, `ImportClause`, `EntityCollectionServiceElementsFactory`, `PlayerLink`, `APIWrapper`, `IGiftsGetByContactState`, `CsvReadOptions`, `AxisScale`, `Fetcher.IEncrypted`, `PuppetASTClass`, `AutorunFunction`, `RollupBuild`, `StackProc`, `AwsVpcConfiguration`, `EngineConfigContent`, `StreamManager`, `GauzyAIService`, `PendingModifiedValues`, `UpSampling2DLayerArgs`, `GLTFNode`, `IRenderFunction`, `GLsizei2`, `InDiv`, `DataBySchema`, `TransportWideCC`, `FormProperty`, `FindQuery`, `ExpensiveResource`, `requests.ListModelsRequest`, `interfaces.BindingOnSyntax`, `ts.LeftHandSideExpression`, `TreeStructure`, `TimeSeries`, `SchemaConfigParams`, `core.IHandle`, `SphereGeometry`, `DAL.DEVICE_ID_THERMOMETER`, `ThermostatFanMode`, `GfxFormat`, `CompletionExpressionCandidate`, `NetworkState`, `PiLangExp`, `ISocket`, `RElement`, `AstNodeParser`, `ReactNativeContainer`, `IssueStatus`, `ConeLeftSide`, `SmoldotProvider`, `ResolvedEntityAtomType`, `ISlope`, `DateIntervalFormatOptions`, `PromiseQueue`, `VolumeTableRecord`, `Tmpfs`, `NotificationId`, `SwitchOrganizationCommand`, `DescribeExportTasksCommandInput`, `XDate`, `PlatformRender`, `ItemDefBase`, `SparseArray`, `UIResource`, `CollectionPage`, `ClassType`, `Variant`, `OpsMetrics`, `WorldmapPointInfo`, `IMonitoringFilter`, `UnlinkFromLibraryAction`, `WriteContext`, `IMigrationConfig`, `StyleRules`, `IndexKind`, `U8Archive`, `InitialStatistics`, `ScatterPointItem`, `CommandQueueContext`, `Typeless`, `Sorting`, `WasmSceneNode`, `LexoRank`, `pouchdb.api.methods.NewDoc`, `RateLimiter`, `StringASTNode`, `ManagedDatabaseSummary`, `MatDialogRef`, `FormControlProps`, `FormikErrors`, `MsgCloseBid`, `SkipListMap`, `BuildTask`, `CreateTemplateCommandInput`, `RtkQueryApiState`, `JobPostLike`, `IApiComponents`, `PokerScoreService`, `Stash`, `LeveledDebugger`, `ObjectGridComponent`, `SqrlKey`, `ElementSet`, `Repository`, `PartialEmoji`, `T.LayerStyle`, `Bluetooth`, `ThreadState`, `ParamIdContext`, `ValidationService`, `PointStyle`, `RateProps`, `fs.WriteStream`, `MemoryHistory`, `fGlobals`, `MetaDataModel`, `CandidateInterviewersService`, `Uint32Array`, `RenderArgs`, `ContractService`, `GetCommandInvocationCommandInput`, `StackMap`, `UrlParam`, `PossibleValues`, `StorageReference`, `AbbreviationTracker`, `MediaInfo`, `models.ChatNode`, `MutationResolvers`, `Survey.Base`, `Choice`, `ContentGroup`, `InstanceInfo`, `LinkParticle`, `PartialItem`, `ThyNotifyOptions`, `XsuaaServiceCredentials`, `BTI_Texture`, `CollectionDataStub`, `ScoreInstrument`, `AddTagsToResourceCommandInput`, `ThemePair`, `EnvironmentService`, `PropertyDrivenAnimation`, `TaskModel`, `Criteria`, `ColumnsSortState`, `QueryCache`, `ErrorMiddleware`, `BufferedTransport`, `AllSettings`, `ProfileIdentifier`, `CompilerEventDirDelete`, `AudioSelector`, `HubPoller`, `WindowsJavaContainerSettings`, `PeerRequestOptions`, `WrappedFunction`, `KaizenToken`, `IMiddleware`, `ICurve`, `BuilderRuntimeEdge`, `ISmartMeterReadingsAdapter`, `ValidationRuleMetaData`, `AvailableSpaceInConsole`, `PickTransformContext`, `QueryGroupRequest`, `ImageStyle`, `Router`, `PlanningRestriction`, `DataAdapter`, `SavedObjectsRawDocParseOptions`, `BulkUnregistration`, `ReactiveArray`, `IStandaloneCodeEditor`, `BoxShadow`, `Clique`, `LineType`, `NodeId`, `XPathResult`, `MenuServiceStub`, `MeshRenderer`, `ProposalTx`, `RemoteFilter`, `JsonParserTransformerContext`, `ProtocolName`, `ExtendedChannelAnnouncementMessage`, `PullAudioOutputStreamImpl`, `BuildOptions`, `MySQLParserListener`, `FirmaSDK`, `InvalidGreeting`, `Tensor1D`, `WeConsoleScope`, `PreviewService`, `ValueFillDefinition`, `IClassification`, `Git.VersionControlRecursionType`, `MdcDialogPortal`, `PacketEntity`, `AccountingEvent`, `DeleteApiKeyCommandInput`, `APISet`, `TimerActionTypes`, `Prism`, `TransformFunction`, `TableDifference`, `IGatsbyImageData`, `CompletionsProviderImpl`, `PointLight`, `ConstantExpressionValue`, `GetReplicationConfigurationCommandInput`, `MessageConnection`, `IPluginBinding`, `CurrentVersion`, `DocHeader`, `MarketData`, `ThanksHistory`, `LabelMap`, `GX.IndTexMtxID`, `BeancountFileContent`, `T.Layer`, `SourceEngineView`, `TwingCallable`, `Semester`, `AnyMap`, `MeetingSessionVideoAvailability`, `Foxx.Response`, `CSSSnippetProperty`, `EngineArgs.MarkMigrationAppliedInput`, `IGameCharaUnit`, `PipelinePlugin`, `com.mapbox.pb.Tile.IFeature`, `TypedGraph`, `Level`, `SerializedCrdtWithId`, `EnvelopesQuery`, `RefreshInterval`, `TransactionProto.Req`, `SupportedExt`, `sbvrUtils.PinejsClient`, `ProcessGraphic`, `SrtcpSSRCState`, `ModuleG`, `TextTheme`, `CanvasTypeVariants`, `MutationName`, `ConfigFileExistenceInfo`, `ContextValue`, `OptionComponent`, `ModifyGlobalClusterCommandInput`, `Movement`, `TemplateContext`, `PackageMeta`, `ESTree.Identifier`, `requests.ListDatabaseSoftwareImagesRequest`, `KeyboardLayout`, `NodeMaterial`, `SequenceDeltaEvent`, `SqrlErrorOutputOptions`, `ActiveToast`, `OhbugEventWithMethods`, `CoreConfig`, `SignedContractCallOptions`, `WordCharacterKind`, `HdEthereumPaymentsConfig`, `BracketPair`, `NonFungiblePostCondition`, `capnp.Data`, `Multiset`, `CandidateCriterionsRatingService`, `AuthenticatorFacade`, `IMemFileSystem`, `LayerListItem`, `xml.ParserEvent`, `EncodingQuery`, `ChannelContext`, `OriginOptions`, `GitHubCommit`, `ShellCommand`, `PutResourcePolicyCommandOutput`, `IDatabaseResultSet`, `requests.ListPingProbeResultsRequest`, `INamesMap`, `Builtin`, `UnlockedWallet`, `InvalidationLevel`, `Controller2`, `DiagramModel`, `RepositoryOptions`, `End`, `TextElementLists`, `ProjectControlFunction`, `DescribeAppInstanceCommandInput`, `backend_util.ReduceInfo`, `Sink`, `FSAOptions`, `StepName`, `SubmissionJsonPatchOperationsService`, `FnCall`, `FileStatWithMetadata`, `PuppetASTResolvedProperty`, `AzExtClientContext`, `ConfigurationDTORegions`, `IJetView`, `Serverless.Options`, `IMappingFunction`, `CertificateVerify`, `CreatePostDto`, `CreatePagesArgs`, `DatabaseContract`, `CheckReferenceOriginsParams`, `UIState`, `SyncRule`, `HeaderColumnChain`, `LocalMarker`, `ServerTranslateLoader`, `TextureCube`, `Sheet`, `ListOptions`, `IRequest`, `ProgressStep`, `CombinedScanResult`, `BillingModifier`, `GX.RasColorChannelID`, `GithubService`, `StateTree`, `MonthPickerProps`, `CSSDataManager`, `Cancel`, `TestIamPermissionsRequest`, `PlaneAltitudeEvaluator`, `SearchError`, `WebSocketEvent`, `AudioVideoEventAttributes`, `StridedSliceDenseSpec`, `Tied`, `TEConst`, `ChangeInstallStatus`, `OpenYoloCredential`, `ValuesDictionary`, `AttributeData`, `RemoteStream`, `ExtendedSocket`, `SeriesRef`, `AggregationRestrictions`, `ContractEventDescriptor`, `Mutable`, `NewsroomState`, `HandlerDefinition`, `IGarbageCollectionDetailsBase`, `GetObjectCommandInput`, `UnocssPluginContext`, `ItemSpace`, `EventSubscriber`, `UseRefetchReducerState`, `ConversationTarget`, `ts.EnumMember`, `ParsedAuthenticationInstructions`, `TokenRecord`, `InheritanceNode`, `NormalizedRuleType`, `EngineAPI.IApp`, `GenericTable`, `KoaContextWithOIDC`, `ReactText`, `ts.NodeArray`, `MovementComponent`, `MetamaskNetwork`, `ReadonlyQuat`, `V1StatefulSet`, `InvalidFormatError`, `IGeneratorData`, `ViewModelReducerState`, `CollectionInstance`, `UsageExceededErrorInfo`, `TransportType`, `HelloResponse`, `ExtractorResult`, `Shipment`, `NavigationTrie`, `IPeripheral`, `NoteItemComponent`, `Quantity.OPTIONAL`, `UpdateInputCommandInput`, `ENUM.SkillRange`, `AssetModel`, `MerchantStaffEntity`, `Factor`, `WlMedia`, `ExecutionMessage`, `LambdaType`, `UpdatePartial`, `TransitionStatus`, `WorkNodes`, `VerificationMethod`, `CellRenderer.CellConfig`, `DescribeDBSubnetGroupsCommandInput`, `Form`, `ModuleElementDeclarationEmitInfo`, `MutationArgsType`, `BuiltinFunctionMetadata`, `LIST_ACTION`, `Shadow`, `SearchStrategySearchParams`, `PredicateContext`, `TopNavMenuData`, `IContentItem`, `CreateSavedObjectsParams`, `BuildSettings`, `ScheduleState`, `Positive`, `BufferChannel`, `People`, `RouteDataFunc`, `ParameterApiDescriptionModel`, `ExpressionRenderHandler`, `Unchangeable`, `DeclarationInfo`, `BoostDirectorV2`, `PackageUser`, `ConditionsType`, `fhir.DocumentReference`, `UniqueEntityID`, `RecordBaseConcrete`, `Variable`, `NohmModelExtendable`, `Union3`, `JSXTemplate`, `IFileMeta`, `IStateBase`, `ParameterWithDescription`, `PropertyChangeResult`, `common.AuthParams`, `LinksFunction`, `IEmployeeProposalTemplate`, `GlobalContext`, `SecurityPermission`, `IWalletContractService`, `EntityApi`, `RequestEntryState`, `BSONType`, `OneOfAssertion`, `ListRoomsResponse`, `StackSpacing`, `QueryOrderOptions`, `BTCMarkets.currencies`, `OrganizationDocument`, `sdk.CancellationDetails`, `S3Resource`, `ClientJournalEntryIded`, `QuestionProps`, `ModelInfo`, `TestRunArguments`, `SymbolDisplayPart`, `ISemver`, `GanttBarObject`, `TopicInterest`, `HdPublicKey`, `VerifiedParticipant`, `React.ReactText`, `PatchSource`, `IKChain`, `ModuleSystemKind`, `ApplyPredicate`, `GfxSamplerFormatKind`, `ConfigurationLoader`, `PoolSystem`, `AggObject`, `IGenericEntity`, `PlacementResult`, `PlanetGravity`, `BitcoinPaymentsUtils`, `FinalDomElement`, `ODataEntitySetResource`, `RebootInstanceCommandInput`, `BuildState`, `CategoriesService`, `PiStyle`, `CliOutputOptions`, `DeleteJobCommandInput`, `Rarity`, `SolverConfig`, `PurchaseInfo`, `PageRect`, `LoggingInfo`, `ReactFrameworkOutput`, `MethodOptions`, `StateValue`, `RecordMap`, `EventUi`, `BIP44HDPath`, `OverlayConnectionPosition`, `TestCommander`, `ChartOffset`, `AppComponentDefinition`, `GeneralImpl`, `MessagePacket`, `UpdateWindowResizeSettings`, `UserRegistrationData`, `Showable`, `altair.LightClientUpdate`, `PrivateIdentifier`, `PDFKitReferenceMock`, `DigitalInOutPin`, `Git.IAuth`, `ListDatasetGroupsCommandInput`, `ReferenceSummary`, `IOOption`, `OperationLink`, `CloudAssembly`, `ListElementSize`, `FeatureState`, `GX.CC`, `DialogType`, `NamespacedAttr`, `SchemaArg`, `QueryCommand`, `PackageInfos`, `GoToTextInputProps`, `DiffuseMaterial`, `ElementDecorator`, `Units`, `QnaPost`, `LocalRenderInfo`, `LoadLastEvent`, `RetrievedCredentials`, `ServerSecurityAlertPolicy`, `AnimationBoneKeyFrameJson`, `TTypeProto`, `TransferParameters`, `SocketIoConfig`, `theia.WebviewPanelShowOptions`, `MatchedStep`, `CompileUtil`, `FacetSector`, `DefaultToastOptions`, `CacheManagerOptions`, `RippleSignatory`, `RewriteResponseCase`, `UpdateIdentityProviderCommandInput`, `LineRange`, `TextRenderStyle`, `d.FsWriteOptions`, `Operator`, `Dialogic.Item`, `SampleInfo`, `EntityFetcherFactory`, `IAnyObject`, `ComponentEventType`, `IndexInfo`, `VerticalAlignValue`, `SendMessageRequest`, `AS`, `IPluginConfig`, `TransactionsModel`, `ITagObject`, `UniversalRenderingContext`, `IScopedClusterClient`, `AuthorizationServiceSetup`, `InvokeCreator`, `DescribeScheduleCommandInput`, `ProjectTechnologyChoice`, `React.Reducer`, `SerializableObject`, `SerializationService`, `DeleteDBClusterParameterGroupCommandInput`, `UserSettings`, `XMLHTTPRequestMock`, `PreferenceProvider`, `QueryServiceClient`, `FrontMatterResult`, `TimeInput`, `SymbolResolutionStackEntry`, `UseQueryOptions`, `DestinationHttpRequestConfig`, `UnidirectionalLinkedTransferAppAction`, `ProductAction`, `DatasetStatistics`, `SpecQueryModel`, `AutoScalingMetricChange`, `DisclosureInitialState`, `SnapshotRelation`, `ServiceContext`, `SyntaxKind.Identifier`, `ICXSetup`, `AsyncBlockingQueue`, `HttpServiceSetup`, `ContextMenuItemModel`, `DirectionConfiguration`, `CapabilitiesProvider`, `NmberArray9`, `StandardAccounts`, `FocusOutsideEvent`, `ITransferItem`, `TranslationStorage`, `NamespaceObject`, `EventSummary`, `Ogg.IPageHeader`, `IUploadItem`, `IFinaleCompilerOptions`, `AzureCommunicationTokenCredential`, `IdentifierValue`, `SystemVerilogSymbolJSON`, `td.WebRequest`, `MouseWheelEvent`, `SettingActionTypes`, `WebGLRenderCompatibilityInfo`, `RawAbiDefinition`, `ChatStoreState`, `UnitState`, `TextProps`, `PymStorage`, `DataCharacter`, `CSharpField`, `AdbClient`, `OptimizelyXClient`, `ParameterConstraints`, `DashboardReport`, `CombatLogParser`, `RFNT`, `MockDocumentTypeNode`, `ProviderApi`, `AndroidActivityEventData`, `ApiResponseOptions`, `DaffNewsletterState`, `ObserverResponse`, `MockStoreCreator`, `WebCryptoEncryptionMaterial`, `ListTypesCommandInput`, `AppOption`, `Decipher`, `StripeModuleConfig`, `LegacySpriteSheet`, `KibanaFeatureConfig`, `RouterActions`, `VerificationClient`, `LoanCard`, `HierarchyChildren`, `RuntimeWorker`, `d.PrerenderConfig`, `TOptions`, `NetworkStatus`, `N1`, `MapPartsRailMoverNrv`, `RandomFunc`, `PackageJsonChange`, `IChangeInfo`, `ERC1155ReceiverMock`, `Arrow`, `PayloadInput`, `ConnectionContext`, `Equipment`, `Epic`, `GunScope`, `AndroidManifest`, `GlobalStateService`, `ExtractorEventEmitter`, `cdk.Stack`, `IApiConnection`, `moment.MomentStatic`, `NZBUnityOptions`, `CreateMemberCommandInput`, `BufferReader`, `ProfileData`, `AstSymbol`, `AddressAnalyzer`, `AnyItemDef`, `ProgressBar`, `METHOD`, `TestEnvironmentConfig`, `AnimVectorType`, `DocumentEntryIded`, `ZodTypeAny`, `VictoryPointsBreakdown`, `TransactionAndReceipt`, `ModuleLoaderActions`, `Web3Client`, `EntityID`, `TAbstractFile`, `ErrorChunk`, `CdkFooterRowDef`, `AttendanceMonth`, `ReactNodeArray`, `GameService`, `MessageDeserializationOptions`, `InteractiveState`, `CategoryType`, `FormatWrap`, `MoviesService`, `NbMenuService`, `PluginDebugAdapterContribution`, `ModifierToken`, `d.ServiceWorkerConfig`, `IMessageDefinition`, `Sequential`, `requests.GetZoneRecordsRequest`, `PartialCanvasTheme`, `SelectionShape`, `EventCreator1`, `GitLogCommit`, `Unit`, `ItemTypes`, `CORSOptions`, `TSESTree.Decorator`, `IndexMapping`, `IMainConfig`, `DatabaseQuery`, `VolumeBackupSchedule`, `HostService`, `AcceptFn`, `ConnTypeIds`, `TAggParam`, `AjaxConfig`, `ILocalDeltaConnectionServer`, `Prefs`, `EnvironmentTreeItem`, `FleetAuthzRouter`, `ListKeysRequest`, `Codefresh`, `StandardClock`, `IndicatorCCGet`, `GfxBufferP_GL`, `PagerXmlService`, `IndependentDraggable`, `TwitterUser`, `ManualServer`, `StatGroup`, `AngularFireStorage`, `GUIDriverMaker`, `BuilderDataManagerType`, `GanttDatePoint`, `PanelModel`, `requests.ListFunctionsRequest`, `EtherscanClient`, `IWorkflow`, `hm.BasicCredentialHandler`, `MsgStartGroup`, `SMTCallGeneral`, `KernelBackend`, `ChartSonify.SonifyableChart`, `IDocumentElementKey`, `NftType`, `NVM500Details`, `EntityTypeT`, `Val`, `X86Context`, `MutableVector3d`, `ClientStringService`, `DaffConfigurableProduct`, `PoiManager`, `LayerForTest`, `TrueFiCreditOracle`, `CreateTableOptions`, `Anomaly`, `BridgeInfo`, `ScopeGraph`, `ShaderSemanticsInfo`, `DebuggerMessage`, `SpotifyErrorResponse`, `cytoscape.EventHandler`, `SubFeaturePrivilege`, `IEventHubWizardContext`, `BaseQuery`, `ServiceScope`, `FormControl`, `BlockFactorySync`, `AuthenticationDataState`, `IColonyFactory`, `DashboardContainerFactoryDefinition`, `TwitchBadgesList`, `CompositeMenuNode`, `Code`, `RowHashArray`, `OptimizationContext`, `MultisigConfig`, `CoreModule`, `InternalOpts`, `IStorageUtility`, `d.JestEnvironmentGlobal`, `ReadonlyVec3`, `ItemUpdateResult`, `TFLiteNS`, `ExternalDMMF.Document`, `APIUser`, `PlotRowIndex`, `N5`, `FirebaseOptions`, `ClaimToken`, `KnobsConfigInterface`, `LedMatrixInstance`, `TestProject`, `KeyIdentity`, `LanguageCCSet`, `EventAxis`, `IApiProfile`, `TFLiteWebModelRunnerOptions`, `IConnectable`, `TreeView.DropLocation`, `OptionsAfterSetup`, `webhookDoc`, `PermissionDeniedState`, `Moc`, `OrderbookL2Response`, `requests.GetJobRequest`, `UserGeoLocations`, `KeyContext`, `vile.PluginList`, `ts.CommentRange`, `EventEmitter`, `LoopReducer`, `x.ec2.SecurityGroup`, `ng.ICompileProvider`, `InternalDiagnostic`, `ITestEntity`, `UpdateStackCommandInput`, `QueryParam`, `QPoint`, `FcNode`, `StoredPath`, `BlockchainClient`, `DisposeResult`, `PrintResultType`, `MathContext`, `IAttachmedFile`, `mat4`, `MediaSubtitlesRelation`, `TSlice`, `MDCTabBarView`, `RuleFix`, `Transactions`, `DrgRouteDistributionMatchCriteria`, `ArrayServiceArrToTreeOptions`, `LibraryEngine`, `firebase.firestore.FirestoreDataConverter`, `PyVar`, `t_44e31bac`, `EdgeCalculatorSettings`, `IncomeService`, `RouteDefinitions`, `Urls`, `BalanceChecker`, `PropsFieldMeta`, `ModelVersion`, `OhbugExtension`, `JStep`, `ISlideRelMedia`, `RecordSetWithDate`, `TCmd`, `BaseTask`, `QualifiedUserClients`, `GluegunFileSystemInspectTreeResult`, `UpdateActivatedEvent`, `CipherService`, `TsPaginatorMenuItem`, `d.HostConfig`, `Chatlog`, `ConstructorParams`, `LaunchContext`, `ManualOracle`, `AggregatedStat`, `PlayerEntity`, `DynamicActionsState`, `AnchorProps`, `FactoryRole`, `TagsViewState`, `mediaInfo`, `PrismaClientOptions`, `DescribeApplicationCommandInput`, `MsgSharedGroup`, `VRMSpringBoneGroup`, `_Transaction`, `VFS`, `pulumi.Resource`, `ComponentSetup`, `LoopBackFilter`, `AppxEngineStepGroup`, `UINavigationController`, `TagRenderingConfig`, `MatSnackBarRef`, `DocumentReference`, `QueryDeepPartialEntity`, `Subsegment`, `SWRKeyInterface`, `VideoTileController`, `ReadGeneratedFile`, `SwankConn`, `SplinePoint`, `HTMLMetaElement`, `BlobModel`, `ITestObjectProvider`, `GitManager`, `MultiSet`, `StatusIndicatorGenericStyle`, `JSXAttribute`, `LatLngLiteral`, `MenuItemConstructorOptions`, `EChartsCoreOption`, `DatabaseSchema`, `CompositeLocale`, `TextContent`, `ICustomerRepository`, `BillAmount`, `xlsx.Sheet`, `CursorPagingType`, `GatherShape`, `IEmbeddable`, `RumEvent`, `NexusPlugin`, `DraggableElement`, `CommentProps`, `GlobalEventDealer`, `GetBotCommandInput`, `PackagePolicyInputStream`, `DataWriter`, `IKernelConnection`, `PropertyPreview`, `DataModel.ChangedArgs`, `JMapInfoIter`, `HdBitcoinPaymentsConfig`, `Survey.Page`, `ToolingLog`, `EndCondition`, `AddMissingOptionalToParamAction`, `Envelope`, `ValueMetadataString`, `BuildFeatures`, `RealtimeAttendeePositionInFrame`, `MdDialog`, `SamplerDescriptor`, `CheckoutAddressesPage`, `DecorationSet`, `BellSchedule`, `NativeScrollEvent`, `ts.ObjectLiteralExpression`, `CancelableRequest`, `NodeFlags`, `CustomTypes`, `SubmissionSectionObject`, `requests.ListTaggingWorkRequestErrorsRequest`, `IPerformTasksCommandArgs`, `ARNodeInteraction`, `Routing`, `ValidationException`, `CeloTransactionObject`, `UpdateMigrationDetails`, `PrefV2`, `Install`, `JRPCResponse`, `StorageEvent`, `ColumnWidths`, `CandidateTechnologiesService`, `IExplanationMap`, `ThyTranslate`, `DocEntry`, `DashboardStart`, `RawSavedDashboardPanel620`, `MToonMaterial`, `JsonRpcResponseCallback`, `CompileContext`, `TypeConstructor`, `DownloadInfo`, `BaseOption`, `IHttpClient`, `ListEmailIdentitiesCommandInput`, `DescribeChangeSetCommandInput`, `ElementData`, `Log`, `FormatterOptionsArgs`, `GfxBufferP_WebGPU`, `SymbolOr`, `HostsByIpMap`, `NavigationGuardNext`, `Match`, `TestingModuleBuilder`, `com.nativescript.material.core.TabItemSpec`, `MSDeploy`, `ExceptionalOpeningHoursDay`, `SearchResponse`, `DueDate`, `RollupClient`, `SettingsType`, `TreeSelectionReplacementEventArgs`, `SearchComponent`, `IndicatorCCSet`, `KuduClientContext`, `MIRInvokeKey`, `SecretProvider`, `Specification`, `ChannelTreeItem`, `TextChangeRange`, `IIncome`, `TT.Step`, `CombinationKind`, `CSSVariables`, `DescribeDetectorCommandInput`, `ChartRequest`, `RedocThemeOverrides`, `Settled`, `Extras`, `SourceDir`, `NormalizedEsmpackOptions`, `xyData`, `monaco.editor.ITextModel`, `MatrixEntry`, `GetEnvironmentCommandInput`, `DbMempoolTx`, `PDFAcroText`, `MessageRequest`, `TxResult`, `CreatePresetCommandInput`, `RobotState`, `DBProvider`, `RegisterDomainCommandInput`, `NamespaceScope`, `AnyApi`, `LanguageCCReport`, `PluginSpec`, `SfdxOrgInfo`, `DynamoDB.ReturnConsumedCapacity`, `Frontstage1`, `vscode.TreeItem`, `DependencyDescriptor`, `ExpressMeta`, `FactoryResult`, `IWebhookMatchedResult`, `MVideoUUID`, `ReduxAction`, `Civil`, `Hostname`, `SubsystemType`, `PiTypeStatement`, `ExportInfo`, `UniswapVersion`, `Request`, `Widget.ResizeMessage`, `BalanceTransferPayload`, `SpotTag`, `PlayerInputModel`, `TrueConstraint`, `ContentTypeProperty`, `FetchableType`, `ITerminal`, `TestingRuntime`, `ResourceXML`, `PredicateProvider`, `FluidDataStoreContext`, `CoapForm`, `MediaManager`, `GenericDeclarationSupported`, `AzureDeployerService`, `IViewArgs`, `LibraryNotificationActionContext`, `CausalRepoCommit`, `ExpressionStatement`, `vscode.EventEmitter`, `ModifyPayloadFnMap`, `Cropping2D`, `ElementMeta`, `NormalRange`, `TSubfactionArmy`, `Telemetry`, `CheerioElement`, `CustomClientMetadata`, `ArcTransactionDataResult`, `ExoticComponent`, `TrueFiPool2`, `MountOptions`, `CompilerEventFileDelete`, `DateInput`, `ImportedCompiledCssFile`, `ViewportHandler`, `RNConfig`, `ListRuleGroupsCommandInput`, `NotificationType`, `ExportTypesRegistry`, `ErrorWithLinkInput`, `PropertyUpdatedArgs`, `ToastId`, `d.LoadConfigInit`, `GoalTimeFrame`, `QueueFunctions`, `requests.ListSourceApplicationsRequest`, `Bit`, `AuthenticationSession`, `cc.Node`, `GlyphplotComponent`, `JsNode`, `SimplifyOptions`, `ThisExpression`, `CanvasIconTypes`, `SpinnerProps`, `TaskGroup`, `Slicer`, `AppType`, `Deferred`, `ICanvasProps`, `UrlSegmentGroup`, `CommandLineParameter`, `TradeService`, `BlockchainService`, `TableRequestProcessorsFunction`, `ISdkBitrate`, `InitOptions`, `LinkedListNode`, `TileLevel`, `ZoneAwarePromise`, `IVec2Term`, `SerializeOpts`, `ChannelsSet`, `Bundler`, `CameraKeyTrackAnimationOptions`, `DidResolutionOptions`, `IResourceInfo`, `SecurityCCNonceReport`, `NgGridItemSize`, `AuxConfig`, `JobSavedObjectService`, `CompilerSystemRenameResults`, `Thenable`, `SymbolWithScope`, `Web3Utils`, `Builder`, `ChartTemplatesData`, `CloneOptions`, `ImportStatement`, `ListEnvironmentsCommandInput`, `ProfilePage`, `BaseField`, `Recipients`, `ShootingNode`, `yubo.IRecordMessage`, `AST.Node`, `GridGraphNode`, `RemoteUserRepository`, `WalletStore`, `CMB`, `Themed`, `CreateConnectionDetails`, `FlattenedFunnelStepByBreakdown`, `JobValidationMessageId`, `Pos`, `InterfaceDeclaration`, `IService`, `BaseCallback`, `GetConnectionsCommandInput`, `CombinedEntry`, `LicenseState`, `TimelineProps`, `CodeMirror.EditorFromTextArea`, `AWSOrganizationalUnit`, `UnvalidatedIndexingConfig`, `PullRequestReference`, `RoomLayout`, `MessageObject`, `RPCResponse`, `SelectBuilder`, `SectionState`, `ArrayTypeNode`, `ShortcutService`, `IndexPatternValue`, `CommandsMutation`, `AdminUserEntity`, `ExpressClass`, `workspaces.ProjectDefinition`, `IndexTemplate`, `AppConfirmService`, `FnU2`, `RunningState`, `AbstractCancellationTokenSource`, `three.Object3D`, `CoinPayments`, `ArmResourceTemplate`, `ColorModeRef`, `RewardManager$1`, `FundingStrategy`, `WalletMock`, `INetworkNavigatorNode`, `UserDescription`, `DependencyChecker`, `RockType`, `SVGMark`, `TableRowState`, `KeyRingService`, `Access`, `CountingChannel`, `LocalContext`, `KPuzzleDefinition`, `StorageObject`, `LocalStorageSinks`, `d.JestConfig`, `ConvectorController`, `STLoadOptions`, `EditArticleDto`, `VariableAST`, `Mapper`, `DockPanel`, `ITabData`, `SPort`, `TopAppBar`, `VitePluginConfig`, `SignatureDeclaration`, `EmailService`, `NodePbkdf2Fn`, `BitFieldResolvable`, `PurgeHistoryResult`, `next.Page`, `CurrencyDisplayNameOptions`, `MemoryInfo`, `IExpense`, `ISubgraph`, `SelectOptionBase`, `IResultGroup`, `Interaction`, `FixtureFunc`, `GfxrAttachmentSlot`, `StartInstanceCommandInput`, `ReqMock`, `word`, `EnumValueDefinitionNode`, `IRequestDTO`, `SecretWasmService`, `URIAttributes`, `UserProvider`, `GraphQLFieldConfigMap`, `CreateComponentCommandInput`, `EndOfDeclarationMarker`, `ExpressionFunctionTheme`, `TestRunner`, `QueryPlan`, `firebase.firestore.Timestamp`, `CachePolicy`, `SessionStorageSources`, `ReactElement`, `VroRestClient`, `TRPCClient`, `HydrateScriptElement`, `ViewEvent`, `IPropertiesElement`, `PdfCreator`, `Layouter`, `NodeTypes.IMessagingService`, `StringDocument`, `ITempDirectory`, `SkillLogicData`, `ng.ICompileService`, `ReduxReducer`, `ObservableQueryBalances`, `PrettierOptions`, `K.StatementKind`, `MatMulPackedProgram`, `DbService`, `ReportGenerator`, `BitmexSpy`, `OnTouchedType`, `VirtualCollection`, `Monster`, `VRMBlendShapeProxy`, `AutoCompleteContext`, `ITrace`, `DeleteApplicationRequest`, `Ellipse`, `DropOptions`, `NavAction`, `RedBlackTreeEntry`, `Alt`, `GanttService`, `CurveLocationDetail`, `WindupMember`, `EntityDto`, `TicketDoc`, `StylingContext`, `BilinearPatch`, `BaseTxInfo`, `Mountpoint`, `ArticleDetail`, `ModernRoute`, `next.Artboard`, `IEndpointOptions`, `IRepo`, `EndpointArgument`, `REQUIRED`, `PolyfaceAuxData`, `PutObjectCommandInput`, `ResolverRegistry`, `requests.ListCrossConnectsRequest`, `GetRequest`, `RpcClientFactory`, `GraphQLScalarType`, `configuration.uiType`, `CSG`, `CheckBoxProps`, `IUIProperty`, `Iterable`, `TypeNames`, `VariableLikeDeclaration`, `IFilterListItem`, `PreimageField`, `CreateAppInstanceCommandInput`, `RenameLocation`, `cc.Sprite`, `GoogleActionsV2AppRequest`, `StoreClass`, `IInputIterator`, `CompSize`, `AvailableMirror`, `Joi.ObjectSchema`, `MEvent`, `SharedMetricsPublisher`, `JsonFormsStateContext`, `CreateRuleCommandInput`, `PutDeliverabilityDashboardOptionCommandInput`, `Animated.Node`, `ProcessRepresentation`, `DataRow`, `SrtpSSRCState`, `GraphOptions`, `Circline`, `IInstruction`, `BlobEvent`, `GeoObject`, `ClientHttp2Stream`, `BNLike`, `GetAllAccountsRequestMessage`, `SessionsState`, `mat2d`, `ConfigKey`, `ProjectsActions`, `ViewContainerRef`, `ExecaReturnValue`, `DeepStateItem`, `SubmissionProgress`, `socketio.Server`, `MaterialData`, `ts.ModuleDeclaration`, `RequestsDataItem`, `ActionCreators`, `BuildListInstanceCreateOptions`, `SignedResponse`, `GameStateRecord`, `ListCV`, `messages.Pickle`, `TransactionDetails`, `LocationInformation`, `INetwork`, `RequestStatistics`, `CompilerEventBuildNoChange`, `Taro.request.Option`, `PriceSpec`, `CreateErrorReportInput`, `Models.GamePosition`, `Datafile`, `BuildVisConfigFunction`, `RecordSubType`, `apid.GetReserveOption`, `PostQueryVarsType`, `IGrid2D`, `RtcpTransportLayerFeedback`, `AnimationKeyframesSequenceMetadata`, `PcmChunkMessage`, `ConfigIntelServer`, `firebase.FirebaseError`, `Primitives.Point`, `ChangeInfo`, `LocalMicroEnvironmentManager`, `GaxiosResponse`, `ScaleContinuous`, `SafeHtml`, `IEventPlugin`, `Serenity`, `WindowManager`, `TypeDBTransaction`, `QualifiedRule`, `CreateDatasetImportJobCommandInput`, `ResolvingLazyPromise`, `MatrixArray`, `IHttpResult`, `DaoFilter`, `ISchema`, `UILog`, `Directionality`, `ProviderFrameElement`, `IpAddress`, `FilterEngine`, `Moized`, `State`, `NameBindingType`, `ColorSchemeName`, `WechatMaterialIdDTO`, `AttributionsWithResources`, `LoginItemProps`, `PSTTableBC`, `AllKindNode`, `ICommandPalette`, `GraphStoreDependencies`, `ImageDataLike`, `handleEvent`, `CreateChannelMembershipCommandInput`, `DefineMap`, `ABIDecoder.DecodedLog`, `GalleryActions`, `PasswordSchema`, `BoxGeometry`, `THREE.Box2`, `ts.TypeQueryNode`, `Sticker`, `IBuildTask`, `SnippetSession`, `HsQueryBaseService`, `Security2Extension`, `ClientHttp2Session`, `ByteWriter`, `A0`, `RenderCanvas`, `Waveform`, `IAggregateStructure`, `SearchResultsLayer`, `TokenResult`, `DiagnosticAddendum`, `SharedDelta`, `RouteArg`, `Whitelist`, `IParameterDefinitionsSource`, `RequestBody`, `ColDef`, `MergeQuerySet`, `StateContext`, `IConnectOptions`, `ICard`, `InvoiceEstimateHistoryService`, `TooltipPoint`, `Replace`, `LinearSearchRange2dArray`, `Unpacker`, `PixivParams`, `CSharpDeclarationBlock`, `EdmxMetadata`, `USB`, `ServiceHttpClient`, `ModalWindowProps`, `BitReader`, `LuaMultiReturn`, `IFileChanges`, `ConstraintTiming`, `TrendResult`, `requests.ListPublicIpsRequest`, `Sidebar`, `RoutingService`, `MatchCallback`, `SystemType`, `VIS0_NodeData`, `ChartConfig`, `GltfFileBuffers`, `ProfileStore`, `FetchArgs`, `PoolConnection`, `PostMessage`, `IsometricPath`, `PropertyDescription`, `InferredSize`, `IApiSecurityRequirement`, `TokenPosition`, `RenderableSprite3D`, `LoginModel`, `ScreenshotBuild`, `IAuthenticateOidcActionConfig`, `SignedOnUserService`, `ITestReporter`, `MagicMessageEvent`, `IndentToken`, `HashKeyType`, `RoomManager`, `HoveredNavItemPayload`, `CommandContext`, `TimeRaster`, `SceneMouseEvent`, `TRaw`, `SeoService`, `SuggestQueryInterface`, `HighlightRepository`, `NextcloudClientInterface`, `DataViewObject`, `IUserPPDB`, `FocusTrapManager`, `Uint64Id`, `ChatLoggedType`, `NativeReturnValue`, `RowList`, `MarkdownOptions`, `NodeCue`, `KeyboardNavigationAction`, `WebSocketAdapter`, `ComponentItem`, `IDeploymentStrategy`, `StynWalk`, `DBDocument`, `MapValue`, `ColumnsPreviewType`, `UniqueId`, `ConditionFilterType`, `UseCaseExecutorImpl`, `NetworkInterface`, `CommonStatusBarItem`, `SerializedPolicy`, `InputHandler`, `SessionTypes.Proposal`, `SnailfishNumber`, `IVottJsonExportProviderOptions`, `AssessmentTypeData`, `QR.QueryResult`, `IPty`, `UserAnnotation`, `PointComponentProps`, `ProtectedRequest`, `LogAnalyticsLabelView`, `DemoChildGenerator`, `XArgs`, `BOOL`, `FilterValueFormatter`, `SnackbarService`, `AkimaCurve3dOptions`, `BufferEncoding`, `msRest.RequestOptionsBase`, `ChildItem`, `UnauthorizedException`, `ITenantCreateInput`, `RequestHandlerEntry`, `HttpEffect`, `ITextFieldExpression`, `FieldTypeByEdmType`, `KeywordMatcher`, `ts.ClassDeclaration`, `Tenancy`, `UserSelection`, `egret.DisplayObject`, `GestureTypes`, `BigNumber`, `LastSnapshot`, `CopyImageCommandInput`, `AstNodeFactory`, `AddTagsCommandOutput`, `AsyncManager`, `RankState`, `ApiItem`, `P2PPeerInfo`, `IVueComponent`, `WebLayer`, `SubscriptionCallback`, `InsecureMode`, `ExtractResponse`, `Electron.App`, `Filesystem.FileExistsAsync`, `BaseError`, `TopicType`, `QueuePeekMessagesResponse`, `BuilderOutput`, `ExpressRouteCircuitPeering`, `TreeService`, `SketchName`, `BuilderDataManager`, `SqrlSlot`, `storeType`, `RecordsFetchFilters`, `NativeNode`, `BrowserIndexedDBManager`, `bbox`, `ContractFunction`, `requests.ListThreatFeedsRequest`, `UpdatePayload`, `VoyagerConfig`, `ExpressAdapter`, `TokenItem`, `monaco.editor.ICodeEditor`, `ShellString`, `LView`, `Year`, `TAuditReport`, `BriefcaseConnection`, `EqualityComparison`, `MutableVector4`, `RowAccessor`, `UserActionBuilder`, `Language`, `NodePositionOffset`, `DebugState`, `MultiMaterial`, `FrameOffset`, `SpeechRule`, `GetIdentityVerificationAttributesCommandInput`, `sdk.SpeechRecognitionEventArgs`, `ResolvedModuleFull`, `BankTransfer`, `ParseNode`, `ConstructionSite`, `ng.IFilterService`, `Meeting`, `NavigationEntry`, `TaskCustomization`, `RangeValue`, `IInjector`, `AtlasResourceSource`, `ITypedDump`, `IScoutStems`, `DocumentPositionStateContext`, `ServiceConfigurationOptions`, `MarkovChain`, `FileDoc`, `InternalDefaultExpression`, `URLDescriptor`, `ActionItem`, `TextInput`, `WhereGrouper`, `Filesystem.ReadJsonSync`, `MessageGeneratorImplementation`, `AttributeOptions`, `Evaluation`, `core.BIP32Path`, `AnyAction`, `CmsModelFieldToGraphQLPlugin`, `SearchResult`, `ITokenizer`, `RadixSpunParticle`, `NerModelVersion`, `WorkItemUI`, `LogItem`, `GfxTextureSharedP_WebGPU`, `ModuleDest`, `IESAggField`, `IDocumentReference`, `IdSelector`, `KnownDomain`, `IPdfBrick`, `Timers`, `ConditionOperator`, `server.Server`, `AppConfigType`, `VirtualFolder`, `PlacementType`, `Displayable`, `_Column`, `TextView`, `FormatterService`, `lsp.Connection`, `Stores`, `DeviceTypes`, `BotConfig`, `TimelineMax`, `CheckpointTrie`, `SupportedFiletypes`, `EnvPair`, `RARC.JKRArchive`, `ExecutableItem`, `CacheChangeEventData`, `ReviewId`, `EngineTypes`, `BitBucketServerPRComment`, `ServiceWorkerRegistration`, `DragAction`, `ObservableQuerySecretContractCodeHash`, `ApolloReactHooks.MutationHookOptions`, `TransferTransactionUnsigned`, `SurveyTemplateRendererViewModel`, `ViewType`, `NPCActorCaps`, `PathSolution`, `EndorsementPolicy`, `TArrayValue`, `TouchState`, `TIdType`, `GetStaticPropsContext`, `BinaryOpComplexProgram`, `ExplorationInfo`, `EntitySet`, `ListParticipantsRequest`, `PanelProps`, `FastifyTypeBoxRouteOptions`, `ReferenceArray`, `GVBox`, `PortRange`, `ObjectDefinitionBlock`, `CallHierarchyIncomingCall`, `UserUpdate`, `DataListItem`, `DepNodeAssembly`, `EdmxEntitySet`, `TraitLabel`, `FieldStruct`, `ObjectUpdatesService`, `WebsocketService`, `AnyProps`, `XDomain`, `IPercentileAggConfig`, `TestColdObservable`, `XNodeData`, `MessageWorkflowMapping`, `DatasetEntry`, `RawDimension`, `FileDiagnostics`, `JobCreatorType`, `FileChunkIterator`, `Progress.IChunk`, `Province`, `KVS`, `AutoFix`, `TestServiceContext`, `InputTypes`, `DiscoverUrlGeneratorState`, `AddValue`, `CallGNode`, `ContainerFormData`, `THREE.Camera`, `IBuildTaskConfiguration`, `PrefetchOptions`, `DefaultRouterOptions`, `EnableOrganizationAdminAccountCommandInput`, `SerialAPICommandContext`, `IOrganizationTeamCreateInput`, `AuthTokenResult`, `CheckoutState`, `any`, `NodeCryptoCreateHash`, `DetectionResultItem`, `EmitterSubscription`, `CodePointCharStream`, `CIImage`, `SNSTopicArnNotFoundFault`, `JSONWebToken`, `AppletType`, `CSSScope`, `CreateConnectorResponse`, `GetSessionCommandInput`, `DataState`, `...`, `ExternalModuleInfo`, `ImportedData`, `ForwardTsnChunk`, `SpriteArgs`, `ListItemBase`, `AppSources`, `CommandArgs`, `d.CollectionCompilerVersion`, `PerPanel`, `TimeScaleUnit`, `Checkpoint`, `ICoordinates`, `ReaderFragment`, `Uint8Array`, `ImGui.IO`, `ChangePasswordState`, `EarlyStoppingCallbackArgs`, `StableRange`, `IAmazonServerGroupCommand`, `SavedObjectsFindOptions`, `MGLMapView`, `DouyuPackage`, `ChromeBreadcrumb`, `DeserializeFunction`, `SearchThemeAttributes`, `CodeGeneratorFileContext`, `FormEntry`, `ConstructorTypeNode`, `FrameworkVersionId`, `RepositoryEditWriteModel`, `NPMContext`, `Failure`, `ArrayCriteriaNode`, `PrismaObjectDefinitionBlock`, `AuthResult`, `Collapse`, `ModelValue`, `LayoutAction`, `MockCamundaWorkflow`, `NotifyModel`, `CustomEditorUpdateListener`, `StatedBeanContainer`, `PublicDeviceDTO`, `request.CoreOptions`, `Comm`, `NbJSThemeOptions`, `GPUData`, `ui.Rectangle`, `ts.EnumDeclaration`, `HttpOperationResponse`, `ClientIntakeFormIded`, `Arity1`, `PromiseFulfilledResult`, `ParserInputWithCtx`, `RelatedClassInfo`, `ValidationResponse`, `lf.schema.Table`, `UploadableMap`, `requests.ListInstancesRequest`, `SourceType`, `EmbedProps`, `PdfSolidBrush`, `IRule`, `ParseFunction`, `WebGLTransformFeedback`, `LocationResult`, `TMap`, `ConstantSchema`, `UnwrappedArray`, `IPartialDeploymentTemplate`, `ComputeVariant`, `t.MemberExpression`, `IntPair`, `LineIds`, `DeleteUserProfileCommandInput`, `Mdast.Parent`, `FieldItem`, `RepositoryState`, `ExistsFilter`, `Crop`, `AsyncActionCreators`, `EthUnlockRecord`, `ScriptLike`, `GMSMapView`, `V1WorkflowOutputParameterModel`, `DataContextGetter`, `arc_result`, `ReportConfigurationModel`, `KeyLoader`, `TFEOpAttr`, `CmdParts`, `TwingOutputBuffer`, `EntityReference`, `MeetingSessionStatus`, `ToastPosition`, `Cubic`, `ObjectCallback`, `Security2CCMessageEncapsulation`, `Highlighter`, `ICommandMapping`, `KeywordPrefix`, `IUserService`, `MySet`, `SharingSession`, `DeleteProjectResponse`, `messages.Meta`, `IconMap`, `IEvents`, `PingPongObserver`, `Totals`, `PuzzleLoader`, `CaptionDescription`, `BackstackEntry`, `Debouncer`, `DidChangeLabelEvent`, `FeatureMap`, `MonoStyleViews`, `SBDraft2CommandOutputBindingModel`, `DbEvent`, `FeatureRegistry`, `Maximum`, `GunGraphConnector`, `IntervalCollection`, `TestStore`, `RegExpMatcher`, `DocumentService`, `ListAliasesCommandInput`, `ScenarioState`, `IVectorV`, `IProjectSetupData`, `InstallablePackage`, `requests.ListCpesRequest`, `RollupError`, `vscode.ShellExecutionOptions`, `EditableCell`, `TCollection`, `d.BuildTask`, `ViewWithBottomSheet`, `CdsNavigationItem`, `XPortalService`, `DAL.DEVICE_ID_BUTTON_B`, `JsonRpcProvider`, `Trade`, `AngularFire`, `RenderModel`, `GraphQLHOCOptions`, `DBInstance`, `FontWeightType`, `TransactionCtorFields`, `NodeAnnouncementMessage`, `UiActionsEnhancedSerializedEvent`, `AccountMongoRepository`, `DroppableProvided`, `ListTasksRequest`, `EditService`, `MenuPath`, `ListResolversRequest`, `NotificationTargetItem`, `ListHttpProbeResultsRequest`, `ReuseTabCached`, `MouseCoordinates`, `Mention`, `GetBlacklistReportsCommandInput`, `EdgeInsets`, `IBackendApi`, `VocabularyService`, `ReadableSignal`, `DaffSubdivisionFactory`, `DomCallback`, `TaskNow`, `RenderColumn`, `SemanticDiagnosticsBuilderProgram`, `YarnPackageManager`, `RouterRes`, `IndexService`, `SerializedEntity`, `SfdxFalconResult`, `ConnectionService`, `ChartAntVSpec`, `ElectronStore`, `CatDTO`, `StoreModel`, `ConfigItem`, `PluginInfo`, `CHR0`, `InvoicesService`, `ExtraControlProps`, `PackageJSON`, `DeviceInfo`, `OptimizationResult`, `ActivityAttendance`, `TransformContext`, `RawToken`, `SunBurstHierarchyNode`, `TransformPointFn`, `EntityAddOptions`, `UpdateClusterRequest`, `EnvConfig`, `RenderTextureInfo`, `ArticleOverview`, `UriResolver`, `ExprVis`, `MyTabItem`, `ApexTestGroupNode`, `TemplateHead`, `ListComponentsCommandInput`, `CommandEntityBuilder`, `FabricObject`, `GfxCullMode`, `ThreadChannel`, `VisibilityVertex`, `ApiConfiguration`, `PrintJsonWithErrorsArgs`, `Swagger.Schema`, `ClipboardJS`, `FormAppSetting`, `CtrTextureHolder`, `IDBCursorDirection`, `A6`, `requests.ListPackagesInstalledOnManagedInstanceRequest`, `InvitationDTO`, `AggsMap`, `TileReadBuffer`, `IdentityPermissions`, `KeyboardEventArgs`, `EnrichedAccount`, `ChannelMessageRemove`, `MediaSource`, `ITimelineItem`, `HTMLOListElement`, `IFluxAction`, `Node.Expression`, `PropEnhancerValueType`, `SolidityListener`, `ShaderDescriptor`, `ManagedEvent`, `RLANKeyframe`, `AnimationPromise`, `QueryProvidersRequest`, `AsyncDiffSet`, `EVMEventLog`, `IBaseProps`, `CategoryAxis`, `NamespacedWireDispatch`, `ViewBoxParams`, `TypedNavigator`, `PolyserveApplication`, `GitlabUserRepository`, `Rx.PartialObserver`, `ListableObject`, `Backend`, `WebGLFramebuffer`, `IKeyboardBindingProps`, `GX.KonstAlphaSel`, `PDFArray`, `FlatpickrFn`, `SubscriptionAccountInfo`, `OpenLinkProfiles`, `TestTimelineDataProvider`, `Identifier`, `CreateFleetCommandInput`, `GfxBindingLayoutDescriptor`, `ObjectExpression`, `SharedContentImp`, `HierarchicalEntity`, `LineResults`, `DeleteStackCommandInput`, `VirtualConfig`, `ToggleState`, `ProxyDao`, `DeeplinkPayPayload`, `UploadFileStatus`, `IActionInputs`, `CarouselButton`, `AnyChannel`, `TextFormatter`, `MockApiClient`, `ODataCallable`, `PieChart`, `UserResumeEntity`, `ValidationControllerFactory`, `ENDStatement`, `BotTagMasks`, `LoadAll`, `DeleteDomainResponse`, `ColorPickerProps`, `ITestContainerConfig`, `GoogleMeetSegmentationConfig`, `CollapseGroupProps`, `IEmitterBehavior`, `ConnectorReferenceHandler`, `IResolver`, `PrintTypeFlags`, `ExtendableMessageEvent`, `ChainsService`, `angular.ui.bootstrap.IModalServiceInstance`, `PddlWorkspace`, `EntityComparer`, `Topology`, `ProjectReflection`, `IComponentState`, `V3RouteWithValidQuote`, `SWRResponse`, `SpanKind`, `TargetSummary`, `EffortInfo`, `ArenaAttribute`, `ICommand`, `TextRenderer`, `StdSignature`, `FunctionDefinitionContext`, `PowerlevelCCReport`, `ThyFormDirective`, `ParityRegion`, `CdsRadio`, `CreateAliasCommandInput`, `OrderDoc`, `ITokenPayload`, `PriceAxisViewRendererData`, `sdk.ConnectionEventArgs`, `DebugProtocol.Request`, `OneofDescriptorProto`, `Element.JSON`, `ActionData`, `RouteMeta`, `LocalBlockExport`, `DOMString`, `VirtualItem`, `Capabilities`, `DeepLinker`, `FatalErrorsSetup`, `MatStepperIntl`, `ResizeStrategy`, `types.CSSProperties`, `VSvgNode`, `WorldState`, `NumberSystemName`, `EditorChangeLinkedList`, `DragSourceArguments`, `requests.ListRulesRequest`, `PointerCtor`, `PartialStoryFn`, `UpdateProfileCommandInput`, `jsdom.JSDOM`, `SocketContextData`, `IFirmware`, `CloudProvider`, 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`RouterState`, `Graphics`, `RectangleObject`, `KeyboardKey`, `NullAction`, `ProvisioningParameter`, `GitClient`, `ErrorResponseData`, `Stub`, `CompilerConfig`, `ListRecommendationsRequest`, `ATNState`, `IAssetComponent`, `ReactNode`, `Animated.AnimatedInterpolation`, `IdentifierToken`, `Triangle3`, `FormatType`, `ContractCallReturnContext`, `ISimplestConfigFile`, `ExpectationRepository`, `ProviderCard`, `FormatState`, `DescribeWorkspaceCommandInput`, `RuleManager`, `VersionInterface`, `TeleportContext`, `UserTypeReference`, `CreateUserDto`, `ArmArrayResult`, `rpcConfig`, `d.JsonDocsUsage`, `IClass`, `WrapLocals`, `RemoveRoleFromDBClusterCommandInput`, `ControllerParameterMetadata`, `HsDimensionTimeService`, `ComboConfig`, `AudioOptions`, `ResultDate`, `MessageContext`, `Events.pointerup`, `GetCapabilitiesXmlLayer`, `ArrayMultimap`, `JobID`, `constructor`, `Highcharts.StockToolsNavigationBindings`, `PrivateLinkConnectionApprovalRequestResource`, `EthereumTransactionTypeExtended`, `ChatLogged`, `FileConfig`, `IGlTFParser`, `HouseCombatData`, `PlaywrightElementHandle`, `nls.LocalizeFunc`, `CountryService`, `B8`, `LocalForageObservableChange`, `PositionService`, `BigIntMoneyBase`, `MathBackendWebGL`, `HandlerResult`, `ActionHandlerWithMetaData`, `LocaleNode`, `KeySignature`, `SeedGenerator`, `ValueDB`, `SlashDot`, `YoonitCamera`, `ParquetSchema`, `TableDiff`, `TaskDoc`, `FilterCallback`, `ServiceType`, `DuiDialog`, `QueryBidResponse`, `BuddhistDate`, `Stylesheet`, `CallbackAction`, `RepeatVectorLayerArgs`, `EmitterWebhookEvent`, `BlockNumberRepository`, `LocaleSpec`, `Comonad1`, `PathOptions`, `Frontier`, `ActionBar`, `Controls`, `IsoBuffer`, `CurriedFunction1`, `TriggerInteractions`, `CompilerWorkerContext`, `TEX0Texture`, `IteratorCreatorFn`, `es.CallExpression`, `TestDataset`, `DecoratedError`, `AvatarSize`, `GoogleAuth`, `PlasmicASTNode`, `SrtpSsrcState`, `NoteCollectionState`, `IItem`, `ListRecommendationsResponse`, `Integration`, `DeleteOneOptions`, `MatcherCreator`, `ModState`, `ProjectClient`, `PackageInstallationResult`, `DescribeChannelMembershipCommandInput`, `ComponentEmitInfo`, `LibraryInfo`, `StatFrame`, `EditableCircle`, `Print`, `ImGuiIO`, `TaskTreeItem`, `CKEDITOR.eventInfo`, `middlewareSingle`, `ConnectedSpaceId`, `AES`, `IIconOptions`, `SinonFakeServer`, `iReduxState`, `ComponentRef`, `ArrayAccessValue`, `d.BuildLog`, `RailPart`, `ExtrusionFeatureParameters`, `TelegramBot.Message`, `XUL.menupopup`, `MpProduct`, `IRepositoryState`, `AlertState`, `EventStoreDescription`, `RivenMod`, `MockConfiguration`, `EventCategoriesMessage`, `IBBox`, `PaginationInput`, `GraphQLInputType`, `VoidFn`, `FastifyRequest`, `MWCListIndex`, `WidgetType`, `ClientRect`, `ConfigurableEnumValue`, `Exception`, `AV1RtpPayload`, `DocumentRegistryBucketKey`, `FlagValidatorReturnType`, `ImmutableFrameTree`, `TransferService`, `ContextItem`, `FormValidator`, `Float64Array`, `WebRTCConnection`, `PropsType`, `WholeHalfNone`, `Directory`, `JsonParserContext`, `Geocoder`, `Data`, `SnippetProvider`, `Modify`, `MapChart`, `TemplateStruct`, `TItem`, `TableConstructor`, `RawJSXToken`, `StatusVectorChunk`, `ISubscriber`, `AuthenticateFn`, `NumberRowModel`, `OperatorContextFunction`, `ts.MapLike`, `TypeAssertionMap`, `ExecutionResultDataDefault`, `PaginationOptions`, `DashboardSetup`, `https.RequestOptions`, `CoverLetterService`, `MediaMatcher`, `FsReaddirOptions`, `IDeferred`, `SimpleSwapAppState`, `DharmaMultiSigWalletContract`, `RollupSingleFileBuild`, `VisualizationsStart`, `ComponentModule`, `AnimationInstance`, `RedisClientOptions`, `OptionsHelper`, `TETuple`, `IConfirmService`, `quantumArray`, `UrlEntity`, `DocumentSymbolCollector`, `TransactionEntityDataService`, `MergeProps`, `DashPackage`, `Reaction`, `Conditions`, `protocol.FileRequest`, `EarningsTestService`, `TAccesorKeys`, `BlockBody`, `SharedRoleMapping`, `Prepared`, `GetMessagingSessionEndpointCommandInput`, `Chai.ChaiStatic`, `FairCalendarView`, `IListProps`, `FlowPostContextManagerLabel`, `UserReference`, `TFnRender`, `STORES`, `And`, `cytoscape.Core`, `FirebaseFirestore`, `ClusterData`, `PrometheusClient`, `EntityCache`, `QuestionAdornerComponentProps`, `SCServerSocket`, `IListViewCommandSetExecuteEventParameters`, `IEdgeRouter`, `OutputTargetDistCollection`, `IGetPatchDirResult`, `TableNS.CellProps`, `Exchange`, `ParseConfig`, `SettingTypes`, `SourcePosition`, `requests.ListDrgRouteRulesRequest`, `ColorT`, `tsdoc.DocComment`, `EntAsset`, `messages.Examples`, `ProjectionRule`, `C6`, `WidgetState`, `TeamCity`, `GoToFormProps`, `Favorite`, `MaybeAccount`, `EslintConfig`, `RepairTask`, `Application.RenderOptions`, `OctreeObject`, `RecordType`, `IBenefitsSearchResult`, `FilterQuery`, `SendTxnQueryResponse`, `WhereCondition`, `PackageTypeEnum`, `StridedSliceSparseSpec`, `OutRoomPacket`, `GraphBatchedTransferAppState`, `RSSItem`, `MarkdownContributions`, `RxFormBuilder`, `BLSPubkey`, `Transaction`, `LastFmArtistInfo`, `W5`, `EmailAddress`, `UseRefetchReducerAction`, `TriggerState`, `NumberMap`, `tag.ID`, `TFlags`, `LineMessageType`, `TransactionButtonInnerProps`, `SpeakerService`, `InputParamValue`, `ByteOrder`, `Stapp`, `PreferencesCategories`, `DeleteConfigurationSetCommandInput`, `Fetcher`, `CSymbol`, `UserInfo`, `Focusable`, `MergeRequestPayload`, `APIService`, `HydrateResults`, `ReporterRpcClient`, `SortOrder`, `StudentRepository`, `ModifyDBClusterCommandInput`, `StepListener`, `HTMLCollectionOf`, `UntagResourceOutput`, `SnapshotConnection`, `IConnectToGitHubWizardContext`, `Lines.Segment`, `IdentityProviderMetadata`, `WindowType`, `IKbnUrlStateStorage`, `Config.Argv`, `SVGIconProps`, `RelationMetadata`, `BooleanInt`, `ListDeploymentStrategiesCommandInput`, `S2L2ALayer`, `requests.ListIpv6sRequest`, `MatSnackBarConfig`, `ListGroupsResponse`, `BlockHandle`, `SyncData`, `IRandomReader`, `PDFCheckBox`, `Resource`, `BasicEnumerable`, `ScryptedRuntime`, `LoggerFactory`, `ProtonApiError`, `EdaPanel`, `DatasetOpts`, `ManifestInventoryItem`, `StateOperator`, `TEX0`, `Functions`, `SignedStateReceipt`, `ConsumerParticipant`, `CpeDeviceConfigAnswer`, `IExecutionFlattedDb`, `AccessDeniedException`, `x`, `LocalVideoStreamState`, `ReactTypes.DependencyList`, `DMMF.SchemaField`, `IValueFormatter`, `MapIterator`, `DomainBounds`, `CrochetForNode`, `LogAnalyticsSourceDataFilter`, `EnumItem`, `ButtonTool`, `PieDataSet`, `_IPBRMetallicRoughness`, `CommandFn`, `AdditionalPropsMember`, `Matched`, `ITiledLayer`, `MethodName`, `WebGLTensor`, `IAssetMetadata`, `MetaProperty`, `HTMLTableRowElement`, `AuditInfo`, `StartJobCommandInput`, `CreateChannelModeratorCommandInput`, `TypeMapper`, `BoxSlider`, `GetByIndex`, `OBJLoader`, `VideoCreateResult`, `ReadStorageObjectId`, `vscode.DebugConfiguration`, `JitsiPeer`, `FungibleConditionCode`, `ScaleQuantize`, `MonthlyForecast`, `DetailedReactHTMLElement`, `ProviderOption`, `HiFiCommunicator`, `CdkRowDef`, `JumpPosition`, `InheritedProperty`, `IDataFilterConfiguration`, `SmoothedPolyline`, `OnePoleFilter`, `RevocationStatus`, `ValidatorStore`, `IModels`, `GADNativeAd`, `UserPool`, `Struct`, `AllDocsResponse`, `MessageSecurityMode`, `GrantAccessData`, `AppModel`, `RegisteredRuleset`, `ir.Block`, `ListRealtimeContactAnalysisSegmentsCommandInput`, `GenericClientConfiguration`, `Work`, `HeadBucketCommandInput`, `StreamEvent`, `Cons`, `StoreEnhancer`, `MemoizedFn`, `ReuseCustomContextMenu`, `GenericRetrier`, `ApiDef`, `Timings`, `Glue`, `ptr`, `AggregateRoot`, `IPluginPageProps`, `IpRecord`, `ClientOpts`, `AccountNetwork`, `ParseArgument`, `IpGroup`, `DashboardService`, `ISearchFeature`, `DevicesService`, `CameraHelper`, `PermissionStatus`, `SegEntry`, `SignaturePad`, `EffectAction`, `CreateDataSetCommandInput`, `DataRows`, `IWaterfallSpanOrTransaction`, `Events.exittrigger`, `CommandOutput`, `ActionCreatorFactory`, `ThemePlugin`, `RolesService`, `Mappings`, `SimpleGridRecord`, `ViewBox`, `MenuValue`, `TinaSchema`, `LexicalToken`, `GfxReadback`, `ts.Printer`, `WidgetIdTypes`, `IPolicy`, `Joi.ValidationResult`, `MyElement`, `PanService`, `TimeState`, `PayloadAction`, `UseMutationResult`, `DispatchQueue`, `ISummaryRenderer`, `GetBinaryPathsByVersionInput`, `FormDataEvent`, `ValidateKeyboardDefinitionSchemaResult`, `JsonMap`, `RibbonEmitter`, `BeachballOptions`, `SetOption`, `IngredientForm`, `SettingContext`, `CoreTypes.VisibilityType`, `ArrayServiceGetKeysByTreeNodeOptions`, `PolicyRequest`, `Inline`, `AVRExternalInterrupt`, `RippleConfig`, `Sampler3DTerm`, `fhir.Location`, `IClientOptions`, `PerformanceTiming`, `AtomicToken`, `AccountStore`, `ConnectionLocator`, `Puppeteer.Page`, `SigningCosmWasmClient`, `MapData`, `_Exporter`, `EducationalMaterial`, `KeyboardScope`, `FactoryBuilderQueryContract`, `TreeNodeViewModel`, `HydrationContext`, `CodeEditor.IToken`, `files.FullPath`, `RPiComponent`, `IAngularMyDpOptions`, `IVector3`, `ICreateData`, `IApiParameter`, `RexFile`, `ReferenceType`, `ITranslateConfig`, `MessageEntity`, `PathValue`, `Lut`, `Capability`, `InjectorType`, `Face`, `Beatmap`, `CallHierarchyItem`, `T.Task`, `IVpc`, `MarketFiltersState`, `IKeysObject`, `MemberExpression`, `requests.ListExternalNonContainerDatabasesRequest`, `FunctionComponent`, `NameNode`, `Single`, `NavSegment`, `GanacheRawExtraTx`, `FirebaseFirestore.Firestore`, `EquipmentSharingPolicy`, `ExtensionConfig`, `events.EventEmitter`, `SelectionInfo`, `OperationDefinition`, `LangiumDocument`, `MockNexus`, `BitMatrix`, `GrowStrategyMock`, `CheckResult`, `GfxRenderTarget`, `CreateUserInput`, `KeyedDeep`, `GaussianNoise`, `CGRect`, `EitherAsyncHelpers`, `TruncateQueryBuilder`, `JSDoc`, `BitcoinishTxBuildContext`, `TreeNodeState`, `UserGroupList_UserGroup`, `GetUrlFn`, `ParamModel`, `IPointUnit`, `MetricsOptions`, `Refetch`, `TargetList`, `GenericMeasure`, `FloatTerm`, `MessagePriority`, `IStringFilter`, `CustomUIClass`, `EventItem`, `ILifecycle`, `MessageTag`, `IsBound`, `DBMethod`, `MutableMatrix33`, `IteratorWithOperators`, `FlatRow`, `IGuildMemberState`, `SatRec`, `PaymentTester`, `LeafCstNode`, `EmptyParametersGatherer`, `Hotkey`, `Auction`, `child_process.SpawnSyncReturns`, `FModel.DllFuncs`, `OwnPropsOfControl`, `MemoryNavigator`, `MDCDialogAdapter`, `SalesforceFormFields`, `UiService`, `RequestBodyParserOptions`, `ModelAndWeightsConfig`, `BespokeClient`, `Functor2`, `BroadcastOptions`, `PanelOptionsEditorBuilder`, `CreateRepositoryCommandInput`, `UserInfoOidc`, `Events.collisionend`, `digitalocean.Account`, `DAL.KEY_BACKSPACE`, `GetTranscriptCommandInput`, `IHeaderProps`, `MenuPopperProps`, `SafeStyle`, `MyNode`, `GeoContext`, `DeleteAnomalyDetectorCommandInput`, `DatabaseResultSet`, `Attrs`, `IdxTree`, `IHighlight`, `School`, `PreviewData`, `MultiEmitter`, `GraphicsShowOptions`, `ScriptTags`, `VisitorFunction`, `ParsedRule`, `Models.KeyValuePair`, `EmitNode`, `CreateSecurityConfigurationCommandInput`, `ProofNode`, `FormatResult`, `AzureSubscription`, `BalanceRequest`, `StateOptions`, `zmq.Dealer`, `RegisterDto`, `MerchantMenuOrderGoodsInfo`, `AttachmentMIMEType`, `IIteratorResult`, `FeatureConfig`, `FormValueType`, `ColumnBuilder`, `AuthInfo`, `INodeHealthStateChunk`, `AccountFacebook_VarsEntry`, `XroadConf`, `Functor1`, `PendingWrite`, `IExecuteResponsePromiseData`, `PlayerProp`, `requests.ListComputeCapacityReservationInstancesRequest`, `RoverStateReturn`, `StorageOptionsChangeData`, `EnvironmentManager`, `StrapiModel`, `BaseTheme`, `HyntaxToken`, `AreaLightInfo`, `MIDIAccess`, `Invitation`, `ISessionService`, `QuizServices`, `Cookies.Cookie`, `SiteMetadata`, `SharePublicKeyOutput`, `DNode`, `DataTypesInput.Struct1Struct`, `InspectPropertyReport`, `ContractPrincipal`, `DrawerContentComponentProps`, `MarkdownDocument`, `AwsEsdkKMSInterface`, `IDataTableColumn`, `FileWrapper`, `BlockArchiveLine`, `DataTransferItem`, `RecordColumn`, `ExpansionPanel`, `IUserSettings`, `Protocol.Network.RequestWillBeSentEvent`, `Ast`, `NumberKey`, `PlotCurveTypes`, `IAmazonServerGroupCommandResult`, `PlayerStat`, `ContractCallOverrides`, `GeoPolygon`, `Scan`, `Deck`, `ICommandContext`, `GetZoneRecordsResponse`, `OrderBookOrderDTO`, `Chainable`, `BookmarkItem`, `IAppSettings`, `QueryMessage`, `PairData`, `Datastore`, `LayoutOptions`, `TaskConfigurationScope`, `AttributeServiceOptions`, `TextElementStyle`, `IMoonData`, `DescribePipelineCommandInput`, `Gateway`, `FieldFormatsGetConfigFn`, `GraphQLTagTransformContext`, `Types.PostId`, `URLTokenizer`, `ArenaSelection`, `ScaleData`, `OnlineUserType`, `SettingGroup`, `ConfirmDialogDataModel`, `CallCompositePage`, `UpdateSiteCommandInput`, `ImportCacheRecord`, `FieldValidateConfig`, `LRUMap`, `Dex`, `LeagueStore`, `ReportingInternalSetup`, `NamespacedWireCommit`, `Analytics`, `ImageEnt`, `vscode.CustomDocument`, `RowId`, `RowRenderer`, `RestConfigurationMethodWithPath`, `requests.ListPluggableDatabasesRequest`, `BNString`, `DistributionData`, `GlobalInstructionType`, `OperateBucketParams`, `CanvasTextAlign`, `SBDraft2ExpressionModel`, `MapOptions`, `ListProjectsResponse`, `Http3PrioritisedElementNode`, `TransitionableCielchColor`, `Discriminated`, `ConsCell`, `Rectangle`, `MouseAction`, `BitcoinCashSignedTransaction`, `requests.ListAlarmsStatusRequest`, `GetOperationCommandInput`, `DeleteDatabaseCommandInput`, `AccessoryTypeExecuteResponse`, `SynthBindingName`, `CustomizePanelProps`, `Component`, `DocfyResult`, `ValidatorFn`, `WordInName`, `PredicateFn`, `Unsubscribe`, `OnSubscriptionDataOptions`, `RouteView`, `VuforiaSessionData`, `GatewaySession`, `IMatrixFunc`, `BaseScope`, `BTree`, `APIResponseCallback`, `ContainerItem`, `APIChannel`, `RayPlaneCollisionResult`, `DigitalCircuitDesigner`, `NodeWallet`, `GlobalSearchResult`, `OptionsType`, `AccessKeyRepository`, `IKeyRing`, `EntityCreate`, `IntegrationClass`, `BaseParams`, `ResizeHandle`, `PropSidebarItem`, `ISecurityGroup`, `Jimp`, `JhiEventManager`, `LCImpl`, `ModelFitArgs`, `IOverlayAnimationProps`, `SSRHelpers`, 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`ActionsInTestEnum`, `DeleteWorkRequestResponse`, `BridgeMessage`, `Types.NavigatorRoute`, `SelectionTree`, `FormPropertyFactory`, `GetShardIteratorCommandInput`, `MileStoneName`, `ActionTypeConfigType`, `OnRenderAvatarCallback`, `IAsyncEnumerable`, `ParsedDateData`, `HTMLVmMenuItemElement`, `RunData`, `ImagesContract`, `MockableFunctionCallCompiler`, `IChannelServices`, `UnicodeUtils.Direction`, `TProductCategory`, `Checker`, `HostClient`, `SessionKey`, `SynchrounousResult`, `IPodFile`, `ThemedStyledProps`, `TokenSet`, `TilePathParams`, `UIntArray`, `SVGStopElement`, `IApiExternalDocumentation`, `IComponentOptions`, `VisibilityVertexRectilinear`, `DeleteCustomVerificationEmailTemplateCommandInput`, `IBlobMetadataStore`, `MarkdownPostProcessorContext`, `IncomingHttpRequest`, `ToneAudioBuffers`, `Anim`, `BigIntConstructor`, `House`, `ChannelIdExists`, `HashMapEntry`, `SagaIteration`, `WithExtends`, `VerificationInitiateContext`, `BoxConstraints`, `React.Component`, 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`ChannelStoredData`, `MockResource`, `DiezComponent`, `SyntaxErrorConstructor`, `BankAccount`, `cytoscape.NodeSingular`, `SizedBox`, `RuntimeBot`, `ImageResolution`, `DecipherCCM`, `SchematicTestRunner`, `Electron.Session`, `Controller`, `RefreshableView`, `Dialogic.InstanceEvent`, `IntrospectionOptions`, `RecordInput`, `MediatorService`, `DeepReadonly`, `TimeRangeLimit`, `ex.Input.KeyEvent`, `IContentType`, `Analyser`, `QRProvisioningInformation`, `DialogflowConversation`, `VertexDescriptor`, `RotationalSweep`, `RemoteTrackInfo`, `ParameterCondition`, `DataSourceOptions`, `IGitService`, `IConnectableBinding`, `IMemoryTable`, `PiPrimitiveProperty`, `NotificationCCReport`, `TaskIDPath`, `TypeOfExpression`, `DiskEncryptionSet`, `XPConnectService`, `O.Option`, `QueryEngineRequest`, `BootOptions`, `TerraformBaseCommandInitializer`, `SystemDomainApi`, `SnippetNode`, `Apollo.QueryHookOptions`, `GetFolderCommandInput`, `I18nMutateOpCodes`, `IGenericDeclaration`, `OfIterable`, `SpotifyWebApiJs`, `RSSSource`, `TUserAccountProvider`, `JoinBuilder`, `AuthenticationClient`, `OperationResult`, `AccessModifier`, `MigrateReset`, `TextElementBuilder`, `ImageAsset`, `CacheManagerContract`, `DescribeSessionsCommandInput`, `CompleteMultipartUploadCommandInput`, `DocumentClient.QueryInput`, `MigrationParams`, `ScrollSpiedElementGroup`, `RoastingMachine`, `StackContext`, `EditorOpenerOptions`, `PartialDeep`, `Ancestor`, `TrackedImportAs`, `PixelFormat`, `ChartDimensions`, `DateTimeModel`, `MidiValue`, `GeneratorProcess`, `QueueSendMessageResponse`, `SeriesIdentifier`, `ProcessLock`, `PrismaClientDMMF.Document`, `ClassProvider`, `PDFButton`, `FileSyntax`, `ISlickRange`, `Background`, `ProtocolConnection`, `FeatureVersion`, `CloudWatchLogs`, `ToastrManager`, `IndexLiteral`, `ChildWindowLocationProps`, `EMSSettings`, `PiValidatorDef`, `typescript.SourceFile`, `FileEvent`, `OperatorPrecedence`, `XYAxis`, `ManifestContext`, `NavigationType`, `DOn`, `State.FetchStatus`, `EntityIdentity`, `ValidatorSet`, `PagedRequestDto`, `Gadget`, `EventHandlerFn`, `ModalPage`, `PrecommitMessage`, `TestContext`, `PullRequest`, `ModeController`, `ClockHand`, `FsObj`, `CanvazNode`, `DomPortalOutlet`, `Problem`, `EntityOptions`, `AccessTokenScopeValidator`, `Scatterplot`, `Stopwatch`, `LinearlyReferencedFromToLocationProps`, `Exporter`, `ts.SyntaxKind`, `UIProps`, `ImportAliasData`, `IResolvedConfig`, `ISDK`, `ChatBaseSelectorProps`, `BrowserInfo`, `TexMatrixMode`, `DeclarationBlock`, `SecureNote`, `GrantType`, `MigrationOpenSearchClient`, `EulerRotation`, `DbSmartContract`, `CurrencyPair`, `ScanDirection`, `IndicesArray`, `Microgrammar`, `ProtocolError`, `ValidateResponse`, `CalibrationPanelProps`, `KeyboardNavigationHandler`, `MdcRadioGroup`, `DebugProtocol.EvaluateArguments`, `KeyModel`, `IAreaItemLevel`, `SfdxCommandlet`, `CachingLogViewer`, `IssueOptions`, `ITemplatizedLayout`, `MediaStreamTrack`, `VoiceFocusConfig`, `ExtendedArtifact`, `RpcRemoteProxyValue`, `AncestorDefs`, `LSA`, `CreateConnectionDTO`, `RouterReducerState`, `Decoded`, `CompilerBuildResults`, `HTMLParser`, `IReferenceType`, `RoomData`, `Fact`, `EncryptionConfiguration`, `I18NLocale`, `CollectionChangedEventArgs`, `AutoScaling`, `ProcedureRecord`, `DeleteProjectCommand`, `Omit`, `IWorker`, `DocumentInput`, `MealTicketRemoval`, `GridConfig`, `IMessageHandler`, `HttpRequestWithLabelsAndTimestampFormatCommandInput`, `IEditorMouseEvent`, `NamedItem`, `DashboardCellView`, `Cropper`, `MyMap`, `VmNetworkDetails`, `AnalysisResponse`, `TCssTemplate`, `DeleteBotCommandInput`, `ICorrelationTableEntry`, `ANC`, `DatatableVisualizationState`, `StandardContracts`, `VertexTypeStore`, `t`, `RedocNormalizedOptions`, `QueriesResults`, `TrackedMap`, `HarmonyAddress`, `FlowNarrowForPattern`, `NVMParser`, `StateBottomSheet`, `XHROptions`, `VideoProps`, `IResolvedIDs`, `DidDocumentBuilder`, `LexicalScope`, `Vin`, `ProsemirrorNode`, `TypeContent`, `Locator`, `BalmConfig`, `PerformAction`, 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`types.TracerBase`, `WorkflowOutputParameterModel`, `IEquipmentSharingPolicy`, `ElementDescriptor`, `FeedItem`, `Hapi.Request`, `MinecraftLocation`, `SetShape`, `LexoRankBucket`, `TileImageSize`, `ChokidarEvents`, `GridState`, `InfoDialogService`, `BottomNavigationTabBase`, `RafCallback`, `DoorLockLoggingCCRecordGet`, `InstanceTargetWithMetadata`, `RemoteRequest`, `ISlideObject`, `Regl`, `ClientPlugin`, `CancellablePromiseLike`, `RComment`, `NumberW`, `SvelteDocumentSnapshot`, `EntityFactory`, `WalletResult`, `AnnotationWriter`, `AnalyzerService`, `TextLine`, `LimitToPipe`, `JSONType`, `SearchScope`, `TokenIdentifier`, `CategoricalAggregate`, `DragResult`, `ILiteralExpectation`, `InteractiveConfig`, `Schedule`, `ICloudTimerList`, `SFU`, `AsyncHook`, `DeleteDatasetCommandOutput`, `TrailImage`, `MIRBody`, `IObjectWithKey`, `TabHandler`, `WebCryptoDecryptionMaterial`, `PTG`, `TemplateElement`, `LongTermRetentionPolicy`, `BatchConfig`, `OnLoadParams`, `AlainSTConfig`, `IToastCache`, `IPanesState`, `TeamModel`, `ShallowStateItem`, `CSSProperty`, `BarSeriesStyle`, `ProjectContainer`, `TypeValue`, `Movie`, `JSDocMethodBodyCtx`, `CompletionProvider`, `PageObjectConstructor`, `PluginVersionResource`, `PeerTubeServer`, `RectangleEditOptions`, `MarkerElement`, `ExprNode`, `SerializableError`, `MockConfig`, `KudosTokenFactoryService`, `ImportMap`, `ContextShape`, `MaterialVariant`, `TLE.NumberValue`, `AccountsOperationStep`, `IVirtualRepeater`, `UseMetaState`, `GenericError`, `SimpleContext`, `AwsServiceFactory`, `PairingTypes.Proposal`, `AdaptElementOrNull`, `AnalysisRequest`, `TickOptions`, `IDateUtils`, `ResultTree`, `RNNCellForTest`, `MongooseFilterQuery`, `GenericStyle`, `IServiceWizardContext`, `TrackedCooldown`, `WebDriver2`, `TargetGroupAttachment`, `MyClassWithReturnExpression`, `FactoryDatabase`, `OptionalDefaults`, `GX.TevBias`, `LockFile`, `DialogItemValue`, `FragmentMap`, `SelectorList`, `MalSymbol`, `TopologyObjectId`, `IEmployeeJobPost`, `IPropertyGridEditor`, `FasterqLineModel`, `ConvLSTM2D`, `AtToken`, `PostContentDocumentRequest`, `NgrxJsonApiStore`, `LiveDatabase`, `XPCOM.nsIJSID`, `ReactiveVar`, `FlexItemStyleProps`, `ElectricRailMovingPoint`, `MonitorRule`, `ApiRequest`, `AnnotationPointType`, `AbstractGraph`, `def.Vec2`, `LucidRow`, `SceneModel`, `MilestoneDataPoint`, `RightResolvable`, `RuleType`, `WeightsManifestConfig`, `IosDependency`, `NzDebugConfig`, `JPAExTexBlock`, `ts.NodeFactory`, `k8sutils.KubeClient`, `providers.WebProvider`, `Field.PatchResult`, `TransactResult`, `RequestType2`, `CoreOptions`, `SingleSigSpendingCondition`, `ElementProperties`, `http.RequestOptions`, `SingletonList`, `X12Interchange`, `TSESTree.Statement`, `CacheManager`, `RxSlpStream`, `PivotItem`, `VersionPolicy`, `DriveNumber`, `VcalAttendeeProperty`, `Until`, `INestApplicationContext`, `BeaconBlockHeader`, `AuthData`, `TestResolverDTO`, `FabricGatewayConnectionManager`, `UserRegisterResource`, `OutPoint`, `IFluidCodeDetails`, `ApolloMutationElement`, `DaffOrderReducerState`, `PromiseExtended`, `SWRInfiniteConfiguration`, `ConnectionDTO`, `SelectBox`, `UserToken`, `AxisOrder`, `DejaTile`, `PropMap`, `TView`, `MenuConfig`, `TkeyStoreItemType`, `ToggleCurrentlyOpened`, `BlockFile`, `BaseFullNodeDeploymentConfig`, `PouchDB.Core.Document`, `OfflineContext`, `ContractTxQueryResult`, `Printer`, `LinkProps`, `PackageInfo`, `InferenceContext`, `CodeCommit`, `SKFrame`, `CSSService`, `Bookmark`, `PayloadBundle`, `Serie`, `TypeormRawSetting`, `IGrammar`, `RelationsOpts`, `ComponentsObject`, `ThyTreeSelectNode`, `StaticLayoutProps`, `IBidirectionalIterator`, `ILicense`, `CliCommand`, `StackCollection`, `EvCallData`, `GetObjectOutput`, `NumId`, `OidcSession`, `VideoState`, `JSDocTemplateTag`, `BarcodeInfo`, `K8sResource`, `UserPoolClient`, `inversify.Container`, `Grant`, `JSONRPCClient`, `STEP_RECORDS`, `NodeMessage`, `OutputTargetDistTypes`, `Pilotwings64FSFile`, `DeleteSecurityProfileCommandInput`, `ImpressionSender`, `RefObject`, `NDArrayMath`, `DeleteTagsRequest`, `CausalTree`, `SizeLimitChecker`, `PathStartCoordinates`, `MultisigTransaction`, `HttpRequestWithLabelsCommandInput`, `XMLDocument`, `DealStage`, `SdkAudioMetadataFrame`, `ISong`, `HandleOutput`, `TxnIdString`, `FaviconOptions`, `ForeignKeySpec`, `ListField`, `P2PInternalState`, `SponsorsResponseNode`, `Trader`, `IVirtualPosition`, `CapabilitiesSwitcher`, `KanbanBoard`, `HashFunction`, `RadixAccount`, `GLsizeiptr`, `FeatureGroup`, `Finder`, `ApplicationEntity`, `EquipmentSharing`, `EntitySubject`, `CodeModel`, `IMedal`, `TargetLocation`, `ChangeSetQuery`, `IRecurringExpenseDeleteInput`, `ITemplateDiff`, `AVPlaybackStatus`, `RenderTreeFrame`, `ObjectWithType`, `CamlQuery`, `IComponentDesc`, `FrameOverTime`, `BlobLeaseAdapter`, `CallMessage`, `UserRefVO`, `FloatArray`, `INodeCredentialDescription`, `BaselineFileContent`, `IApiRequestBody`, `NSApplicator`, `VdmMapping`, `DispatchType`, `requests.ListModelDeploymentShapesRequest`, `DeclineInvitationsCommandInput`, `ContextStore`, `AnimationData`, `ErrorWidget`, `TEUopType`, `SyncCommandWithOps`, `NginxDirective`, `d.CompilerCtx`, `ToolbarChildrenProps`, `Recorded`, `LeaguePriceDetails`, `DistanceFn`, `MockStoreAction`, `TaskCommand`, `HttpUrlGenerator`, `KleisliIO`, `DecoratedModelElement`, `SecretVerificationRequest`, `DisjunctionSearchQuery`, `TagsService`, `ResourceNotFoundException`, `Ray`, `ISceneData`, `ITranslationResult`, `T17`, `jest.SnapshotSerializerPlugin`, `ProjectService`, `DataConverter`, `FileChangeType`, `ChartBase`, `HTMLVisualMediaElement`, `GenerationNum`, `HttpClientOptions`, `MouseUpAction`, `ParameterContext`, `ArtifactStore`, `LastColumnPadCalculator`, `PartialBindingWithMeta`, `JsonDocsProp`, `FieldValidation`, `J3DModelInstanceSimple`, `ScannedReference`, `HasInfrastructure`, `ShaderAssetPub`, `TableServer`, `ValueSetterParams`, `SmartStartProvisioningEntry`, `ExternalRouteDeps`, `Neo4jConfig`, `AbstractCartProxy`, `KeyValueChanges`, `_ResourceConstantSansEnergy`, `ThemePrepared`, `RPGGame`, `requests.ListFileSystemsRequest`, `ResetPasswordAccountsRequestMessage`, `TagRenderingConfigJson`, `Bamboo`, `GLBuffer`, `KeyIndexMap`, `CreateHsmCommandInput`, `DownloadTarget`, `CircuitBreaker`, `SpeedtestResult`, `IBookmarks`, `StreamResetOutgoingParam`, `Side`, `App.windows.window.IOverlay`, `DebounceSettings`, `AuxResult`, `ClassIteratorFlags`, `PotentialPartnerActions`, `CreateProjectCommandInput`, `CoreExtInfo`, `ScopeState`, `PresentationTreeNodeLoaderProps`, `ItemDescription`, `VisTypeOptions`, `PanelPlacementMethod`, `ToolRunner`, `ColumnDescription`, `IWorkerModel`, `Fp2`, `BaseOptions`, `DOMError`, `InsertNodeOptions`, `HandlerProps`, `ManagedInstance`, `FormItemProps`, `HorizontalTable`, `IFieldType`, `IUser`, `NavigationTransition`, `ODataQueryOptions`, `KeylistUpdateMessage`, `TextDocumentIdentifier`, `VisTypeAlias`, `CoursesCounter`, `VirtualRepeat`, `Violation`, `LastfmTrack`, `ModifiersArray`, `TextArea`, `IQuestion`, `DependencyTracker`, `RecordedDirInfo`, `ts.BindingName`, `THandler`, `ESLMediaRuleList`, `RtcpReceiverInfo`, `RouteOpt`, `OrExpression`, `DomainInfoCache`, `MinionsController`, `Bzl`, `ActionContext`, `Conf`, `PipeCallback`, `ThyAbstractOverlayOptions`, `RestContext`, `HitSensorType`, `PropValidators`, `BoxColliderShape`, `TextFieldProps`, `GetUpdatedConfigParams`, `Path`, `CancellationTokenRegistration`, `RotationOrder`, `ActivatedRouteStub`, `Node_Annotation`, `ALBEvent`, `GetThreadResponseType`, `AbbreviationNode`, `MIRBasicBlock`, `RegisterData`, `ISecurityToken`, `SplashScreen`, `BackendType`, `ProductAnalyticalResult`, `firestore.GetOptions`, `UserTokenPolicy`, `GroundPlane`, `CharacterMaterial`, `NOTIFICATIONS_STATUS`, `ContractCallBuilder`, `QueryType`, `BlockchainLink`, `peerconnection.DataChannel`, `TestRequestResponse`, `visuals.Coord`, `GetClientFunction`, `ConfigSetName`, `CaseDesc`, `EncryptedSavedObjectsPluginSetup`, `IDeployState`, `FederatedAdapterOpts`, `Handle`, `Flag.Parser`, `SelectionNode`, `Streak`, `PReLULayerArgs`, `AdtLock`, `RecentCompletionInfo`, `PlayerController`, `IOProps`, `InternalCase`, `SQLiteDatabase`, `Toucan`, `Colony`, `three.Mesh`, `HTMLVmPlayerElement`, `SourceStream`, `ExportSummaryFn`, `IOutputs`, `DiagnosticReporter`, `TenantId`, `FlowElement`, `ComponentType`, `RunSegment`, `GitRepo`, `requests.ListDatabasesRequest`, `QueryFunction`, `JSZip`, `UnsignedTransaction`, `KC_PrismHit`, `BuiltLogic`, `Prefetch`, `DatabaseBundle`, `IAboutService`, `InjectedAccountWithMeta`, `RoutingIntent`, `ObjectBindingOrAssignmentPattern`, `PutReportDefinitionCommandInput`, `ListSession`, `AuthHeaderProcessor`, `TestSolo`, `EDateSort`, `V1CommandLineToolModel`, `Enemy`, `DirectiveTransform`, `ProgressEvent`, `JSDocFunctionType`, `GraphQLConfig`, `TupleNode`, `PaymentOptions`, `ts.Token`, `CursorModel`, `QueueEntry`, `QueryExecutor`, `MultiSliderProps`, `CausalRepoObject`, `UserOptions`, `ShEnv`, `HistoryEvent`, `IRECProductFilter`, `IBinaryData`, `IPackageRegistryEntry`, `MockGuild`, `PartyPresenceEvent`, `TemplateAnalysis`, `ActorLightInfo`, `Member`, `protos.common.SignaturePolicy.NOutOf`, `IInboxMessage`, `Signature`, `SignDocWrapper`, `TenancyEntityOptions`, `SIOPRequestCall`, `CommonVersionsConfiguration`, `EvaluatedNode`, `ObjectFactory`, `KeyCompoundSelector`, `OctokitType`, `RemoteNodeSet`, `Reflector`, `VariantObject`, `CompressedPatch`, `GenericNack`, `PaletteDefinition`, `CliApiObject`, `SpriteStyle`, `Tournament.TournamentConfigsBase`, `TestERC20`, `CookieEchoChunk`, `CardRenderSymbol`, `QueryTreeNode`, `IDownloadFile`, `IAccountsState`, `Error`, `Feedback`, `IndexedTechnique`, `ModelShape`, `SecurityGroupRulePorts`, `TDest`, `MeetingSessionConfiguration`, `AParentInterface`, `Extensions`, `GQLQuery`, `OverlayRef`, `System_String`, `IField`, `Doc`, `Dimensions`, `NestedStructuresCommandInput`, `PointerAbstraction`, `ScriptType`, `UpdateIPSetCommandInput`, `Promisify`, `ModelArtifactsInfo`, `MapObjectAdapterParams`, `DiscoverInputSchemaCommandInput`, `SheetContainer`, `CannonColliderShape`, `Mnemonic`, `OnConflictBuilder`, `Credentials`, `TextMeasure`, `MapComponent`, `CloudDevice`, `Balance`, `DownloadRequest`, `CombatPlayerComponent`, `DebugEditorModel`, `StatelessComponent`, `MicroframeworkLoader`, `CommitIdentity`, `IInfectionOptions`, `HydrateAnchorElement`, `TQuery`, `AnimationArgs`, `TEnumValue`, `DebugProtocol.PauseArguments`, `InterpolationFunction`, `PedComponent`, `THREE.Vector2`, `LintOptions`, `DescribeGroupCommandInput`, `DirectiveDefinitionNode`, `NodePhase`, `UserSettingsService`, `BlockedHit`, `IRootAction`, `EnvId`, `Signed`, `PictureGroup`, `DeleteRegistryCommandInput`, `AngularHttpError`, `SymbolMap`, `VmixConfiguration`, `MutationPayload`, `ChatType`, `BezierPoint`, `CustomerVm`, `MarkOperation`, `SdkStreamDescriptor`, `IDataFilterValueInternal`, `FMAT_RenderInfo`, `DestinationOptions`, `PermissionMetadata`, `RARCDir`, `NamingStrategy`, `TestFixture`, `FeedDict`, `AudioConfig`, `ArgumentDefinition`, `Anime`, `CountOptions`, `SerializedAction`, `BootstrappedSingleSpaAngularOptions`, `CallappConfig`, `SnippetsProvider`, `TrackingService`, `BoxrecBasic`, `CreateAssetCommandInput`, `PadplusRoomPayload`, `DispatchedPayload`, `IFormGroup`, `IDeliveryClientConfig`, `OscillatorType`, `Root`, `TimeoutOptions`, `IntersectionObserverEntry`, `StreamInterface`, `OptionLike`, `Character`, `Document`, `FrameNode`, `ConflictingNamesToUnusedNames`, `StackingContext`, `ResponseStream`, `TreeExtNode`, `JoinType`, `ChannelTypeEnum`, `RouteQuote`, `ListJobShapesRequest`, `CurriedFunction3`, `SystemInfo`, `SessionState`, `DCons`, `CheckConflictsParams`, `HttpClientService`, `USSTree`, `Texture`, `THREE.Intersection`, `ICachedResourceMetadata`, `EmptyIterable`, `RegistryService`, `DetachedSequenceId`, `VKeyedCollection`, `TitleTagService`, `MomentumOptimizer`, `ReplayDataMediator`, `BrowserType`, `FlatIndex`, `RTCCertificate`, `TimerHandler`, `BaseCoin`, `RegisterServerOptions`, `IndexRangeScanStep`, `RedundancyConfig`, `SecurityProviders`, `NSMutableArray`, `ModuleReference`, `ApiHttpService`, `CalendarState`, `IDataPerList`, `MessageImage`, `TextObject`, `Gui.VPanel`, `Maybe`, `MathjsBigNumber`, `GeoPoint`, `ParamAssignmentInfo`, `IMode`, `VdmProperty`, `ModuleOptionsWithValidateTrue`, `ToJsonProperties`, `Dynamics`, `AbbreviationInfo`, `RichTextComponents`, `NavigableSet`, `MatrixClient`, `JRPCRequest`, `IDanmaTrackInfo`, `ExpressionAstFunction`, `CheckpointWithHex`, `SetType`, `AsyncActionProcessingOptions`, `GLRenderer`, `ApiGatewayLambdaEvent`, `ContainerBinding`, `INodeStatus`, `MutationResult`, `ChatServerConnection`, `NavigationContainerRef`, `UniqueID`, `IDBDatabase`, `TsmOptions`, `d.OutputTargetHydrate`, `SwUpdate`, `AxiosHttpClient`, `float64`, `Community`, `VerificationContext`, `RX.Types.SyntheticEvent`, `SortValue`, `ItemShape`, `ProjectIdentifier`, `StartTagToken`, `HTMLCollection`, `CanaryMetricConfig`, `IUserAchievement`, `RecordRow`, `HoverFeedbackAction`, `CommonFile`, `TestHelpers`, `TargetedAnimation`, `MPRandGauss`, `Lease`, `OrderSide`, `VirtualEndpoint`, `IPaginationOptions`, `ClusterRole`, `WaitStrategy`, `SessionCache`, `StorageModuleAsyncOptions`, `EmbeddableFactoryDefinition`, `IncorrectFieldTypes`, `PageDTO`, `FFTProgram`, `IControlData`, `ChunkRange`, `SavedObjectsBulkUpdateOptions`, `JsonWebSignatureToken`, `ArgVal`, `ResponderModeTypes`, `GraphicsGrouping`, `ImageSegmenterOptions`, `TodosST`, `ListProtectedResourcesCommandInput`, `ChatContext`, `TypeEmitOptions`, `AstParsingResult`, `IKeyboardDefinitionDocument`, `SceneRenderContext`, `BackgroundStyle`, `MinifyOptions`, `RegistryContract`, `PerfTools`, `HTLC`, `DirtiableElement`, `RenderTag`, `StringWithEscapedBlocks`, `DeleteHsmCommandInput`, `TrophySubmission`, `apid.AddRuleOption`, `ListKeysCommandInput`, `requests.ListProjectsRequest`, `ColorSchemaOptionsProps`, `SignedCanonicalOrder`, `vscode.DecorationRenderOptions`, `DatatableArgs`, `AnalyzeResult`, `SubExpr`, `ConcreteSourceProvider`, `PortProvider`, `ConfirmDialogService`, `DistanceQueryInterface`, `NumberParams`, `Mdast.Root`, `ResponseReaction`, `ExportRecord`, `SearchExpression`, `HowToPay`, `instantiation.IConstructorSignature5`, `Templateable`, `DSpaceSerializer`, `Propagation`, `UIBrewStorage`, `NumberConstructor`, `SuspenseListRegistryItem`, `Node_Const`, `ScopedProps`, `EncryptedData`, `GfxRenderInst`, `DebugBreakpoint`, `InventoryInteractionService`, `HorizontalPlacement`, `SubscriptionEntry`, `CorporationCard`, `Fraction`, `DtlsClient`, `ElevationProvider`, `ImageStretchType`, `MemoryDebe`, `FunctionConstructor`, `HierarchyFacts`, `ElTableStoreStates`, `server.DataLimit`, `GlobalReplicationConfig`, `InnerClientState`, `ISuggestion`, `y`, `IKibanaMigrator`, `TransactionView`, `JobCommand`, `StepFunction`, `ListFirewallPoliciesCommandInput`, `TimelineItem`, `WebGLExtensionEnum`, `TestFn`, `DejaSelectComponent`, `TestDeployRetrieve`, `LookupSorter`, `ChannelList`, `GauzyCloudService`, `ExpressionRegexBuilder`, `IFluidDataStoreContext`, `SelectorMap`, `SetDefaultPolicyVersionCommandInput`, `ReleaseChannel`, `ApiClientRequest`, `IWebhookData`, `MatMenuItem`, `GenerativeToken`, `Submitter`, `WorkspaceSummary`, `EC2Client`, `Kernel.IKernelConnection`, `FocusKeyManager`, `RootHex`, `React.HTMLProps`, `DebugProtocol.StepInArguments`, `ForwardingSchema`, `SafeSelector`, `SceneGraphNode`, `ScratchOrg`, `MongoClientOptions`, `https.ServerOptions`, `AbiEntry`, `ValueMetadataAny`, `AuthorizationNotFoundFault`, `FilterDescriptor`, `SignedMultiSigTokenTransferOptions`, `HandlerParamOptions`, `UserTokenAccountMap`, `Compression`, `ModOutput`, `LogsConfiguration`, `pe`, `BuildPipelineParams`, `TypeAST`, `ResourceKeyList`, `webpack.loader.LoaderContext`, `ZimCreator`, `NotFoundError`, `requests.ListImagesRequest`, `EnergyAmounts`, `search.SearchState`, `VisualizationsPlugin`, `CharacterClassElement`, `CommandBase`, `DeviceSize`, `ColorFilter`, `UpdateFolderCommandInput`, `ts.JSDocTag`, `ISortOption`, `EventToAsyncUnHandler`, `SuggestionWithDetails`, `IClaimData`, `ShValue`, `DisableOrganizationAdminAccountCommandInput`, `InlineResolveOptions`, `MetadataPackageVersion`, `WeakEvent`, `ParsedSchema`, `URLSearchParamsInit`, `Trap`, `OctoServerConnectionDetails`, `VisSavedObject`, `ArticleType`, `SendMessageData`, `ServiceDefinitionPaths`, `PackageListItem`, `DomainDeliverabilityTrackingOption`, `Progress`, `ListInvitationsCommandInput`, `WhereBuilder`, `CreateAccountsValidationResult`, `SpeechSynthesisEvent`, `TestLogger`, `IsolatedAction`, `ColumnDifference`, `PluginSettings`, `TreeviewNode`, `jest.MatcherUtils`, `CSSOutput`, `Regions`, `PullRequestState`, `XMLHttpRequestResponseType`, `PointS`, `TransferArgs`, `ColumnSubscription`, `CheckPrivilegesOptions`, `CombinedDataTransformer`, `firestore.DocumentSnapshot`, `StackParams`, `Json.Token`, `IGetUserInvitationOptions`, `MockCSSRule`, `ProseNodeMap`, `t.JSXElement`, `ExpansionModule`, `GlimmerComponent`, `EditHistoryCommit`, `UnsupportedSyntax`, `StandardMaterial`, `HttpOptions`, `DescribeOrganizationConfigurationCommandInput`, `GrpcEventEmitter`, `AuthAction`, `EventObject`, `PersistentCharacter`, `CreateSnapshotCommandInput`, `BigLRUMap`, `RootState`, `ExplorerState`, `TimeTicksInfoObject`, `AwaitNode`, `___JSE_XLSX___Node`, `SanityTestData`, `OnScroll`, `MenuService`, `ContentActionRef`, `BaseSettings`, `LazyLight`, `SchematicContext`, `EqualityComparer`, `CreateOptions`, `PluginInsertActionPayload`, `PaymentDataRequest`, `IDiff`, `AnimationTransitionMetadata`, `Actors.Actor`, `AsyncCommandWithOps`, `PipelineVersion`, `ZoneNode`, `INativeTagMap`, `ISQLScriptSegment`, `InsertBuilder`, `DaffStateError`, `BoundsOffsets`, `TestElementDrivesElement`, `FlexStyleProps`, `ACCategory`, `Oas3Rule`, `ContextAwareLogger`, `RemoteStoreRoom`, `DescribeAddonCommandInput`, `Sidekick`, `TToken`, `CollectionViewLayout`, `SequentialArgs`, `ContextTransformer`, `TestChannelArgs`, `UITraitCollection`, `ProxyConfig`, `TFLiteDataType`, `Stereotype`, `ObsoleteOptions`, `CreateDomainNameCommandInput`, `GoConditionalMove`, `vscode.Hover`, `CookieSettingsProps`, `PDFState`, `ExecutionPureTransitions`, `OrderStruct`, `TSQueryOptions`, `QueryResultRowTypeSummary`, `NodeURL.URL`, `SearchState`, `DataTableService`, `ShardingInstance`, `AaiMessage`, `DetailedStackParameter`, `TransactionEvent`, `NuxtConfig`, `PieVisualizationState`, `ServiceCollection`, `Statements`, `PluginConstructor`, `TSigner`, `CreateUserService`, `GoogleUser`, `PadchatContactPayload`, `DiscoveredClass`, `immutable.Set`, `VariablePart`, `CallHandler`, `ReducerWithInitialState`, `VideoStreamRenderer`, `Linters`, `ContentProvider`, `JStretch`, `IHookCallbackContext`, `RebootBrokerCommandInput`, `TitleTagData`, `GroupAction`, `AnimatorDuration`, `ProgramOptionsList`, `ParserFnWithCtx`, `AnimationProps`, `EasingFunction`, `UsageInfoHoverInfo`, `TypingIndicatorStylesProps`, `KarnaughMapProps`, `ConnectionHandler`, `EvictReasonType`, `LayerService`, `InputBit`, `RightHandSideEntry`, `ScopedStateManager`, `SVGRect`, `CesiumProperties`, `ListFormat`, `ClientGoalState`, `Keyboard`, `SimpleTest`, `NumberInfo`, `PlatformUtilsService`, `W3`, `HandlerOptions`, `SupportCode`, `SerializedEntityNameAsExpression`, `AST.Root`, `ObserverNameHolder`, `TopologyService`, `DraggedWidgetManagerProps`, `Psbt`, `InspectorOptions`, `TelemetryServiceConstructor`, `MetadataMap`, `InferTypeNode`, `IDocumentMergeConflict`, `ProjectViewModel`, `Basket`, `ValueGetter`, `VSCServerManagerBase`, `TFields`, `ImportDefaultInterface`, `IntersectionType`, `GaiaHubConfig`, `SQLResultSet`, `NavigationDirection`, `ListServicesRequest`, `HdBitcoinPayments`, `MetricAggType`, `GlossyMaterial`, `ComponentTypeOrTemplateRef`, `ComponentHandler`, `BaselineEvaluation`, `TRPCLink`, `IssueWithStatus`, `VirtualContestItem`, `XmlEmptyMapsCommandInput`, `WordcloudSeries.WordcloudFieldObject`, `IGameData`, `Commutator`, `CheckedObserver`, `Team`, `Provide`, `PuppeteerScreenshotOptions`, `OperatingSystem.Windows`, `StyleHelpers.QuoteInput`, `UserBuilder`, `NavigationTree`, `ChartConfiguration`, `DrawIOUMLDiagram`, `BlockchainGatewayExplorerProvider`, `d.ComponentConstructorWatchers`, `UserStatsState`, `TransactionFunction`, `ReactDataGridFilter`, `OverlayConfig`, `XPCOM.nsXPCComponents_Interfaces`, `AttributionsToResources`, `MessageType`, `IMongoResource`, `StoreConfig`, `IListFunctionOptions`, `NodeParameterValue`, `PersonState`, `project.Project`, `RouteHandler`, `IDs`, `OrderByNode`, `dKy_tevstr_c`, `MentionInputorElement`, `IChannelManager`, `compare`, `SettingDictionary`, `IColumnIndices`, `CSharpFieldType`, `Random`, `GetMetaDataFunction`, `RosettaOperation`, `TinderLike.Props`, `ObjectASTNode`, `ApiViewerTab`, `GraphQLSchemaNormalizedConfig`, `PreferenceInspection`, `BooleanValidator`, `ASStatement`, `AlertWrapperProps`, `PureTransitions`, `FooterProps`, `SpectatorHost`, `AtomTweeningNumberElement`, `IdentityProviderConfig`, `IonContent`, `ClipPrimitive`, `requests.ListManagedInstanceGroupsRequest`, `PlaneType`, `PAT0_TexData`, `FileCache`, `EngineMiddleware`, `FocusOrigin`, `void`, `BlokContainer`, `InternalPropertyObserver`, `LanguageOptions`, `Recommendation`, `PartitionFilter`, `CreateEmailIdentityCommandInput`, `InsightObject`, `Pong`, `MapMarker`, `GlobalState`, `SubPredArg`, `QueryFn`, `GraphQLFieldResolver`, `VisualizeAppProps`, `LoadMetricInformation`, `NavigatorRoute`, `NotebookEvents`, `SubnetAlreadyInUse`, `DiscordMockContext`, `DropHandler`, `RuleOptions`, `SolutionStackProps`, `FlashArguments`, `MinAdjacencyListArray`, `_NotificationConfig`, `IDocumentMessage`, `EnergyMap`, `ILanguageSyntax`, `GravityType`, `ExtraFieldDetail`, `ContainerAdapterClient`, `SMA`, `MDCProgressView`, `StubXhr`, `Var`, `PlaintextMessage`, `HandleResult`, `PrepareEnvVariablesProps`, `GCPAuthOptions`, `CodeGeneratorContext`, `ConnDataType`, `UpptimeConfig`, `CallExpression`, `ControllerMetadata`, `CursorModelConfig`, `X509CertificateSupplier`, `ComposeSubscriber`, `ValidationRule`, `DocumentSnapshotCallback`, `MyAppProps`, `CloseReason`, `promise.Promise`, `AppNotificationManager`, `ToneBufferSource`, `TransitionOptions`, `ProgressAtDayModel`, `LevelActionTypes`, `StateSelectors`, `IDeployContext`, `AlignSelf`, `EntityDeserializer`, `PromiseRejectionEvent`, `QueryProviderAuditorRequest`, `NetworkData`, `Assets`, `QualifiedId`, `BoxProps`, `FrameBuffer`, `Shortcut`, `AngleSweep`, `ResourceTypes`, `SearchQueryBuilder`, `Styler`, `FooService`, `NodeWithId`, `TxType`, `NetworkProvider`, `V1APIService`, `Fn4`, `ModalsState`, `Events.pointerleave`, `WorkRequestResource`, `TransitionInstruction`, `PackageManagerType`, `DeleteModelCommandInput`, `TimelineHeaderWrapper`, `EcommerceItem`, `FindSelector`, `Necktie`, `NameOrCtorDef`, `ICoverageFile`, `IRemindersGetByContactState`, `RatePretty`, `React.ClipboardEvent`, `CategoryRendererItem`, `GitStatus`, `ExtensionItem`, `AureliaProgram`, `TestKeyring`, `SupportedService`, `TypeSignature`, `GetInstanceCommandInput`, `CallbackFunc`, `ChartSeries`, `WebrtcProvider`, `ERC721TokenDetailed`, `TradingPair`, `CentralSceneCCNotification`, `InstanceBlockDeviceMapping`, `RemoveEventListener`, `DataArray`, `JoinCandidateBuilder`, `StablePlace`, `IReportEmbedConfiguration`, `Proppy`, `Dirigibles`, `ByteSize`, `DebugProtocol.VariablesArguments`, `IBirthCompositionBody`, `ISharedFunction`, `PreventCheck`, `ConnectionInvitationMessage`, `ConfigService`, `ImmutableListing`, `AnyCoinCode`, `ProppyFactory`, `EthereumProvider`, `StackFrame`, `ConfigureOptions`, `BlockPath`, `AClass`, `cheerio.Root`, `MatOpN`, `GeneralState`, `TElementNode`, `CollectorOptions`, `WebGLActiveInfo`, `MakefileConfiguration`, `PickDeepObj`, `vscode.ConfigurationScope`, `InterfaceSymbol`, `GetDeliverabilityTestReportCommandInput`, `RlpSerializable`, `VisualizePluginStartDependencies`, `requests.CreateCertificateRequest`, `GfxProgram`, `IMilestone`, `TransferBatch`, `KeywordType`, `AnyRecord`, `TrainingZone`, `SidenavContextType`, `DataStore`, `GetGroupRequest`, `EarlyReturnType`, `redis.RedisClient`, `mb.IRecording`, `PropertyCategoryLabelFilterer`, `Duplex`, `LogStatement`, `DictionaryPlugin`, `RemoteFile`, `ConnectionWorkflow`, `PiScopeDef`, `DataSourceType`, `ChartJSService`, `SerializedPlayer`, `TransformedPoint`, `ImageHandler`, `XhrCompleteContext`, `MIMEType`, `LocationLink`, `WsConnection`, `Separate`, `CommandHandler`, `IGatewayRoom`, `TabStripItem`, `ProductTypeService`, `TreeElement`, `PianoNote`, `ISiteScript`, `IIterator`, `Agenda`, `IConnected`, `StkTruToken`, `GreetingWithErrorsCommandInput`, `MyOtherObject`, `FcUuidAuth`, `DropIndexNode`, `CandidateCriterionsRating`, `ts.InterfaceType`, `GeometryStreamProps`, `sdk.SpeechSynthesizer`, `IRectangle`, `M`, `DataContext`, `HTMLOptGroupElement`, `ComputedPropertyName`, `IConnector`, `ApplyChangeSetOptions`, `Auth0UserProfile`, `EventState`, `Box3Like`, `SinonSpy`, `TokenModel`, `ExpressionRendererEvent`, `FieldNameList`, `TestControllerPoint`, `RepositoryFile`, `MethodNode`, `TextMatchOptions`, `IOrderCreationArgs`, `AppWithCounterAction`, `AST.Regex`, `Strapi`, `FourSlashFile`, `ExploreState`, `BIP85Child`, `ListSchemaVersionsCommandInput`, `ArtifactSizes`, `MeshLambertMaterial`, `BigNum`, `PathResolverResult`, `Types.RouteCallback`, `LoginInfo`, `TransferValidatorStakeV1`, `Select`, `ColumnSeriesOptions`, `ChannelWrapper`, `ParseEvent`, `QueryBarTopRowProps`, `JSONSchemaType`, `KeyPairKeyObjectResult`, `NzI18nService`, `IDBPDatabase`, `MessageWriter`, `WsDialogService`, `RouteRecord`, `LocalStorageKeys`, `ElectronService`, `ListInputsCommandInput`, `FieldOptions`, `IndexedAccessType`, `StyleInfo`, `ExpRes`, `MessageResolvable`, `Curry`, `IStore`, `Prop`, `ProblemFileType`, `Equals`, `requests.ListWafBlockedRequestsRequest`, `Services.UIHelper`, `TypedBinOp`, `ClientCapabilities`, `IterableReadable`, `HexString`, `ApiProps`, `SExpressionRepl`, `EdgeCollider`, `Picture`, `Reject`, `ParentFiber`, `ENR`, `i64`, `IMapSettings`, `InputThemeConfig`, `AssemblyOption`, `Fn`, `MentionSuggestionsProps`, `ReactWrapper`, `XorShift`, `Rule.RuleContext`, `DalBoard`, `SendManyOptions`, `PageState`, `GitRemote`, `RawDraftContentState`, `InjectedMetadataSetup`, `egret.MovieClip`, `SbbIconOptions`, `ServiceUnavailableException`, `NodeWorkerMain`, `SocialError`, `CheckoutPaymentPage`, `ParentNode`, `Resume`, `FunctionFlags`, `Send`, `TextureProvider`, `RequesterBlockMap`, `GfxImplP_GL`, `LocalAccount`, `IMouseZone`, `HandlerMap`, `AssetKey`, `TemplateScope`, `Booking`, `ITdDataTableColumn`, `TestComponentProps`, `XAxisProps`, `OrganizationRecurringExpenseService`, `Parameter`, `SettingsStateType`, `STStyle`, `Primitives.Value`, `DBDriverResource`, `SchemaObjCxt`, `ICompiledFunctionCall`, `IPluginContext`, `MOCK_TYPE`, `RegExpCompat`, `DaffMagentoCartTransformer`, `MethodSignature`, `RouteDefinitionParams`, `SearchBoxProps`, `IHTTPRequest`, `IAction`, `IResultSetColumnKey`, `MapRewardNode`, `ExportedNamePath`, `IRemoteUser`, `LanguageDetectorAsyncModule`, `SKShadowItem`, `ServiceEntitlementRegistrationStatus`, `InitWindowProps`, `BinaryOpNode`, `UsersRepository`, `CompletrSettings`, `AsyncResultCallback`, `SfdxCliActionResultDetail`, `UiStateStorageStub`, `SortablePolygon`, `InitChunk`, `TwistyPlayer`, `BaseKey`, `SChildElement`, `GoogleMap`, `SubjectsBounds`, `IMergeTreeDeltaOpArgs`, `Variation`, `HttpMiddlewareEffect`, `Validator`, `IFormatterParserFn`, `ProcessOptions`, `SavedEncounter`, `MapViewFeature`, `TokenObject`, `InteractionService`, `Apollo`, `kifp_element`, `AggregationMap`, `ObjectDescriptor`, `SimpleObject`, `NotificationItem`, `RegistryKey`, `DatePrecision`, `EffectSystem`, `CreateBranchCommandInput`, `HdErc20Payments`, `IMusicInfo`, `ServerlessRecord`, `SignedCredential`, `Aabb3`, `ProjectStatus`, `PointerInfo`, `ProviderSettings`, `PingMessage`, `HTMLRewriter`, `SimpleRNNCellLayerArgs`, `GDQBreakBidManyOptionElement`, `RecordsGraph`, `TypeInferences`, `protos.google.iam.v1.ISetIamPolicyRequest`, `SearchPattern`, `RendererProps`, `ApiService`, `AuthContextData`, `DSVParsedArray`, `DescribeDBClusterSnapshotsCommandInput`, `HTMLScTooltipRowElement`, `TestConfigData`, `DidConfig`, `ContractKit`, `IModLoaderAPI`, `ILookUpArray`, `ParsedTypeDetailed`, `TxSummary`, `NewPackagePolicy`, `ContentLayoutProps`, `AngularExternalTemplate`, `IObjectInspector`, `ExpressionExecOptions`, `DoubleLinkKVStore`, `ts.ESMap`, `StyleResource`, `GroupBySpec`, `TargetElement`, `ActionSheetOptions`, `IterableProtocol`, `TestBadgeComponent`, `NpmPackageManager`, `V1Container`, `TypedNode`, `HasTaskState`, `UserConfig`, `CollectBBox`, `Decomposers`, `ItemSocket`, `IndyProof`, `ChannelPickerItemState`, `ProviderLibrary`, `MDCTabBarAdapter`, `Plugin_2`, `MessageTypeMapEntry`, `ModuleRpcServer.ServiceHandlerFor`, `ContainerRegistryEvent`, `TxGeneratingFunctionOptions`, `ConfigAccount`, `DeleteEventSubscriptionCommandInput`, `Inherits`, `UnicodeRangeTable`, `BasicGraphPattern`, `ResourceComputationType`, `SubmissionStatus`, `PureEffect`, `XPCOM.nsIComponentRegistrar`, `WebPhoneUserAgent`, `KeyframeNodeOwner`, `TriggerEvent`, `ValidateDeviceOwnershipQuery`, `ScrollIntoViewOptions`, `requests.ListPublishersRequest`, `SchemaValidator`, `UnresolvedLogs`, `HTMLWalkState`, `MinMaxSurroundAttestation`, `NodeJS.ReadableStream`, `DelonLocaleService`, `SubjectService`, `TSeed`, `NodeSelector`, `NewOrganizationDTO`, `RuleFixer`, `SyncServer`, `DAL.DEVICE_ID_BUTTON_RESET`, `Accessibility.PointComposition`, `IActorRdfDereferenceOutput`, `BroadcastTx`, `InterventionTipsStatuses.StatusIds`, `ArrayServiceTreeToArrOptions`, `Test2`, `QBFilterQuery`, `MeshLODLevel`, `BaseApplication`, `FinalEventData`, `AppEntry`, `FetchResolveOptions`, `ItemModel`, `ThumbnailModel`, `PIXI.Container`, `StreamingFeeState`, `ConfigurableStartEnd`, `MomentInterval`, `PutFeedbackCommandInput`, `NonReactive`, `TutorialDirectoryHeaderLinkComponent`, `GitHubRef`, `Bootstrap`, `EventAggregator`, `Shared`, `Config.DefaultOptions`, `TPDISearchParams`, `XmlMetadata`, `d.HostRuleHeader`, `DeleteIdentityProviderCommandInput`, `CountItem`, `ClipboardWatcher`, `ClientStateType`, `CreateAccountStatus`, `GunValue`, `MicrophoneConfig`, `Facsimile`, `BeatmapDifficulty`, `UpdateAuthorizerCommandInput`, `SourceFuncArgs`, `NgEssentialsOptions`, `ParquetCodec`, `fused.Activation`, `TemplateGroup`, `SimpleCharacter`, `CeramicApi`, `SelectorQuery`, `UseInfiniteQueryResult`, `BSTProxy`, `Pipe`, `IRunConfig`, `BaseInterface`, `ILeg`, `InterpolationConfig`, `ConfigEntity`, `CurrentProfile`, `Callout`, `GenesisCommit`, `ISkin`, `UserClaims`, `ISizes`, `Tape`, `MeterScale`, `CommandError`, `os.NetworkInterfaceInfo`, `TradeSearchHttpQuery`, `JwtPayload`, `TaggedTemplateLiteralInvocation`, `PageChangeEvent`, `VisiteRepartitionType`, `Genesis`, `T.NodeRef`, `d.HydrateResults`, `PDFString`, `region`, `StoredEvent`, `CSharpInterface`, `HTMLOptions`, `types.Position`, `GX.WrapMode`, `IPartyMember`, `IOpenRepositoryFromURLAction`, `IVariantCreateInput`, `VirtualFile`, `WaveformHD`, `IntervalNode`, `FSA`, `BlockchainPackageExplorerProvider`, `DeleteManyInput`, `Decl`, `PointGraphicsOptions`, `SVGAElement`, `ICompiledRules`, `SymOpts`, `AppsState`, `SendEmailOptions`, `HookHandlerDoneFunction`, `AbstractModel`, `ControllerType`, `runtime.HTTPHeaders`, `GithubAuthProvider`, `WalletContractService`, `SongState`, `estypes.SearchRequest`, `Vol`, `InMemoryUser`, `DescribePackageVersionCommandInput`, `MarkdownFile`, `Models.Side`, `Subject`, `Y`, `DomainEventMapping`, `SearchResultsAlbum`, `SecurityManager2`, `SqrlEntity`, `LobbyOverlayProps`, `NanoID`, `RotationType`, `ShareStoreMap`, `requests.ListInstanceConsoleConnectionsRequest`, `CapsuleColliderShape`, `UpdateSpellUsableEvent`, `TSESTree.MemberExpression`, `ClassLike`, `HeroService`, `ICollections`, `lf.Database`, `PublicSymbolMap`, `PrimaryTableCol`, `FormatOptions`, `MultiMult`, `ASModule`, `ElementHandle`, `TargetDetectorRecipeDetectorRule`, `RenderingContext2D`, `JAddOn`, `Thickness`, `Prando`, `MockContract`, `LocalOptions`, `TableType`, `GraphGroup`, `Geometry`, `android.app.Activity`, `ESLintClass`, `CSS`, `CompositeBrick`, `ReportFunnel`, `BrowserContextOptions`, `SanityTestNode`, `JSONPath`, `CompressedImage`, `AppealChallengeData`, `ListAppInstancesCommandInput`, `RstatementContext`, `ModelEvaluateArgs`, `ID3v2MajorVersion`, `ISolutionEntry`, `ServerModel`, `Linter`, `IntVoteInterfaceWrapper`, `ApplicationState`, `ACLType`, `T15`, `KeyShare`, `CoapServer`, `UsePaginatedQueryState`, `AtomDataHandler`, `MetricIndicator`, `ApplicationOptions`, `OptionNameMap`, `vscode.QuickPickOptions`, `IsSpeakingChangedListener`, `ITile`, `DType`, `TSPosition`, `IProjectCommand`, `IStszAtom`, `StructureLab`, `RowViewModel`, `View`, `MessageSerializer`, `FindingCriteria`, `CommonContext`, `Models.DiagnosticsSettings`, `Comparison`, `ScmResourceGroup`, `SubContext`, `ts2json.DocEntry`, `HsEndpoint`, `GlyphInfo`, `GetInvitationsCountCommandInput`, `Vorgangsposition`, `JRes`, `ConnectorType`, `LayoutType`, `Handlebars.HelperOptions`, `TimeFilterServiceDependencies`, `BaseNavTree`, `VimMode`, `DebugAction`, `StreamSelection`, `SpacesManager`, `HttpChannelWrapper`, `ExpressionFunctionClog`, `EmaSubscription`, `HttpLink`, `requests.ListJobRunsRequest`, `TileCoords3D`, `Ulong_numberContext`, `MagicRPCError`, `Transformable`, `FactoryProvider`, `PredicateNode`, `IButtonClickEvent`, `PushRPC`, `Augur`, `IPlatform`, `CssFile`, `KeyPairOptions`, `V1ClusterRole`, `PackageJsonInfo`, `KeyboardKeyWrapper`, `Build`, `requests.ListSecretsRequest`, `DataPublicPlugin`, `SignedTransaction`, `IdOrNull`, `FlattenedXmlMapWithXmlNamespaceCommandInput`, `DescribeAppCommandInput`, `SVGRectElement`, `requests.ListLocalPeeringGatewaysRequest`, `SubMiddlewareApi`, `OurOptions`, `FunctionDesc`, `GPUSampler`, `ReadonlyVec`, `MonitorState`, `ILineInfo`, `GetPolicyVersionCommandInput`, `LogicAppInfo`, `TransmartRelationConstraint`, `requests.ListNotebookSessionsRequest`, `DataModels.Correlations.ProcessInstance`, `AjaxAppenderConfiguration`, `SshSession`, `GitQuickPickItem`, `DataViewColumn`, `LineSelection`, `ErrorMessageTracker`, `DesktopCapturerSource`, `StoreActions`, `MockMessageClump`, `Constraint`, `AggregationCursor`, `ShellWindow`, `LITestService`, `UpdateEntrypoint`, `PDFPage`, `PubScript`, `DbAbstractionLayer`, `CollectionTypes`, `BaseAsset`, `MenuTree`, `requests.ListNodePoolsRequest`, `ITestRunnerOptions`, `MixinTable`, `LocaleData`, `InstancedBufferGeometry`, `GuardFunction`, `Listr`, `ImageEdits`, `ChunkList`, `FlexDirection`, `RollupBlock`, `requests.ListSteeringPoliciesRequest`, `GeneralName`, `TexGen`, `angu.Context`, `ClassDescriptor`, `AnyIterable`, `FlexboxLayout`, `IJSONSegment`, `GameDataStateRecord`, `ActionReducer`, `TNATxn`, `ComponentWithUse`, `MonitoringStats`, `d.BuildResultsComponentGraph`, `PropertyExt`, `DeprecationsFactory`, `Collector`, `TreemapNode`, `DataExtremesObject`, `PointOctant`, `SimpleRNNLayerArgs`, `AsyncPriorityQueue`, `TScope`, `RequestType`, `DaffOrderFactory`, `IScreenshot`, `AppMenu`, `ISourceOptions`, `React.Ref`, `NSNotification`, `PartyJoinRequest`, `BundleManager`, `CompilerError`, `JapaneseDate`, `JPAResourceData`, `enet.NetData`, `ReplyRequest`, `BinaryTargetsEnvValue`, `STDeclaration`, `MatchingLogic`, `SegmentGroup`, `LengthType`, `ProcessEnv`, `social.UserData`, `PrismaPromise`, `TLE.TleParseResult`, `ProjectOptions`, `TickerFuncItem`, `MediaSlot`, `_.Dictionary`, `ListIdentitiesCommandInput`, `VKFParamMap`, `HookTypes`, `StyleSheetList`, `EditorPackage`, `ClrDatagridStateInterface`, `RoutableTileWay`, `DockerContainerProps`, `TypeFeatures`, `SendCommandResult`, `DashboardPanelState`, `PopupModel`, `LwaServiceClient`, `GenericDefault`, `EndResult`, `DynamoDB.QueryInput`, `EntityActionOptions`, `Bundle`, `CreateChildSummarizerNodeParam`, `apiKeysObject`, `UILayoutGuide`, `GetMapParams`, `KeyboardShallowWrapper`, `TypeReconstituter`, `AppContextData`, `ConfigurationData`, `ListChannelsCommandOutput`, `ExpressionsServiceStart`, `IAccount`, `DiffLine`, `FieldAccessInfo`, `AudioVideoControllerState`, `vscode.DebugSession`, `d.OutputTarget`, `DatabaseSet`, `JSDocTagInfo`, `Discipline`, `Pool`, `TempDir`, `MpEvent`, `Tabs`, `SegmentedBar`, `SocketPoolItem`, `FormDefinition`, `ThermostatSetpointType`, `SampleView`, `SelectedScope`, `Rx.Observable`, `RtpHeader`, `kKeyCode`, `WebGPUTensor`, `ToastsManager`, `InitData`, `CoreConnector`, `DescribeDatasetCommandInput`, `Privacy`, `ColorData`, `SchemaConstructor`, `GroupProperties`, `Resolution`, `SignalingClientObserver`, `QuickCommand`, `Fauna.Expr`, `SimulatorState`, `stream.Writable`, `AureliaProjects`, `RuleStateData`, `HnCache`, `Events.postdraw`, `DocCollection`, `RouteDeps`, `IterationUI`, `CarouselItem`, `ChannelService`, `UpdateParticipantRequest`, `WType`, `RemoteAction`, `ArrayOption`, `MainModule`, `CipherCCM`, `TweenInput`, `StorageOptions`, `CreateUserCommandOutput`, `TemplateUnparser`, `SpriteSpin.Data`, `StateBlock`, `google.maps.MarkerOptions`, `ViewPortManager`, `BifrostProtocol`, `GraphStats`, `Vec`, `IRequestOptions`, `StylableModuleSchema`, `ClrFlowBarStep`, `CSharpMethod`, `ColumnsProps`, `BaseUnit`, `CollectionValue`, `RuleChild`, `VisibleTextLocator`, `L1L2Args`, `IInventoryItem`, `RequestType0`, `ProviderData`, `InviteActions`, `AbiItem`, `MatrixProvider`, `GetChildNodes`, `AiPrivateEndpointSummary`, `PluginKey`, `TextComponent`, `HTMLLineElement`, `HookFunction`, `SuiDropdownMenuItem`, `ConvLSTM2DCellArgs`, `StreamAddOutgoingParam`, `FuseConfigService`, `CircuitGroupCircuit`, `ZipsonWriter`, `Types.PresetFnArgs`, `PathTargetLink`, `XTableColumn`, `HtmlTagObject`, `CSVInput`, `CoreDeploy`, `NextApiReq`, `BoundAction`, `Folder`, `dia.Cell`, `MigrationMap`, `OutputMessage`, `AgentOptions`, `Koa`, `IntelliCenterConfigRequest`, `Stmt`, `ValueObject`, `CivilContextValue`, `PriceData`, `TestMochaAdapter`, `Touch`, `Highcharts.Options`, `ContractCall`, `CollectionViewer`, `B2`, `ParameterName`, `ILyric`, `NonExecutableStepCall`, `CreateAppRequest`, `AutoFeeLevels`, `SearchEnhancements`, `AuguryEvent`, `DaffGetCategoryResponse`, `ts.ImportClause`, `LContext`, `ITheme`, `RiskLevel`, `AddressBookConfig`, `KeyframeIconType`, `ResourceManager`, `TEvents`, `StructureContainer`, `FilterObject`, `DataAssetSummary`, `UpdateNetworkProfileCommandInput`, `PrivateEndpointDetails`, `DynamicTextStyle`, `CircleShape`, `TaskDto`, `NestedHooks`, `Fu`, `DescribeSnapshotsCommandInput`, `LogEntry`, `CustomCode`, `RefactorAction`, `CLIElement`, `TabStateReturn`, `DraggableData`, `Blok`, `EnumDeclaration`, `AnnotationsMap`, `VMenuData`, `InstanceDetails`, `BaseRecordConstructor`, `CompletionPrefix`, `IssuesCreateCommentParams`, `d.ComponentCompilerProperty`, `ShortcutsTypes`, `DebuggingMode`, `TableSchema`, `SeederCollection`, `PartyMatchmakerAdd`, `LogicalQueryPlan`, `MapViewApp`, `ManualClock`, `requests.ListBootVolumesRequest`, `BlocksModel`, `TaskObserversUnknown`, `TransformCssToEsmOutput`, `TEmbeddableInput`, `OperationType`, `OhbugClient`, `Models.QuotingParameters`, `BarProps`, `Feature`, `TreeSelectItem`, `TokenPayload`, `INodeInfo`, `SketchLayer`, `VChild`, `ViewportScrollPosition`, `requests.ListStreamPoolsRequest`, `IAward`, `TaskTypes`, `IterableX`, `DeleteEmailTemplateCommandInput`, `ResolveInfo`, `LanguageData`, `MutableVector2`, `StaticComponent`, `ISystemActions`, `BlobService`, `YallOptions`, `DictionaryService`, `FunctionCall`, `PerfectScrollbarConfigInterface`, `WebhookActionConnector`, `BottomSheetNavigationState`, `pxtc.ApisInfo`, `TransactionAuthFieldContents`, `ISampler`, `PackageDetails`, `BaseEvent`, `ToolbarUsage`, `LayoutBase`, `BaseAtom`, `ex.Input.PointerEvent`, `DocumentExtra`, `MediaTrackConstraints`, `TableColumn`, `TimePrecision`, `TemplatePieces`, `QueryDocumentSnapshot`, `MsgDepositDeployment`, `CentersService`, `IdentityProviderSelectionPage`, `ICellEditorParams`, `DomSource`, `SourceMaps`, `ArgValue`, `ContextInterface`, `TestClient`, `PlayerListPlayer`, `RotationallySymmetricShape`, `StoredConfiguration`, `CmsConfig`, `requests.DeleteWorkRequestRequest`, `ILoggerService`, `MDCTabAdapter`, `HapiServer`, `RenameParams`, `ISvgMapIconConsumerProps`, `IFormProps`, `StateVisNode`, `ReuseContextCloseEvent`, `AnimationFactory`, `MatHint`, `ResManager`, `ParseExpressionTextResults`, `CharCategoryMap`, `ActiveLabel`, `VisualizationsStartDeps`, `GunGraph`, `VariableValue`, `ExpectedDiagnostics`, `GX.DiffuseFunction`, `requests.ListVmClusterUpdatesRequest`, `NamedType`, `gPartial`, `SelectionConstructorArgs`, `AnimationKeyframeHermite`, `ClassDefinition`, `IObjectType`, `TimeZone`, `DeleteFlowCommandInput`, `MapDispatchToPropsFunction`, `Outbound`, `OptionMessage`, `React.ReactNode`, `HsdsCollection`, `android.net.Uri`, `DoStatement`, `NoticeItem`, `DisplayObjectWithCulling`, `CreateFolderCommandInput`, `GeneratedKey`, `WcCustomAction`, `ASTNode`, `usize`, `SelectOptionValue`, `VisOptionsProps`, `HeroSearchService`, `InteractiveProps`, `GtConfigField`, `DescribeValidDBInstanceModificationsCommandInput`, `TextRange`, `ProtractorBrowser`, `ArrayContent`, `E2EPage`, `RendererMock`, `QuestionMatrixDynamicModel`, `DeployProviders`, `btTransform`, `RoomMember`, `RouteTable`, `RuleData`, `d3.HierarchyPointNode`, `FD_Entity`, `ScaleByFactor`, `Profile`, `RadioButton`, `ActionTypeExecutorOptions`, `PlanetApplicationRefFaker`, `IAtDirectiveData`, `NodeStat`, `requests.ListDrgRouteDistributionsRequest`, `SeriesPoint`, `MessageDocument`, `WalkState`, `AssignmentDeclarationKind`, `AccountIdRequestMessage`, `ButtonHTMLProps`, `OrganizationTeamEmployee`, `CharWhere`, `StandardTokenMock`, `PageService`, `AttributifyOptions`, `LoginUser`, `TComAndDir`, `BrowserSession`, `AssignAction`, `LayoutStateModel`, `CommandCreatorResult`, `SMap`, `ActivityInfoModel`, `IKernel`, `SwaggerOptions`, `MissionSetupObjectSpawn`, `StopMeetingTranscriptionCommandInput`, `serviceRequests.GetWorkRequestRequest`, `NumberListRange`, `android.graphics.drawable.BitmapDrawable`, `TSTypeReference`, `TBSelection`, `d.TranspileModuleResults`, `HTMLHeadingElement`, `IncomingHttpResponse`, `BEMData`, `RadioItem`, `FlipperLib`, `ApiReturn`, `PDFObjectStream`, `INewProps`, `EndpointConfiguration`, `BottomNavigation`, `CancellationReason`, `ErrorMessage`, `Leg`, `PayloadType`, `Happening`, `MetaStaticLoader`, `OpenSearchUtilsPlugin`, `NuxtContext`, `GX.IndTexFormat`, `TActions`, `AnalysisCache`, `Helpers`, `ThExpr`, `ConnectFailedListener`, `GettersFor`, `OwnedUpgradeabilityProxyInstance`, `Collectable`, `TextField`, `CreateBundleDTO`, `FontAwesomeIconStandalone`, `FireLoopRef`, `CameraComponent`, `DAL.DEVICE_ID_MULTIBUTTON_ATTACH`, `FontMetricsObject`, `PromiseExecutor`, `LocalForage`, `WebController`, `Coll`, `ContainerInfo`, `HostedZone`, `Entitlement`, `IMetricContext`, `semver.SemVer`, `ClipEdge`, `ListConfigurationRevisionsCommandInput`, `SearchInWorkspaceResultLineNode`, `GetIamPolicyRequest`, `InternalParser`, `SigningWallet`, `ICountry`, `RawVueFileName`, `MenuPositionX`, `ProblemTagEntity`, `ActionMetadataArgs`, `AbstractAssets`, `ServerAccessKey`, `ValueQuery`, `MutableTreeModelNode`, `PatcherServer`, `RollupWatcherEvent`, `HttpPipelineLogLevel`, `DeclarationName`, `ResolveRequest`, `GalleryImageVersion`, `DebugGeometry`, `Keyframe`, `ContractAPI`, `LinearOptions`, `ThemeNeutralColors`, `IImageBuilder`, `AccountV10`, `ListTagsForResourceCommand`, `CLValue`, `PinchGestureEventData`, `UnionBuilder`, `AggregateCommit`, `WalkStats`, `BTI`, `NodeJS.Dict`, `StateChannelsJsonRpcMessage`, `IObserver`, `InteractiveController`, `IContentSearchFilter`, `SVGDefsElement`, `IFluidHandleContext`, `TopAggregateParamEditorProps`, `t_08f7c2ac`, `LoaderFactory`, `RecommendationSummary`, `ListenerFn`, `VNodeElement`, `InnerJoin`, `OptionalResources`, `MessageInstance`, `PaymentMethodCreateParams.BillingDetails`, `PathFn`, `CreateModelCommandInput`, `GoldenLayout.ItemConfig`, `TrackedSet`, `ICaptainDefinition`, `SingletonDeployment`, `JobDatabase`, `WrappedDocument`, `ProbabilitySemiringMapping`, `AzureBlobStorage`, `grpc.Metadata`, `DbSystemEndpoint`, `User1524199022084`, `JSMs.Services`, `BooleanType`, `OutputFile`, `ConverseContext`, `InvoiceItem`, `SelectorGroup`, `DescribeDomainsCommandInput`, `CdkHeaderRowDef`, `PendingRequest`, `ExtensiblePayload`, `FolderData`, `Gamepad`, `Iter`, `StyledComponentClass`, `IChangeRequestManagementItem`, `DirectionsType`, `MethodDeclaration`, `Dialogic.MaybeItem`, `RouterHistory`, `NameValue`, `ScreenInfo`, `CreateProcedureWithInputOutputParser`, `LambdaIntegration`, `LineNode`, `MXDartClass`, `CallReceiverMock`, `IOmnisharpTextEditor`, `SrvRecord`, `InputNode`, `TestView`, `ElectronEvent`, `IAssetState`, `ArcTransactionProposalResult`, `IEventType`, `TracksState`, `APIConfigurationParameters`, `IterableOrArrayLike`, `UploadFile`, `FaunaCollectionOptions`, `FirmwareWriterProgressListener`, `CFDocsDefinitionInfo`, `IThemeRegistration`, `R.Chain`, `ITransaction`, `NSDictionary`, `WorkerResponse`, `StackOutput`, `Exprs`, `Ui`, `Apollo.LazyQueryHookOptions`, `ConditionResolver`, `GetStateReturn`, `BasicJewishDate`, `FetchOptions`, `ISetting`, `DidChangeWatchedFilesParams`, `MaybeFuture`, `ProviderLike`, `PerimeterEdge`, `MessageFormatterOptions`, `Subscriber`, `TestingModule`, `DiagnosticWithLocation`, `RendererEvent`, `ItemPositionCacheEntry`, `SystemVerilogIndexer`, `AuthenticationPolicy`, `ITokens`, `Kwargs`, `ColumnScope`, `MissingTranslationHandlerParams`, `DAOMigrationParams`, `DeletePackageCommandInput`, `LayouterService`, `ast.MacroCallNode`, `LogSummary`, `polymer.Element`, `FormRenderer`, `SampleUtterances`, `UnitRuntimeContext`, `AlertUtils`, `Params$Create`, `EdmxFunction`, `yargs.Argv`, `PrerenderHydrateOptions`, `CommandBuilder`, `TextElement`, `d.TransformCssToEsmOutput`, `ClientRequestFailedEventArgs`, `PaginateOptions`, `Synth`, `angular.IHttpService`, `ProxyPropertyKey`, `OmniOscillator`, `TGetStaticProps`, `MDL0_MaterialEntry`, `PotentialLemma`, `NodeArray`, `CoinTransferMap`, `EmbeddableRendererProps`, `WebpackTestBundle`, `WorkflowDto`, `PublicCryptoKey`, `JCorner`, `SimpleStore`, `RawResponseCallback`, `BastionShareableLinkListRequest`, `IShikiTheme`, `UploadedFile`, `UI5Aggregation`, `SceneActivationCCSet`, `BaseSyntheticEvent`, `OsuBuffer`, `_SelectExplanation`, `TabbableHTMLProps`, `ListSubscriptionsResponse`, `CollisionEndEvent`, `WarframeData`, `UIBrewHelper`, `O.Compulsory`, `NPCActor`, `IDejaGridColumn`, `TextSegment`, `DenomHelper`, `ClockRotate`, `VariableMap`, `GitScmProvider`, `TreeIterator`, `RuntimeShape`, `SavedObjectsExportError`, `Endorser`, `Records`, `SignalOptions`, `DeletePublicAccessBlockCommandInput`, `BgState`, `NgxPermissionsService`, `Atom.Point`, `DecodeError`, `IAddGroupUsersResult`, `TypeData`, `BaseCollider`, `ParsedCssDocument`, `AccountOperation`, `requests.ListOnPremConnectorsRequest`, `CellInterface`, `CanvasItem`, `ISet`, `MessageEmbeddedImage`, `OptionalWNodeFactory`, `CloudService`, `ReadRepository`, `i`, `UpdateHostClassService`, `TestDriver`, `PreviewVer`, `SignatureHelpItem`, `IMergeTreeOp`, `GoToOptions`, `KibanaResponseFactory`, `SimpleRNNCell`, `apid.Rule`, `NgxDropzoneService`, `WsTitleService`, `StorageDriver`, `QuaternionKeyframe`, `Comparable`, `L.LatLngExpression`, `IProfileMetaData`, `Pooling2DLayerArgs`, `GetIntegrationCommandInput`, `OverridePreferenceName`, `RepositionScrollStrategy`, `Timer`, `INotificationOptions`, `ChartsPluginSetup`, `ScenarioResult`, `ShardFailureOpenModalButtonProps`, `ForgotPasswordEntity`, `UiCounterMetricType`, `FramePin`, `ContextContainer`, `KubectlContext`, `React.DependencyList`, `ViewportOptions`, `IMatchOptions`, `CheckboxGroupProps`, `SessionLogoutRequest`, `DeploymentParameters`, `VoiceFocusDeviceOptions`, `PendingMaintenanceAction`, `ThemeServiceStart`, `TimeInfo`, `LintReport`, `SearchParamAsset`, `ServiceError`, `PaperProfile`, `Linkman`, `GaussianNoiseArgs`, `CssSelector`, `Lookup`, `CumsumAttrs`, `ArmObj`, `TUserBaseEntity`, `InternalHttpServiceStart`, `DaemonSet`, `DocumentAccessList`, `HmrStyleUpdate`, `UpdateSource`, `MsgPauseGroup`, `QCNode`, `TBuilder`, `AbiStateUpdate`, `ForInStatement`, `AlfredConfigWithUnresolvedTasks`, `IntervalCollectionIterator`, `firebase.firestore.DocumentReference`, `ResolvedCoreOptions`, `CommandLineToolModel`, `ApexDebugStackFrameInfo`, `RowArray`, `PartialObserver`, `DataPublicPluginEnhancements`, `WExpression`, `CogJob`, `ILoaderPlugin`, `PendingFileType`, `GBDeployer`, `Kernel.IFuture`, `RangeInterface`, `CheerioAPI`, `UpdateSubscriptionsRequest`, `WasmTensor`, `OriginationOp`, `INEO`, `Updater`, `ReLULayerArgs`, `Clef`, `vscode.Task`, `So`, `PrivateEndpointConnectionsDeleteOptionalParams`, `TransmartExportJob`, `JsonDocsStyle`, `TabsService`, `MIRResolvedTypeKey`, `LockerService`, `NAVTableField`, `EventAction`, `ModifyDBClusterEndpointCommandInput`, `admin.app.App`, `DeploymentDocument`, `InsertQuery`, `SharedString`, `DotDotDotToken`, `MyAccountPage`, `Demand`, `Testability`, `ItemBuffer`, `Rx.AjaxRequest`, `YamlCodeActions`, `VAStepWord`, `IVFSMount`, `DeploymentCenterStateManager`, `CodeLensBuffer`, `DeserializedType`, `FocusEventInit`, `i18n.TagPlaceholder`, `Spreadsheet`, `ListCertificatesCommandInput`, `Indicator`, `ts.CustomTransformers`, `RenderErrorHandlerFnType`, `ColorDataObj`, `IGroup`, `FlowNode`, `PageBlock`, `AveragePooling2D`, `ResponsiveMode`, `QuantityFormatter`, `InputStream`, `PipetteOffsetCalibration`, `FunctionCallArgumentCollectionStub`, `requests.ListMountTargetsRequest`, `UserUI`, `TagList`, `V1PersistentVolumeClaim`, `PlasmicContext`, `Seek`, `BaseClientOptions`, `Requestor`, `CreateRulesSchema`, `DeleteRoomResponse`, `CheckboxChangeEvent`, `PhraseFilter`, `LineInfo`, `TableRowProps`, `AuthenticationHelper`, `ResolverBuilder`, `IColumns`, `Processor`, `IPointData`, `QuestionFormatter`, `WebTreeMapNode`, `Redis.ClusterOptions`, `ResponsiveFacade`, `ClassTypeResult`, `HttpEventType`, `ZRImage`, `DomRecorder`, `MnemonicVariationsX86`, `IDynamicGrammarGroup`, `AnimationTriggerMetadata`, `HDKey`, `PDFOperatorArg`, `MerchantOrderGoodsEntity`, `OutcomeShortHand`, `m.Component`, `IncomingStateType`, `AndroidMessagingStyle`, `UsePaginatedQueryData`, `Events.entertrigger`, `LegendProps`, `IZosFilesOptions`, `DeleteApplicationCommand`, `tsc.TypeChecker`, `CredentialRequestOptions`, `CardRenderEffect`, `PluginsService`, `PropSchema`, `SavedObjectsUpdateResponse`, `SidebarLinkProps`, `SingleOrBatchRequest`, `OrderState`, `LedgerState`, `ReactIntl.InjectedIntl`, `SeekOutput`, `SignatureFlags`, `OpenApiSchema`, `ZipFile`, `InsertOneWriteOpResult`, `DeploymentGroupConfig`, `ServiceWorkerState`, `AnimationBase`, `LambdaNode`, `EffectScope`, `ChromiumBrowserContext`, `HitEvent`, `Camera_t`, `ConfigurationItem`, `Vue.CreateElement`, `FsUtil`, `ShouldShow`, `RequiredParserServices`, `DeleteFriendsRequest`, `SearchKey`, `ChangedEvent`, `TabBarProps`, `STDataSourceOptions`, `ObjectInstance`, `ClickOptions`, `KeyedReplacementMap`, `HelperService`, `RepositoriesStatisticsState`, `ConversationTimeline`, `GetStorageSuccessCallbackResult`, `SAPNode`, `AuthKey`, `PhysicsStatistics`, `VirtualMachine`, `IUserRepo`, `SheetObject`, `ToTypeNode.Context`, `Traversable3`, `TraceIdentifier`, `translateMapType`, `UITapGestureRecognizer`, `SwitchLayerAction`, `IEditorAction`, `Kernel.IKernel`, `PhysXPhysicsMaterial`, `DataToExport`, `Publications`, `SendCommandRequest`, `SavedObjectsImportResponse`, `RelativeTime`, `IThriftRequest`, `GXShapeHelperGfx`, `KeymapItemEditableProps`, `BaseItemState`, `ValidEndpointType`, `Clip`, `Stone`, `IErrorState`, `CompoundSelector`, `KeybindingScope`, `RenderCamera`, `KeyBindings`, `JQueryXHR`, `Exponent`, `OptionEditorComponent`, `hardforkOptions`, `NewLineFile`, `Azure.TableBatch`, `TAccount`, `d.ComponentCompilerTypeReferences`, `GenericTreeItem`, `OptionsDevice`, `ParallelPlot`, `UnarynotaddsubContext`, `DropDownOption`, `ImperativeBase`, `HexDocument`, `BFT`, `NullAndEmptyHeadersClientCommandInput`, `FilterList`, `PDFPageLeaf`, `EarlyStopping`, `Timeslot`, `DispatcherLocals`, `XQuery`, `EmbeddableActionStorage`, `ToolbarItemProps`, `Axis3D`, `pb.Callback`, `DAL.DEVICE_ID_SCHEDULER`, `MatcherHintOptions`, `Ledger`, `Space2DSW`, `MTDTexture`, `Voting`, `IRoutes`, `HandlerInboundMessage`, `InstrumentedStorageTokenFetcher`, `ThunkActionT`, `C`, `MzInjectionService`, `JSType`, `DrawType`, `DebtPareto`, `SubmodelImage`, `ExcaliburGraphicsContextWebGL`, `DiagnosticRule`, `DecodedSourceMap`, `HsDialogContainerService`, `OptimizerConfig`, `MdcSnackbar`, `MDL0ModelInstance`, `GetMyProfileCommand`, `S1Node`, `CourseName`, `CreateAssetDTO`, `GetStudioCommandInput`, `MemoryPartition`, `ImportSavedObjectsOptions`, `MediaQueryData`, `VirtualInfo`, `ethers.Signer`, `ApplicationCommandOptionChoice`, `Debe`, `ActionBase`, `DataModels.Correlations.Correlation`, `UpdateActionDef`, `Indy.LedgerRequest`, `OrganizationContactService`, `RouteFactory`, `UpSetSelection`, `CallNode`, `LocaleProviderService`, `_IDb`, `setting`, `ButtonManager`, `CompactProtocol`, `MessageChannel`, `ENUM.AfflictionType`, `SymbolTracker`, `ReaderStateParserLike`, `ReadBuffer`, `NzSafeAny`, `DependencyWheelPoint`, `TargetTypesMap`, `SenderFunction`, `QueryStringInputProps`, `RedspotContext`, `AllInputs`, `requests.ListCostTrackingTagsRequest`, `PluginModel`, `MerchantIdentity`, `ImmutableNotebook`, `IqResponseStanza`, `SpecialPropertyAssignmentKind`, `TriggerType.GITHUB`, `ResetDBParameterGroupCommandInput`, `OverlayProps`, `ImageCache`, `InMemoryDriver`, `ApisInfo`, `BenefitMeasurement`, `requests.ListIamWorkRequestLogsRequest`, `ConnectedComponent`, `GfxMegaStateDescriptor`, `SubmissionEntity`, `IDiagramState`, `RegisterDeprecationsConfig`, `CommandName`, `StartDBClusterCommandInput`, `TextureParameterEnum`, `AdapterUser`, `RedisClient`, `Error_ContextEntry`, `PostRoles`, `OperationVariant`, `GetPolicyCommandInput`, `GridElement`, `HTTPBuffer`, `SdkProvider`, `RGBStrings`, `MeshVertice`, `SalesInvoiceModel`, `requests.ListErrataRequest`, `PlaneAngle`, `apid.ReserveId`, `DeployedCodePackageCollection`, `ServerHost`, `Twitter`, `ExampleDefinition`, `IChannelFactory`, `IntrospectionInputTypeRef`, `Booru`, `FieldFormatsRegistry`, `ExtraComment`, `DescribeComponentCommandInput`, `ImplDeployment`, `BIP32Path`, `order`, `ClientsService`, `IItemScore`, `AnalyticUnit`, `Angulartics2Mixpanel`, `vscode.WorkspaceEdit`, `JellyfishWallet`, `Matrix44`, `DkrTexture`, `Cropping2DLayerArgs`, `IntersectionObserverInit`, `StreamDeckWeb`, `IAssignmentUnitModel`, `TPackageJson`, `Electron.MenuItemConstructorOptions`, `Controller$`, `IpcMessageEvent`, `DayProps`, `IModuleStore`, `CAShapeLayer`, `BlockIndex`, `MeasureFormatter`, `ListWorkRequestLogsRequest`, `TSTNode`, `TradeFetchAnalyzeResult`, `IBabylonFileNode`, `TranslationService`, `LeaveGroupRequest`, `GridAxis`, `TimesheetService`, `ConfigurationTarget`, `IQueuedMessage`, `ActiveComponent`, `com.mapbox.pb.Tile.ILayer`, `OidcRegisteredService`, `GatewayToConceptRequest`, `TickItem`, `ContentManager`, `TTableOperand`, `Animation`, `WebFontMeta`, `CompilerSystemCreateDirectoryOptions`, `SelectionChangeEventArgs`, `Koa.Context`, `PositionWithCaret`, `LuaType`, `BrowseService`, `SendTxBody`, `NavigationContext`, `X`, `IShadingContext`, `DataModels.TokenHistory.TokenHistoryGroup`, `RippleCreateTransactionOptions`, `Appearance`, `KeyList`, `LabelSet`, `KeycloakAdminClient`, `E2EProcessEnv`, `Bond`, `GraphQLFieldConfigArgumentMap`, `EntityValidator`, `BazelWorkspaceInfo`, `SavedDashboardPanel730ToLatest`, `Animated.SharedValue`, `MatButtonToggle`, `IVSCServerManagerEventsHandler`, `ProposalResponse`, `ICfnSubExpression`, `IDataSource`, `ColumnFilters`, `Receiver`, `DefaultRequestSigner`, `DataNode`, `DotnetInsightsGcDocument`, `Vector4_`, `ExpressRoutePort`, `InitiatingWindowProps`, `MatchmakerMatched_MatchmakerUser_StringPropertiesEntry`, `IValidatedEvent`, `IJavaProjectWizardContext`, `Bsp`, `TileData`, `FixedPointX64`, `ReaderTask`, `UsernamePassword`, `ContinuousDomain`, `PIXI.DisplayObject`, `C9`, `TaskStatus`, `ESLSelectItem`, `ThyDropPosition`, `DeviceRegistryService`, `ZWaveErrorCodes`, `t.NodePath`, `CacheInfo`, `ToggleDeselectSeriesAction`, `ChaincodeStub`, `Object`, `Price`, `KintoRequest`, `ListInstancesRequest`, `requests.ListVolumeBackupsRequest`, `DeployStepID`, `ISetActionTypes`, `IItemBase`, `RenameEntityEvent`, `DataTypeDefinition`, `TSTypeElement`, `core.CommonInputFieldConfig`, `PQLS.Analysis`, `SerializedTemplateInfo`, `t.Statement`, `ValueDescriptor`, `InitiateLayerUploadCommandInput`, `TestCursorQuery`, `DeepPartial`, `TrustedSc`, `ObjWrapper`, `FakeData`, `FrameworkInfo`, `LineComment`, `NullLiteralExpr`, `Matrix3x2`, `t.Visitor`, `ISmartContract`, `ConnectionMode`, `SingleProof`, `MatchedContext`, `Calc`, `IdentifyEventType`, `Documentable`, `LayerType`, `SavedQueryAttributes`, `AuditConfig`, `_ISchema`, `tf.io.WeightsManifestConfig`, `ts.TypeLiteralNode`, `vue.ComponentOptions`, `DescribeParameterGroupsCommandInput`, `ApplicationRef`, `requests.ListDataGuardAssociationsRequest`, `TSConfig`, `PhotoService`, `JsonPatchOperationsState`, `FSWatcher`, `TLPointerInfo`, `PackageTarget`, `IFieldsAndMethods`, `AnimationFrame`, `BuildVideoGetQueryOptions`, `TokenBalance`, `ProductVariantSettingService`, `BreadcrumbsListProps`, `BigQueryRetrievalResult`, `CommentTag`, `AggregateRewriteData`, `CachedQuery`, `trm.ToolRunner`, `StickerOptions`, `RelationshipType`, `TAccumulate`, `GetGroupCommandInput`, `ReactiveInteraction`, `CurrencySymbolWidthType`, `IServiceManager`, `Flair`, `RnM2Accessor`, `RemoteEvent`, `PixelImage`, `MetricState`, `DataChannel`, `IOdspTokenManagerCacheKey`, `TablePaginationConfig`, `Bunjil`, `EaseItem`, `EncryptedDataKey`, `SolutionSet`, `K.FlowTypeKind`, `CssPropertyOptions`, `app.LoggerService`, `FixedPointNumber`, `Docker`, `EbsMetricChange`, `InstallStatus`, `TransactionType`, `Model.Option`, `LineSegment3d`, `KeyPairTronPaymentsConfig`, `IndexSpecification`, `EdgeMaterialParameters`, `FloatSym`, `DraftBlockType`, `CreateAlbumeDto`, `SerializedRenderResult`, `StreamReturn`, `argparse.ArgumentParser`, `ListrRendererValue`, `QueryGraph`, `WorldBoundingBox`, `TradeStrategy`, `IDiffObject`, `SelectEffect`, `EmbeddableOptions`, `AveragePooling3D`, `OrganizationService`, `ContentMatcher`, `CellOptionType`, `AppHookService`, `AnyArenaNode`, `SIDE`, `EngineArgs.EvaluateDataLossInput`, `LexerActionExecutor`, `FlexParentProps`, `LeftHandSideExpression`, `Capture`, `MDCSwitchAdapter`, `requests.ListApmDomainsRequest`, `ASSymbol`, `WCLFight`, `MutationTree`, `MDCCheckboxAdapter`, `DeleteTableCommandInput`, `CreateOneInputType`, `DebugProtocol.ContinueResponse`, `PostProcessor`, `TAbstractControl`, `BasicSeriesSpec`, `Usage`, `WithSubGeneric`, `BehaviorHook`, `MappedCode`, `OnLoadArgs`, `AzureAccount`, `IObjectHash`, `ProofCommandResponse`, `StackGroup`, `FormPayload`, `ColumnSetting`, `Prioritized`, `IMessageItem`, `FiltersState`, `SyncExpectationResult`, `InitMessage`, `HttpsCallableResult`, `Double`, `UserLecture`, `TradeSearchRequest`, `MockedResponse`, `DefItem`, `jdspec.ServiceSpec`, `ControlPanelConfig`, `StateInfo`, `RTCDataChannel`, `TStore`, `HairProps`, `TransformFactory`, `COURSE_TYPE`, `G`, `IHookStateSetAction`, `IZoweTreeNode`, `Candidate`, `ICommandArgs`, `TagResourceCommandOutput`, `DynamicColorProperty`, `GeniePlugin`, `ParsedBlock`, `GithubIssueItem`, `BlockNumberState`, `BenefitService`, `StaticConnectionType`, `BinaryTreeNode`, `AskQuestionsParams`, `UnionOfConvexClipPlaneSets`, `FileSystemStats`, `IterationDirection`, `ErrorInfo`, `ISectionProps`, `DecryptResultPmcrypto`, `TupleType`, `ChannelSummary`, `StoryFile`, `IVarSize`, `InstanceStatus`, `BasicCCSet`, `RepositoryIssue`, `IAuthResponse`, `ESTestIndexTool`, `GenericLogger`, `SystemFixture`, `OrganizationsService`, `IExtent`, `Importance`, `DebugProtocol.ScopesArguments`, `DiagramEngine`, `IPathResultItem`, `Base58CheckResult`, `BINModelSectorData`, `ClassBuffer`, `Showtime`, `Carrier`, `DraftDecoratorType`, `IListItemAttrs`, `GeoLatLng`, `RequestTracingConfig`, `IdentifierInput`, `ForeignAttributeSelector`, `BasicUnit`, `WebContext`, `IChallengeProps`, `CommentGraphicsItem`, `SignatureHelpResults`, `MdDialogRef`, `InfoWindow`, `AddressInformation`, `ReminderFormatConfig`, `handlerFunc`, `ResourceTimelineGridWrapper`, `RtpTrack`, `FixResult`, `PCode`, `TimeRequestOptionsSourcesTargets`, `SimpleAttribute`, `ICreateVsamOptions`, `ReportService`, `GfxDevice`, `SideBarItem`, `BlockingResponse`, `FileSource`, `TwComponent`, `UsageCounter`, `OverlayPortal`, `cdk.CustomResource`, `VirtualMachineRunCommand`, `META`, `MarkerSnap`, `TransactionOverrides`, `Toplevel`, `MaybeElementRef`, `IPythonVenvWizardContext`, `AuthenticationConfiguration`, `RegionTagLocation`, `EntityAction`, `ChildRule`, `CertificateSubjectAlternativeName`, `CanvasTextBaseline`, `MockSegmentStore`, `TypeMoq.IMock`, `CredentialStore`, `MenuContextProps`, `WorkflowType`, `HTMLDivElement`, `NodeTree`, `SuspenseContextType`, `RoutesManifest`, `QR`, `CoinPretty`, `HashedFolderAndFileType`, `AnyType`, `LoginSuccessPayload`, `ModifyPoint`, `FauxClassGenerator`, `ParsedTemplate`, `Transforms`, `Enum`, `ListIntegrationInstancesRequest`, `P7`, `LanguageType`, `SortingService`, `Jest26CacheKeyOptions`, `ResponsiveInfo`, `InstallTypingHost`, `ThemeReducer`, `ZoneDefinitionModel`, `MessageReaction`, `PathData`, `TrueSkill`, `APIPost`, `CheckFn`, `requests.ListReplicationPoliciesRequest`, `BrowserFiles`, `I18N`, `HexMesh`, `ISearchResult`, `ConfigurationModel`, `IAllBondData`, `CumSumProgram`, `requests.ListBootVolumeReplicasRequest`, `IGetToken`, `DOMEventName`, `RecordProxy`, `CliArgs`, `HighlightService`, `CoreEnvironment`, `BScroll`, `Uint32List`, `DecimalFormatOptions`, `ModalWrapperProps`, `UserForm`, `ActivationFunction`, `StructuredAssignment`, `ContactMock`, `ChartErrorEvent`, `KnownAction`, `ServerConfig`, `MediaModel`, `ReactTestRendererTree`, `RangeResult`, `PositionOffset`, `ICategoricalFilter`, `AuthzService`, `ResponseGenerator`, `ResourceUnavailableException`, `DaffCategoryFilterToggleRequest`, `SecurityHealth`, `AxisOptions`, `StateT`, `ContextMenuInteraction`, `ListResourceTypesRequest`, `HsShareUrlService`, `Err`, `SinonMatcher`, `ICfnBinding`, `Types.GenerateOptions`, `PLAYER`, `GameplayClock`, `IHealthStateChunk`, `JointTreeNode`, `ShortcutID`, `TQuestionFull`, `Node.MethodParams`, `ErrorContext`, `QuirrelClient`, `AssignNode`, `Color.RGBA`, `Dexie.Table`, `NVM3Object`, `ReserveInstance`, `TrimmerTheme`, `I`, `IRoute`, `ProductContentPipe`, `CandidateStore`, `RemoteHotspot`, `TableServiceClient`, `LogAnalyticsParserField`, `JsxElement`, `ProxyOptions`, `AnonymousType`, `requests.ListCloudExadataInfrastructuresRequest`, `RenderTreeDiff`, `TensorArray`, `TypeTable`, `ActionRuntimeContext`, `CardScript`, `UpdateUserDto`, `TestSetupBuilder`, `GetRouteCommandInput`, `SdkPingPongFrame`, `TableAccessFullStep`, `StopExecution`, `AssetItem`, `DependencyIdentifier`, `SyncTable`, `DOMMatrix`, `PositionObjOrNot`, `IRecordedApiModel`, `Eula`, `PopoverController`, `ChromeApi`, `FileReflection`, `TimelineStep`, `OptionsState`, `WorkspaceFolderConfig`, `BotFrameworkAdapter`, `Intl.DateTimeFormatOptions`, `CalendarDay`, `EnvironmentInfo`, `RecoilValueReadOnly`, `ToComponent`, `GeneratorPaths`, `BoneAnimator`, `XTreeNode`, `ContextService`, `SCN0`, `NestedStagePanelsManager`, `BooleanInput`, `RequestWithUser`, `AnimatedSettings`, `S5PL2Layer`, `SavedObjectLoader`, `Storable`, `SimpleManipulator`, `ViewRef`, `Space`, `Kinds`, `SerialFormat`, `NodeEncryptionMaterial`, `MergeOptions`, `IDataSet`, `FontCatalogConfig`, `PagesService`, `RecordingSegment`, `CameraRigControls`, `vscode.DiagnosticSeverity`, `ConvertState`, `GetDomainRecordsResponse`, `WeatherService`, `IFontManager`, `JasmineTestEnv`, `TextDocumentSettings`, `BigNumber.BigNumber`, `MatchExp`, `ShapeBase`, `ListSourcesRequest`, `WebAppConfigStack`, `AssetBalance`, `ICommandBarProps`, `NormalizedCacheObject`, `SortingOrder`, `TreemapSeries.NodeObject`, `DevServer`, `TargetDatabaseTypes`, `TextureCubeFace`, `PatternStringProperty`, `PasswordGenerationService`, `CameraStrategy`, `Pow`, `BoundCurves`, `Prompt`, `Selective`, `PickerDelegate`, `ChartDef`, `ScullyContentService`, `DependencyPair`, `Function`, `Shift.Expression`, `IOpenSearchDashboardsSearchResponse`, `DescribeFleetsCommandInput`, `ActionProcessor`, `NumberValue`, `LineGraphicsOptions`, `WebSocket.MessageEvent`, `NextHandler`, `IAdapter`, `ReactiveChartStateProps`, `StrictValidator`, `ValidatePurchaseAppleRequest`, `DeleteDatasetCommandInput`, `ChipCollection`, `UnixTimestamp`, `PSTTableItem`, `VerdaccioConfig`, `ExecutionItem`, `OpenApiPersistedSchema`, `ts.PrefixUnaryExpression`, `RequiredValidator`, `Purchase`, `CompiledQuery`, `BaseRouteName`, `IDefinition`, `AlainSFConfig`, `PublisherSummary`, `ChartData`, `IStopwatch`, `SRT0_TexData`, `instance`, `MockProxy`, `PositionData`, `OnPostAuthResult`, `LogoActionTypes`, `PackageDependency`, `Publisher`, `PlatformNode`, `ParseSpan`, `ByteArray`, `AsyncBarrier`, `MmpService`, `_`, `Aes128Key`, `LogStructuredData`, `DataPointPosition`, `StaticMeshAsset`, `JsonRpcResult`, `IInterceptorOptions`, `_1.Operator.fλ`, `ReadOnlyAtom`, `ScreenDimension`, `IHandlerParameters`, `SignedStateVarsWithHash`, `model.Model`, `TPositionPair`, `Flatten`, `ReportingConfig`, `AudioOutputFormatImpl`, `ComponentSymbolTable`, `LeaguePriceSource`, `CircularAxisData`, `SupportedBodyLanguage`, `EntityConfig`, `PythonShell`, `CirclinePredicate`, `FilterRequest`, `UploadData`, `AlphaDropoutArgs`, `LoginToken`, `DocumentCollection`, `PreprocessorSync`, `IExchangeInfo`, `MakiObject`, `BackendValues`, `DAL.KEY_TAB`, `SlideProps`, `i.Node`, `OnProgressCallbackFunction`, `StringValidator`, `ITokenResponse`, `HashMap`, `IGBInstance`, `EidasRequest`, `CommentModel`, `PackInfo`, `HeaderProps`, `GlobalAveragePooling1D`, `IPhysicsMaterial`, `OverlappingPathAnalyzer`, `RelaxedPolylinePoint`, `ComplexSelector`, `TxHelper`, `CoreURI`, `VMLDOMElement`, `requests.ListJobShapesRequest`, `StacksKeys`, `PopperProps`, `ActiveModifiers`, `StateDto`, `SimpleStatementContext`, `UndoManager`, `OptionalEntry`, `TypeDisplayOptions`, `OpcuaForm`, `SFCDiffWatcher`, `ManagedListType`, `StorageEngine`, `FormDialogService`, `ParticipantItemStrings`, `V1WorkflowStepInputModel`, `MessageLogger`, `BodyComplexClient`, `ReferencesNode`, `EC_Public_JsonWebKey`, `messages.Ci`, `DnsRecord`, `BadgeButtonWidget`, `ListChannelsResponse`, `CombatStats`, `ServiceProviderAdapterMongoService`, `ScaleGamma`, `TimeIntervalTriggeringPolicyConfig`, `DefaultPass`, `IColorValueMap`, `IceState`, `IValidationSchema`, `MgtFlyout`, `IBasePickerSuggestionsProps`, `BN.Value`, `ReportStoreService`, `NavLocation`, `Highcharts.ClusterAndNoiseObject`, `ServerEntry`, `CreateTagsRequest`, `megalogDoc`, `anyNode`, `StateNamespace`, `AccessLevel`, `anchor.Wallet`, `NzConfigService`, `markdownit`, `BaseException`, `LangiumSharedServices`, `Emission`, `AccessTokenData`, `IAggregateConfiguration`, `HttpFetchOptions`, `SerializedSourceAnalysis`, `ListDatasetsCommandInput`, `ProxyGroup`, `LabelEncoder`, `PlotlyLib`, `PayloadTooLargeError`, `SpecQueryModelGroup`, `XColorsTheme`, `ATN`, `StructureCollection`, `SVGProps`, `MessageImages`, `core.ETHVerifyMessage`, `AtomicAssetsNamespace`, `StackStatus`, `TypeOptions`, `IInviteGroupUsersResult`, `AllureStep`, `CertificateProfileType`, `MockTemplateElement`, `PluginRevertActionPayload`, `android.view.ViewGroup`, `Topic`, `TabWatcher`, `SemicolonClassElement`, `NgbDate`, `AllSeries`, `ServerService`, `FileElement`, `DaffCartCoupon`, `SubTrie`, `CreateOrganizationCommandInput`, `LayoutProps`, `PickerInput`, `UIViewControllerTransitionCoordinator`, `ClassNameMap`, `NodeGraphicsItem`, `ConnectionProvider`, `ComponentChild`, `NativePlatformResponse`, `NgGridItemEvent`, `EdmxProperty`, `ActionReducerMapBuilder`, `VisitFn`, `NSFileManager`, `DebugVariable`, `UpdateContent`, `A4`, `CollectorFilter`, `ChildBid`, `PathNodeData`, `WhitelistInstance`, `IHttpGetResult`, `InsertWriteOpResult`, `DataMaskCategory`, `IEditorController`, `PatternCaptureNode`, `WorkspaceHeader`, `DataClient`, `IKsyTypes`, `TaskConfigurationModel`, `ProcessRequirementModel`, `HappeningsValidationOutcome`, `ObservableArrayProxy`, `BuildRequestOptions`, `GlobalEventModel`, `StorageLocation`, `IFB3Block`, `AppearanceService`, `AvailabilitySlot`, `TsSelectionListComponent`, `XActionContext`, `RuntimeConfig`, `TsLinter`, `StreamModule`, `StateInline`, `GridRenderCellParams`, `Round`, `requests.ListJobsRequest`, `Play`, `ReturnTypeInferenceContext`, `GraphQLConnectionDefinitions`, `FactoryFn`, `ServiceRequest`, `Func`, `IQueryCondition`, `DeleteScheduleCommandInput`, `PrefixLogger`, `hubCommon.IRevertableTaskResult`, `StackCardInterpolatedStyle`, `Nameable`, `ServiceRoom`, `CSSObjectWithLabel`, `AppExecution`, `IStop`, `FileRelativeUrl`, `ModelFactory`, `SafeUrl`, `FieldTransformConfig`, `ElementX`, `TickLabelBounds`, `ColumnPreset`, `IDockerImage`, `SerializableResponse`, `Asserts`, `EventRecord`, `XData`, `ExtraPost`, `SMTLet`, `IProgressReporter`, `DateTableContext`, `ComponentCompilerLegacyConnect`, `ListPipelineExecutionsCommandInput`, `Cascade`, `IRoom`, `ProxyAgent`, `ServiceIdRequestDetails`, `Allocation`, `SqlTuningTaskSqlDetail`, `CRUDEngine`, `DocumentGeneratorItem`, `AngularPackageLoggerMessage`, `LoggingMetaData`, `IrisIcon`, `CreatePackageCommandInput`, `MockedLogger`, `ExtraOptions`, `LambdaService`, `IDragCursorInfos`, `CandidatePair`, `RoomPosition`, `LogicNode`, `WorkspaceRepo`, `TransactionExplanation`, `ICardProps`, `VersionData`, `ISavedVis`, `TestCaseSetup`, `TurtleBuilder`, `ProsemirrorAttributes`, `JLCComp_t`, `DejaColorFab`, `ClassSession`, `SyntheticPerformanceMetrics`, `DocumentRecord`, `HeadersInit`, `PointEditOptions`, `SharedService`, `Listable`, `ExportKind`, `ExportsAnalyzerResult`, `ResponderModel`, `TempoEvent`, `CreatorBase`, `RxnArrow`, `Multiply`, `MockSetup`, `FormatFunc`, `ThyTooltipConfig`, `ArmResourceDescriptor`, `GoodGhostingInfo`, `NetworkAddress`, `ReportingAPIClient`, `NodeInterface`, `PermissionType`, `CommentReply`, `AppLeaveHandler`, `GroupedPriorityList`, `Amplitude`, `vscode.DocumentSymbol`, `RowValidatorCallback`, `NgWalkerConfig`, `DkrObject`, `ConnectionErrorCode`, `SpeechTranslationConfigImpl`, `WebSiteManagementModels.AppServicePlan`, `TimeChangeEvent`, `ListrTaskWrapper`, `requests.ListDbSystemPatchesRequest`, `EmitTextWriter`, `EditableRow`, `DocumentViewResponse`, `HttpAdapter`, `apid.ThumbnailId`, `ShipData`, `BoxSliderOptions`, `TabType`, `MetadataInfo`, `Highcharts.QuadTreeNode`, `ElasticLoadBalancingV2MetricChange`, `NgModuleRef`, `AggsCommonStart`, `UntypedBspSet`, `PhysicalQueryPlanNode`, `AddUserCommand`, `FunctionConfig`, `Transition`, `ReduxCompatibleReducer`, `FieldDefinitionNode`, `AESEncryptionParams`, `TombFinance`, `Html5QrcodeSupportedFormats`, `SdkIndexFrame`, `e`, `OrchestrationVariable`, `HTMLIonMenuElement`, `CreateDeploymentResponse`, `BaseApi`, `FreezeObject`, `AliasDeclaration`, `CreateAppCommandInput`, `RoleHTMLProps`, `PortRecordType`, `EnrichedDeprecationInfo`, `TestObject`, `CommonNode`, `MDCButton`, `Tremolo`, `AtomicMarketContext`, `Id64Set`, `OidcCtx`, `VariableUse`, `IModel`, `DiagnosticCategory`, `DescribeChannelModeratedByAppInstanceUserCommandInput`, `EventFacade`, `CounterProps`, `SymbolFlags`, `PartialSequenceLength`, `AdvancedSettings`, `GitlabUser`, `UIToast`, `DebtTransaction`, `DateRangeBucketAggDependencies`, `DirectChannel`, `DensityBuilder`, `E2EPageInternal`, `TraceNode`, `StoreModule`, `PublicationDocument`, `ColumnRefContext`, `AdEventListener`, `BeanWrapper`, `NextFunction`, `JWTVerifyResult`, `ITrackItem`, `MatcherState`, `SlashParams`, `ContentItem`, `TInterval`, `GnosisExecTx`, `SolidLineMaterial`, `Inode`, `IdTokenResult`, `IArtifact`, `TriggerApexTests`, `ResDicEntry`, `CtrFail`, `ApexExecutionOverlayAction`, `SearchQueryProps`, `VisualizeEditorVisInstance`, `SurveyPropertyEditorBase`, `alt.Vector3`, `YamlParser`, `CodeActionContext`, `ObjectProvider`, `DBContext`, `ValueService`, `EventManager`, `RequesterType`, `PanelHeaderProps`, `G6Node`, `LemonTableColumn`, `SwaggerJson`, `CoapMethodName`, `ChartwerkTimeSerie`, `WaitingThreadInfo`, `BezierCoffs`, `NotExpression`, `vscode.CodeAction`, `AdjacencyGraph`, `Ability`, `SchemaRefContext`, `MapboxGeoJSONFeature`, `FixtureLoader`, `Tokenizer`, `RouterReq`, `AudioDescription`, `UpdateDashboardCommandInput`, `WebDriver`, `ItemService`, `INotificationTemplate`, `CurrencyFormatOptions`, `VersionedTextDocumentIdentifier`, `AzHttpClient`, `PlacementContext`, `Hash256String`, `It`, `RestManager`, `ExpressionValueSearchContext`, `IHeader`, `CreateAccountParams`, `ListChangeSetsCommandInput`, `DtlsRandom`, `BackupPolicy`, `CkbBurn`, `PageNode`, `TabComponentProps`, `Course`, `TreeNodeLocation`, `IExternalStorageManager`, `Adapter`, `DeleteResourcePolicyRequest`, `DetectorBuilder`, `zowe.IDownloadOptions`, `alt.IVector3`, `MapOf`, `LifecycleSettings`, `QuerySet`, `BaseListParams`, `ImageResult`, `EntityLike`, `PagerCell`, `SlpRefType`, `StaticRegion`, `SchemaAttributeType`, `FeatureUrl`, `Labor`, `Sponsor`, `DeleteProjectRequest`, `HyperlinkProps`, `UpdateStudioCommandInput`, `LegacyDrawing.Sprite`, `Stitches.ScaleValue`, `ComponentBed`, `OpCode`, `PreviewDataApp`, `ODataActionResource`, `InventoryFilter`, `MatchSpecific`, `IHttpFetchError`, `CompositePropertyDataFilterer`, `Shift.Node`, `ReviewerStatisticsState`, `d.FsReadOptions`, `requests.ListAlarmsRequest`, `DMMF.ModelAction`, `EditOptions`, `requests.ListVirtualCircuitsRequest`, `Spread`, `CreateProfileDto`, `ListAutoScalingConfigurationsRequest`, `IControllerAttribute`, `CreateDatasetCommandOutput`, `BitcoinjsNetwork`, `InputListProps`, `Elevation`, `ListCertificatesResponse`, `ModalComponent`, `BinaryNode`, `UseQueryReturn`, `TileMatrixSet`, `XRInputSource`, `MultiCommandCCCommandEncapsulation`, `ConnectionContracts.ConnectParams`, `AugmentedAssignmentNode`, `IClassify`, `InMemorySpanExporter`, `PostRequest`, `ListObjectsV2CommandInput`, `DataClassBehaviors`, `Lang`, `QueueItem`, `VcsRepository`, `EnhancedEmbeddableContext`, `NotificationData`, `XPCOM.nsIDOMWindow`, `ThunkAction`, `EditorStore`, `OptimizeCssInput`, `ProviderInfo`, `TableCell`, `FnArg`, `PageContent`, `Serializable.GraphSnapshot`, `ListDatasetsCommandOutput`, `WatcherFolderMap`, `TJSONObject`, `ProofreadRuleMatch`, `FunctionAppStack`, `OpIterator`, `d.PrintLine`, `OAuthRequest`, `ProductCategoryService`, `Trash`, `InternalContext`, `ICircuitGroup`, `ProjectDataManager`, `MaterialEntry`, `NamedImportsOrExports`, `OnExistingFileConflict`, `Test.TestLogType`, `GfxrPass`, `ApolloError`, `SvelteComponent`, `TaskBase`, `MoveTree`, `ethers.providers.Provider`, `DaffCategoryReducerState`, `Datepicker`, `SpatialStandupRoom`, `ComponentAst`, `Serverless`, `SM`, `DownloadTask`, `DetailedPeerCertificate`, `DevToolsExtensionContext`, `LowLevelResponse`, `ProofAttributeInfo`, `KeyResult`, `ComponentsState`, `UserDataPropertyAPI`, `QueueMap`, `UInt16`, `OsmConnection`, `HookResult`, `ThermostatFanModeCCReport`, `PlatformTypes`, `DeployedServicePackage`, `JobQueue`, `ActionTypes`, `XcodeProject`, `WebsocketData`, `CalibrationResponseAction`, `VisualizeEmbeddableFactoryDeps`, `Generate`, `EditDoc`, `ShapeConfig`, `Chance`, `TinyPg`, `ScannedBehavior`, `TweetEditorState`, `Blockchain`, `MappedTypeDescription`, `WatchDecorator`, `GuaribasUser`, `BroadcastService`, `DeploymentEnvironment`, `InstructionData`, `IMutableQuaternion`, `StatusUpdate`, `DiscordooError`, `ParticipantContents`, `JDesign`, `SymlinkCache`, `EthereumPaymentsUtilsConfig`, `OperationParameter`, `core.IRawOperationMessage`, `NextServer`, `IRenderer`, `GalleryProps`, `BooleanCV`, `GlobalCoordinates`, `Verifier`, `IBaseImageryMapConstructor`, `CollectionData`, `HsAddDataService`, `SavedObjectsBulkUpdateObject`, `MediaStreamConstraints`, `DatePipe`, `TIn`, `NavigationContainerRefWithCurrent`, `IntersectionTypeNode`, `ViewNode`, `Stripe`, `IWriteAbleSetCombination`, `BlockCache`, `OptionsStruct`, `MyCompanyRowConfig`, `ComparisonResult`, `AbstractRegisteredService`, `moneyMarket.oracle.PricesResponse`, `HTMLIonItemElement`, `IMutableCategorizedPropertyItem`, `Folded`, `NamespaceImport`, `DefaultContext`, `Cypress.PluginConfigOptions`, `SolutionBuilderHost`, `InputTimeRange`, `CancelExportTaskCommandInput`, `DialogDelegate`, `PlayerOptions`, `ParseTree`, `IProcFSEntry`, `Coverage`, `WorkingDirectoryStatus`, `InferredProject`, `StoneTypeArray`, `WorkItemTypeField`, `FsFiles`, `GroupName`, `GfxWrapMode`, `ObjectLiteralElement`, `IElement`, `TiledMap`, `ObjectTracker`, `common.RegionProvider`, `LoggableTarget`, `DriveFile`, `requests.ListDedicatedVmHostShapesRequest`, `HostInstanceMap`, `ProxyIntegrationTester`, `GetEndpointCommandInput`, `ReindexActions`, `CollectionMetadata`, `SyntaxTree`, `DocInstance`, `LineUpJSType`, `ListDataViewsCommandInput`, `TabsListProps`, `IPromiseRetry`, `CollectionEvent`, `CellTile`, `SampleAt`, `IEmployeeJobsStatisticsResponse`, `WalletConnect`, `FnN3`, `API`, `INodeTypeDescription`, `TranslateAnswerConfig`, `VisiterOption`, `TxEventContext`, `TestAnalyzer`, `IBeacon`, `ProjectUser`, `BuildHelpers`, `ManualServerConfig`, `IStartTsoParms`, `DNSPacket`, `GatewayShardsInfo`, `ResourcePermission`, `BasePlacement`, `ReconnectionOptions`, `FieldConfigData`, `ExploreStateModel`, `Services.Plugins`, `KV`, `SourceMapSource`, `Canonizer`, `TEntity`, `NmberArray16`, `StoreMap`, `JSON5Config`, `DAL.KEY_6`, `ColorScaleInfo`, `Command.Command`, `MediaFormat`, `SVGAttributes3D`, `ArrayDiff`, `PostData`, `TProductFilter`, `MultilevelSwitchCCStartLevelChange`, `SimpleFunction`, `AbbreviationAttribute`, `CreateServiceRequest`, `IntervalJobOptions`, `CSVOutput`, `WithMetadata`, `CipherContext`, `TokenLocation`, `EphemeralTaskLifecycle`, `CallContext`, `MonoRepo`, `StackDataValues`, `PiEditProjectionItem`, `TokenList`, `ClassInfo`, `QueueStorageContext`, `TestingAggregate`, `MetaLogger`, `ANGLE_instanced_arrays`, `RadixParticle`, `BaseProtocolLabware`, `PackageConfig`, `LightGallery`, `ImageType.StyleAttributes`, `OrderTemplatesOverviewPage`, `Radian`, `IAnswer`, `ValueTypes`, `EntityConfiguration`, `TemplateService`, `DeleteAccountsRequestMessage`, `Effects.SpriteEffect`, `VirtualDocument`, `FsFile`, `SVGNodeAttribute`, `DereferencedSchema`, `NonRelativeModuleNameResolutionCache`, `StreakItem`, `ViberTypes.MessageOptions`, `Water`, `ASTVisit`, `JobLifecycleState`, `Types.KafkaConsumerMessageInterface`, `SupCore.Data.EntryNode`, `ts.StringLiteral`, `AT`, `NgOpenApiGen`, `GlobalService`, `LookupResult`, `TransitionCheckState`, `ImportNamespace.Interface2`, `UndoState`, `SignalData`, `IconSvg`, `CardName`, `ListSchemasCommandInput`, `apid.DropLogFileId`, `StatusCodeCallback`, `ListComprehensionIterNode`, `Registrar`, `ObjectNodeParams`, `PatternClassNode`, `JobSummary`, `doctrine.Type`, `requests.ListNetworkSecurityGroupsRequest`, `ModelManager`, `AriaProps`, `IPluginSettings`, `immutable.Map`, `IVirtualDeviceValidatorResult`, `KintoResponse`, `PatternMatch`, 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`WebSocket.Server`, `TableModel`, `DerivationPath`, `BuildSupport`, `S3.PutObjectRequest`, `ListResolverEndpointsRequest`, `CsvParserStream`, `MappedDataRow`, `JassPlayer`, `IActionContext`, `ComponentSlotStyle`, `vec2`, `VisualizePlugin`, `NcTab`, `XTransferNode`, `ILiquidationCandidate`, `ITaskRepository`, `CreateProjectCommand`, `worker.IWorkerContext`, `GraphContract`, `DropDownProps`, `ElementFound`, `forge.pkcs12.Pkcs12Pfx`, `Persona`, `Meta`, `ImportType`, `SearchCondition`, `CoerceFunc`, `EntityUID`, `CanvasElementModel`, `TestResults`, `IdentifierDecorator`, `StudioState`, `ScreenService`, `TResolvedResponse`, `AddUpdatesEvent`, `ControlActivity`, `DownloadResponse`, `InstallVirtualAppParams`, `WebampWindow`, `BlocksInfo`, `ListGroupsCommandInput`, `HistoryEntry`, `IDownload`, `InvalidateOptions`, `Rendered`, `RolesFunc`, `AbiInput`, `NgControl`, `Endomorphism`, `BaseMaterial`, `TypescriptEditorPane`, `IPersonalizationSurveyAnswers`, `RegExpLiteral`, `MediaRequest`, 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`CodeEditor.IPosition`, `RouteResponse`, `DaffCartPaymentMethod`, `OauthRequest`, `FSEntry`, `StepExtended`, `BastionHost`, `IUserData`, `RouteService`, `SalesInvoice`, `RefSet`, `Station`, `ClientPayload`, `ItemKeyboardNavigator`, `AstNodeWithLanguage`, `MActor`, `IAuth`, `ITestCase`, `WpResourceConfig`, `CogStacJob`, `BufferLike`, `VariationInfo`, `ObOrPromiseResult`, `WebSiteManagementModels.User`, `MockRequestInfo`, `Hapi.Server`, `GetQueryResultsCommandInput`, `CredentialsService`, `EndpointWithHostLabelOperationCommandInput`, `ImportAsNode`, `AuthenticateSteamRequest`, `DedicatedHost`, `ResolvedModuleWithFailedLookupLocations`, `HTMLPropsWithRefCallback`, `RouterConfiguration`, `OperationError`, `ConnectionResult`, `ParsedInterval`, `SavedObjectOpenSearchDashboardsServices`, `css.Node`, `Colors`, `messages.Location`, `RawResult`, `Oazapfts.RequestOpts`, `ImageHandlerEvent`, `AbiOutput`, `ResolveStylesOptions`, `RulesObject`, `CreateRepositoryResponse`, `PN`, `ChannelContract`, `Tracing`, `ServerMessage`, `DenoExtensionContext`, `LinkedHashSet`, `AlertInput`, `IAudioStreamNode`, `RNG`, `DragTarget`, `MicrosoftStorSimpleManagersResources`, `ResponseCallback`, `PrimaryKey`, `PatternMappingKeyEntryNode`, `RefreshTokenService`, `NgActionBar`, `BuildifierFileType`, `SlotOp`, `requests.ListMetastoresRequest`, `ArrayValues`, `TrackBuilder`, `PaginationDTO`, `SystemService`, `DID`, `IClassicmenuRuleSpec`, `MDSPostgresClient`, `ConnectArgs`, `ListUsersResponse`, `ConvLSTM2DCell`, `VaryMap`, `MdcCheckbox`, `RouteMethod`, `NpmInfo`, `TraceConstraint`, `SettingsDataUpdate`, `NotifyMessageDetailsType`, `KonvaEventObject`, `BlockchainTreeItem`, `android.graphics.drawable.Drawable`, `BinaryBitmap`, `FieldJSON`, `DeleteDomainCommand`, `ScalarTypeSpec`, `InfoActor`, `ExtraArgs`, `FileSystemUpdater`, `ESRuleConfig`, `UmiPluginNProgressConfig`, `Found`, `VcalVeventComponent`, `TestingFacade`, `AnimeListStatusFields`, `FullCalendar.ViewObject`, `kuberesources.ResourceKind`, `LookupItem`, `SubnetGroup`, `SentryScopeAdapter`, `PermuteLayerArgs`, `DeploymentConfig`, `DataMessage`, `NoteSnippetEditorConfig`, `BindingState`, `BaseClient`, `FileSystemEntries`, `PutConfigurationSetTrackingOptionsCommandInput`, `ThemeTool`, `SubscribeActions`, `TypeOrTypeArray`, `BasicCalculator`, `ImportStatements`, `ImageryMapExtent`, `CardManager`, `EventListenerCallback`, `FileHolder`, `ISequencedDocumentAugmentedMessage`, `PluginOrPackage`, `SerializedVis`, `UniqueOptions`, `IAttachMessage`, `convict.Schema`, `TimeQueryData`, `ListChannelModeratorsCommandInput`, `AuthenticationTemplate`, `StatefulChatClientArgs`, `VtexHttpClient`, `Http3FrameParser`, `CountryState`, `NzConfigKey`, `EntryObj`, `InnerAudioContext`, `SslConfig`, `IPlayerState`, `SCNMaterial`, `LobbyMember`, `ServiceProto`, `BackupShortTermRetentionPolicy`, `Sizes`, `requests.ListRoutingPoliciesRequest`, `Fzf`, `RemoveTagsFromResourceMessage`, `ListItemProps`, `Visitor`, `DataGridRow`, `CardProps`, `ListModelDeploymentShapesRequest`, `OmvFeatureFilterDescriptionBuilder.FeatureOption`, `SourceComponent`, `PublicEndpointDetails`, `AbsolutePosition`, `CheckPrivilegesResponse`, `LinterOffense`, `AutoforwardConfig`, `JoinTree`, `CHAINS`, `IRouter`, `CircularList`, `FnModules`, `IControl`, `ContactPayload`, `OpticsDomain`, `CustomWindow`, `ChangeDatabaseParameterDetails`, `RecordEdge`, `ModalType`, `PersistConfig`, `ResponderType`, `ExtractOptions`, `CsmSlotEntity`, `SMTFunctionUninterpreted`, `GeneralEventListener`, `ConchQuaternion`, `IssuanceAttestationsModel`, `CloudAccounts`, `FileListProps`, `PutBucketTaggingCommandInput`, `Vpc`, `IZoweJobTreeNode`, `EmployeeRecurringExpenseService`, `WaveformRegion`, `VerticalTextAlignment`, `Ident`, `DaffCategoryPageMetadata`, `PrimitiveField`, `PgType`, `RunnerGroup`, `ProofStatus`, `WechatTypes.SendMessageOptions`, `DeleteKeyPairCommandInput`, `Assembler`, `SPClientTemplates.RenderContext`, `Formatter`, `IndexProps`, `SentryEvent`, `StreamZip`, `TimeLog`, `SqlFile`, `Notifications`, `RunnerInfo`, `MongoMemoryServer`, `ConditionalTransactionCommitmentJSON`, `IMainMenu`, `RTCRtpCodecParameters`, `glob.Options`, `BSPFile`, `Iprops`, `HandlerResourceData`, `monaco.editor.IMarkerData`, `CliConfig`, `IKeyValuePair`, `FirmwareWriterPhaseListener`, `Glossary`, `SocketUser`, `IOpenSearchDashboardsSearchRequest`, `FetchFn`, `RootCID`, `WordGroup`, `ASTParserTree`, `TokenStreamRewriter`, `DeferredAction`, `ResourceDayGridWrapper`, `CreateCollectionOptions`, `PlanetApplicationService`, `TeamsActionConnector`, `PubKeyEncoding`, `NodeBuilderContext`, `ModuleKind`, `DataViewCategoryColumn`, `InstantRun`, `AEADCipher`, `NgxsDataStoragePlugin`, `EthereumAddress`, `ConditionalType`, `TrackDetails`, `CreateCustomVerificationEmailTemplateCommandInput`, `EmployeeLevelService`, `MovieService`, `PlannerConfigurationScope`, `T3`, `Weapon`, `WriteTournamentRecordRequest_TournamentRecordWrite`, `Login`, `MediaElementAudioSourceNode`, `CMDL`, `MagickGeometry`, `ResourceDifference`, `GDevice`, `ExploreBundleResult`, `ClassMember`, `InteractionModel`, `ThunkCreator`, `Json2Ts`, `DebouncedFunc`, `HandleProps`, `ts.BlockLike`, `RequestUser`, `UseSubscriptionReturn`, `CueSet`, `ProviderState`, `ComponentRegistry`, `JsxOpeningFragment`, `MockContext`, `WyvernAsset`, `InlineResolved`, `ng.ILogService`, `StationModel`, `DaffConfigurableProductVariant`, `DataViewHierarchyNode`, `AnimationDesc`, `RefedMixin`, `PerspectiveGetResult`, `PersistencyBlockModel`, `Cidr32Block`, `ServerException`, `BackgroundBlurOptions`, `IMatrixProducer`, `Events.pointerdragend`, `SetOverlap`, `TraceServiceSummary`, `ExecOutput`, `IVisualizerVertex`, `ResponseHandler`, `Accidental`, `RetryStrategy`, `AndroidSplashResourceConfig`, `ShrinkStrategyMock`, `CategoryCollection`, `Mailbox`, `FindUsersResult`, `FuncArg`, `CityRouteProps`, `HookEffects`, `PaginationModelItem`, `InitialAlert`, `StructureValue`, `BaseContext`, `ConfigurationModule`, `StacksOperationOutput`, `tcl.Tag`, `ModuleResolver`, `BroadlinkAPI`, `AppStateStatus`, `Vout`, `SlashingProtectionAttestation`, `ICodeGenerationStackOutput`, `RegistryConfig`, `ElementInfo`, `GeoJSONGeometry`, `LinuxDistribution`, `Caching`, `pxtc.BlocksInfo`, `CompiledProxyRule`, `VoyagerSubscriptionContextProvider`, `BinaryOp`, `ir.Type`, `ModuleRpcCommon.EncodedContext`, `JobIdOption`, `SceneContext`, `NodeJSKernelBackend`, `StatefulChatClient`, `ModelPredictConfig`, `DeletePolicyCommandInput`, `Entries`, `CppParseTree`, `TFSavedModel`, `GfxTextureDescriptor`, `YCommandInput`, `IStatusWarning`, `ClusterExplorerResourceNode`, `d.CompilerWorkerContext`, `ComponentWithProps`, `StyledCharacterStrategy`, `AssignOptions`, `ethereum.PartialTransaction`, `WritableData`, `IMdcSelectElement`, `EventSource`, `RailRider`, `DataTypeConfig`, `IFrameAttachment`, `PlannerPage`, `CommandRunner`, `VariableData`, `DocumentFragment`, `BlogState`, `Champion`, `TextContentBuilder`, `RouteArgs`, `KVStorageBackend`, `RunnerOptions`, `SupClient.ProjectClient`, `FetchTicketsActions`, `ReleaseActionProps`, `ParserOptionsArgs`, `Lobby`, `IPermissionReturnType`, `TestKmsKeyring`, `AirnodeRrp`, `ExpressionParams`, `CognitoMetricChange`, `ExecutionProbe`, `protos.google.iam.v1.ITestIamPermissionsRequest`, `ProductEntity`, `T.ComponentMap`, `InputResolution`, `ScreenshotBuildResults`, `DecodedSignaturePart`, `XScaleType`, `d.ErrorHandler`, `ConnectedUser`, `TwingCompiler`, `InfiniteLine`, `requests.ListTagsRequest`, `OrderGraph`, `TestAccountProvider`, `FieldValuePair`, `BodyImplementation`, `LanguageModes`, `ParameterListContext`, `DatabaseConfiguration`, `UX`, `AnyArena`, `TAggConfig`, `d.RollupConfig`, `PersonaIdentifier`, `HashType`, `Presence`, `IDataSourceDictionary`, `SerializedMessage`, `LabelService`, `Datatable`, `AngularPackageLoggerMessageType`, `CommandLineOptionOfCustomType`, `ListImagesRequest`, `ModelRenderContext`, `DeclinationDictionary`, `NativeInsertUpdateManyOptions`, `ZoneDelegate`, `d.JsonDocs`, `IResultSelection`, `SpawnClose`, `BindingItem`, `Logs`, `chrome.tabs.Tab`, `XRViewport`, `CompositeStrings`, `WriteFunc`, `THREE.Path`, `GlobPattern`, `ForeignKey`, `OpusRtpPayload`, `d.JsonDocsDependencyGraph`, `T.Model`, `ChatState`, `GetDevicePositionHistoryCommandInput`, `MessageQueue`, `Plane3dByOriginAndUnitNormal`, `TestSystemContractsType`, `ListEvents`, `IResource`, `O1`, `ResponseValue`, `TransferCommitment`, `SignIn`, `HasPos`, `BoolShape`, `InnerPlugin`, `PlaneGeometry`, `Embeddable`, `RequestConfigT`, `PermissionService`, `KickGroupUsersRequest`, `Renderers`, `PersistedEvent`, `MarkerOptions`, `ForAllSuchThatInput`, `IKactusFile`, `ContextInternal`, `RepositoryManager`, `pulumi.Input`, `PreferenceChangeEvent`, `WeaveNode`, `PointProps`, `JobExecutionState`, `MagicExtensionWarning`, `TimeSlotService`, `requests.ListGiVersionsRequest`, `ThemeType`, `NotificationOptions`, `NFT721V1`, `CastEvent`, `SkiplistNode`, `TransactionMetadata`, `Rigidbody3D`, `IOsdUrlControls`, `FunctionReturnTypeCallback`, `ISearchGeneric`, `ifm.IRequestInfo`, `PeerType`, `datePickerModule.DatePicker`, `TileCorners`, `Domain`, `HintID`, `Cmd`, `UpdateAliasCommandInput`, `IdentityData`, `DebugPluginConfiguration`, `ServerSideVerificationOptions`, `Uint64Array`, `NodePolyfillsOptions`, `PageEditContextInterface`, `SVError`, `QueryParameters`, `GeoShape`, `ChatServer`, `BoundExistsFn`, `GlitzServer`, `FirstDataRenderedEvent`, `XBus`, `WorldCountry`, `ExpressRouteCircuitConnection`, `HTMLLinkElement`, `IGovernancePowerDelegationToken`, `ObjectCsvStringifier`, `KeyboardState`, `CoreImagesContract`, `FakeCommand`, `CSSOpts`, `Globber`, `PropertyName`, `VehicleState`, `EditorPlugin`, `ResolvedElement`, `ErrorWithMetadata`, `SVGForeignObjectElement`, `PropertyType`, `browsing.FilesView`, `ThemeUIStyleObject`, `PathComponent`, `PluginPass`, `DQCCacheData`, `MetricSeriesFragment`, `HookRegistry`, `AFileParser`, `GetAuthorizerCommandInput`, `ComponentList`, `CodeCell`, `CdsAlert`, `GenericOperationDefinition`, `SignedStopLimitOrder`, `IReadOnlyFunctionParameterCollection`, `SizeProps`, `ActionDefinitionByType`, `BcryptAdapter`, `Sym`, `S2`, `FirewallPolicyRuleCollectionGroup`, `TransferDirection`, `PartialRequired`, `LocalRegistry`, `TestUnitsProvider`, `WithString`, `InflectorRule`, `TranslateParams`, `MockService`, `UploadObservable`, `AxisSpace`, `AddConfigDeprecation`, `FetchStore`, `ChangeDetectorRef`, `DeletePortalCommandInput`, `JPADynamicsBlock`, `ReducerNode`, `NavigatorAxis`, `Conv2DConfig`, `SourceNode`, `NavigationNode`, `GPUAdapter`, `DiagnosticMessageChain`, `Overmind`, `DatabaseReference`, `GDITrack`, `GfxResource`, `ResolverInfo`, `ScaleContinuousNumeric`, `StudioBase`, `AssetMarketPrice`, `DeepMocked`, `BreadcrumbService`, `AggregationType`, `ScheduleActions`, `ResizeObserverCallback`, `ContestModel`, `Desc`, `MockedKeys`, `ScanSegmentVectorItem`, `ListPlaceIndexesCommandInput`, `Sequelize.Sequelize`, `VisualizationLinkParams`, `EmotesProvider`, `ModuleLinks`, `NumberPattern`, `ContainerProps`, `InternalCredentialManager`, `KeySchemaElement`, `SerializedRootCID`, `NameExpression`, `KeysToKeysToAnyValue`, `AggsSetupDependencies`, `TInjectTokenProvider`, `ThyTableColumn`, `TestHelper`, `GenericThemeShape`, `MockComm`, `NoteSnippetContent`, `uibPagination`, `Typehole`, `RibbonComponent`, `Timestamp`, `TranslationProject`, `ScrollViewProps`, `FullQuestionWithId`, `RulePathEntry`, `ProcessingEvent`, `FunctionResult`, `NetworkIndicator`, `NullableDateLimit`, `RequestProps`, `MeshStandardMaterial`, `ChannelStateWithSupported`, `Previews`, `MappingTreeObject`, `Depth`, `ConnectionSettings`, `LoggingService`, `ConfigValueFormat`, `SeriesBarColorer`, `webpack.LoaderContext`, `FirebaseAuthState`, `CompilerJsDoc`, `TsDocumentService`, `InstanceFailoverGroup`, `WebhookRequestData`, `RecipientCounts`, `ESLCarousel`, `CharacterStatsCalculator`, `RendererPlugin`, `UIEdgeInsets`, `IPolygonPoint`, `SimpleDeep`, `AxisData`, `ConsoleColor`, `PrinterService`, `DecomposedJwt`, `OcsConnection`, `MapDispatch`, `ProjectStatsChartDataItem`, `SemanticsAction`, `BrowserFeature`, `DiceRoller`, `HttpStatusCode`, `JiraIntegrationService`, `VaultItem`, `NzResizeEvent`, `THREE.Shader`, `CategoryThread`, `IDom`, `BluetoothCharacteristicUUID`, `TxData`, `NormalizedPapiParameters`, `TooltipOptions`, `UpdateDomainNameCommandInput`, `UserPasswordEntity`, `UseQueryPrepareHelpers`, `AttachedProperty`, `SqrlStatementSlot`, `ModbusEndianness`, `PerpV2BaseToken`, `IGroupCellRenderer`, `InvalidInputException`, `C7`, `Watchman`, `IHeaderExtensionObject`, `PathResolver`, `DynamoDB.BatchGetItemOutput`, `IParticle`, `CloudFrontWebDistribution`, `ScrollRect`, `IMeta`, `IHTMLInjection`, `Destination`, `ISavedObjectsRepository`, `UploadChangeParam`, `VpcSubnetType`, `Events.deactivate`, `ScopedHistory`, `NativeBookmarks.BookmarkTreeNode`, `UpdateRequest`, `ResourceCollection`, `SavedObjectEmbeddableInput`, `ViewPortComponent`, `PutPolicyCommandInput`, `RSTPreviewManager`, `ListConfigurationsRequest`, `WalletObjective`, `ConfigurationSectionEntry`, `ClientException`, `AlertCluster`, `SelectionManager`, `ResizeHandler`, `ForbiddenException`, `ParsedRequest`, `BehaviorTreeStatus`, `SectionMarkerConfig`, `GalleryState`, `AppInstanceJson`, `EditprofileState`, `ImageFormatTypes`, `ICacheEntry`, `HTTPHotspotObject`, `CrochetModule`, `Tsoa.Parameter`, `AWS.ELBv2`, `VariantMatchedResult`, `Compiler`, `IterationTypesResolver`, `py.AST`, `Area2DSW`, `AdInfo`, `CopyOptions`, `StorageLayout`, `LinkedAccountsService`, `WarningLevel`, `CodeGenOptions`, `SpawnHandle`, `NotebookModel`, `QueryStringFilter`, `TaskRoutine`, `NumberSymbols`, `ProposalService`, `HandlerDecorator`, `FilesystemEntry`, `ExtendedObject3D`, `ImGui.Vec4`, `ReducerAction`, `RouterService`, `FluentRules`, `ModuleDependencies`, `PropAliases`, `TableOfContentItem`, `FunctionImportParameters`, `TableConstraint`, `DestinationFetchOptions`, `ScannedClass`, `ParjserBase`, `TooltipOffset`, `ButtonStyles`, `oai3.Model`, `ParameterValues`, `ts.IntersectionTypeNode`, `Ray2d`, `IdentGenerator`, `Percent`, `SModelRoot`, `ContactCardEmbeddable`, `TriangleOrientation`, `RV`, `NodeCore`, `ModalComponentType`, `PartialTypeGuard`, `IAvailabilitySlotsCreateInput`, `HeaderActionIconProps`, `PathElement`, `DeclarationKind`, `EventActionCallable`, `TreeNodeIndex`, `ListNotificationsCommandInput`, `UntagResourceResult`, `NumbersImpl`, `NodeJS.Signals`, `TexImageSource`, `ListResponseModel`, `BIP32Interface`, `TSource`, `IImageAsset`, `System`, `ChannelChainInfo`, `ast.NodeTag`, `A11yConfig`, `AppContext`, `TimeseriesDataRecord`, `AuthHttp`, `TooltipProps`, `SKColor`, `ActualTextMarker`, `EventRegistry`, `MultipleFieldsValidator`, `GetGlobalObjectOptions`, `FluidObject`, `IUsedState`, `gang`, `IImperativeError`, `FetchData`, `FusedTeamMemberType`, `HeaterState`, `ITypedEdge`, `NumberSchema`, `iNotification`, `jqXHR`, `APIGatewayProxyHandler`, `RegisteredServiceAccessStrategy`, `WaveFile`, `E.Either`, `StagePanelManagerProps`, `zod.infer`, `restify.Server`, `TreeItem`, `ThroughStream`, `ICounter`, `Events.pointermove`, `TargetDiezComponent`, `ConchVector4`, `IMutableFlatGridItem`, `Conv3DTranspose`, `angular.resource.IResourceClass`, `SyncOpts`, `EventUiHash`, `FakeProviderConnection`, `NextComponentType`, `IUserState`, `ReactionCanHandleOptions`, `Re`, `WalletStateType`, `GXMaterial`, `Verification`, `EdgeCalculator`, `Exhibition`, `NetworkService`, `AddressFormat`, `ExecutableItemWrapper`, `ChildNodeType`, `NewObjectOptions`, `ExtensionModule`, `NodeKeyJSON`, `TsSelectedFile`, `IPass`, `SassError`, `CodeModExports`, `TestStatus`, `NavMenu`, `TablePipeline`, `EnrollmentAPIKey`, `DeleteAliasCommandInput`, `QuerySubmitContext`, `NewBalanceFn`, `SubCategory`, `DeviceCreateParams`, `IRegularAttr`, `OnePageDataInternal`, `MultiSigSpendingConditionOpts`, `ESFixedInterval`, `SetStateCommitment`, `V2SubgraphPool`, `IDataFilterValueInfo`, `Redis.RedisOptions`, `ManifestApplication`, `PathTree`, `MediaObserver`, `lf.schema.Column`, `BlobDownloadResponseParsed`, `AuthCredential`, `Slack.Message`, `From`, `PolicyProxyHookOptions`, `SingleVertexInputLayout`, `FirebaseFirestore.CollectionReference`, `EffectiveTypeResult`, `CmsIndexEntry`, `StatefulChatClientOptions`, `ActionMetadata`, `MuteRoomTrackResponse`, `GroupService`, `V1Secret`, `ColumnState`, `TokenStore`, `StopItem`, `CreateSiteCommandInput`, `GoalKPI`, `Mission`, `SharedFunctionStub`, `AddressListItem`, `AndroidProject`, `IConstructor`, `FTP`, `GlobalNames`, `PartitionSmallMultiplesModel`, `TextInputLayout`, `IAppError`, `IGenerateReleaseNotesOptions`, `StdioOptions`, `ChannelEffects`, `CdkDrag`, `TaskFunction`, `FieldArrayWithId`, `InfectableParticle`, `SerializedBoard`, `TipLengthCalibration`, `DiffParser`, `AttendanceService`, `SolflareWallet`, `LabelPropertyDataFilterer`, `DefaultEditorAggAddProps`, `ILayoutState`, `SceneParams`, `PIXI.Sprite`, `ElementSize`, `Section`, `ThemeProperty`, `sdk.SessionEventArgs`, `BleepsSetup`, `MainTab`, `TsInterfaceInfo`, `PromiseType`, `OriginConfig`, `ZebuLanguage`, `ISerializedInterval`, `HttpClientResponse`, `Bitstream`, `FaunaDBClient`, `VpcData`, `TimePickerProps`, `SlashCommandStringOption`, `GenericOneValue`, `GeneratorManifest`, `ResolutionHelper`, `TheRdsProxyStack`, `TypeInfo`, `MiddlewareAPI`, `PropertyValues`, `ExplorerExtender`, `PasswordService`, `URLMeaningfulParts`, `requests.ListIncidentsRequest`, `GeoPointInput`, `Security2CCNonceReport`, `DiagnosticRelatedInfo`, `BizResponse`, `StatusNotification.Status`, `VPC`, `InternalsImpl`, `GetRegexPatternSetCommandInput`, `IAnimatable`, `AbstractColumn`, `PackageTreeItem`, `THREE.DataTexture`, `UseCaseFunction`, `CrudFeatures`, `IPackageFile`, `GraphWorkspaceSavedObject`, `IInboundSignalMessage`, `DraftArray`, `Compose`, `Y.XmlText`, `MapOfType`, `Pose`, `BitbucketAuthResponse`, `AxisOrientation`, `RecoilState`, `WrapperOptions`, `ServiceRepresentation`, `BulletViewModel`, `Cycle`, `MenuMapEntry`, `ISetBreakpointsArgs`, `ITrackWFeatures`, `Statement`, `IBatteryCollectionItem`, `IKLink`, `Mountable`, `GetSpaceParams`, `AzureDevOpsOpts`, `IPaginationProps`, `ToneConstantSource`, `CarsService`, `GraphQLContext`, `CompilerEventBuildLog`, `PostInfo`, `AppCheck`, `TestBufferLine`, `UiSchema`, `Peak`, `U2NetPortraitConfig`, `ParameterValue`, `IArticleAction`, `IContentSearchOptions`, `MergeFsResult`, `GeneratedPoint2D`, `IWebsocketMessage`, `ActionHistory`, `PageType`, `WebDNNCPUContext`, `CompilerStyleDoc`, `CustomerLayoutState`, `AddressLabel`, `OnMessageFlags`, `RawSkill`, `AbridgedFormatErrorMetadata`, `TestFunctionImportComplexReturnTypeParameters`, `FiltersActions`, `NamedTypeNodeDef`, `TooltipData`, `LeaseOperationResponse`, `OutputNode`, `EventInstance`, `LaunchConfig`, `DataTableRow`, `UserAction`, `MessagingDeviceResult`, `LegacyDrawing.Animation`, `PathContext`, `IConnextClient`, `EmbeddablePackageState`, `AppSettingsFormValues`, `B4`, `IAddGroupUsersOptions`, `QueueType`, `angular.ICompileService`, `ComputedOptions`, `DescribeCertificateCommandInput`, `SetOperations`, `CommonProps`, `PriorityQueue`, `SessionModel`, `SetupResult`, `ODataModel`, `MaterialGroup`, `ID3Selection`, `NPC`, `SaveResult`, `AssemblyExpressionContext`, `SerialPort`, `ContactDocument`, `Names`, `PinReference`, `firebase.firestore.QueryDocumentSnapshot`, `LSTMLayerArgs`, `Mmenu`, `ScrollBar`, `FragmentDefinition`, `HyperionWorkerDef`, `GatewayTreeItem`, `ScaleConfigs`, `AppMessage`, `StateModel`, `StdSignDoc`, `TrackItem`, `UserRef`, `IAuthenticatedHubSearchOptions`, `ComponentContext`, `MutableVector4d`, `DefaultTallyConfiguration`, `BodyType`, `IUsersRepository`, `Royalty`, `ElfSectionHeader`, `moment.Duration`, `InteractionForegroundService`, `DisplayNameOptions`, `BaseAction`, `CurveExtendMode`, `OutChatPacket`, `AnimationReference`, `FiatCurrency`, `PerformWriteArgs`, `InteractionState`, `TimeSection`, `SnapDB`, `IpPermission`, `BasicProps`, `MultiWord`, `tStringCurrencyUnits`, `GroupProps`, `ValidationState`, `Conv1D`, `SocketAddress`, `App.SetupModule`, `__SerdeContext`, `DateRange`, `requests.ListExternalDatabaseConnectorsRequest`, `IMatcherFunction`, `LabelDoc`, `monaco.editor.IModelDeltaDecoration`, `IDisposer`, `TeamMembershipProps`, `SMTFunction`, `D3Service`, `UpdateCustomVerificationEmailTemplateCommandInput`, `CertificateAuthorityLifecycleState`, `MockMember`, `IStateMachine`, `DeleteCampaignCommandInput`, `FaunaRef`, `SnapshotQuotaExceededFault`, `TocItem`, `FlowDocument`, `RefsDetails`, `tfc.io.ModelArtifacts`, `DescribeEngineDefaultParametersCommandInput`, `CSSVarFunction`, `NameValidationError`, `ProblemInfo`, `ModuleMetadata`, `NgForageOptions`, `IEmployee`, `ToastConfigCommon`, `CommandMap`, `IBundle`, `UnicodeBlock`, `PercentLengthType`, `StructuredStorageBaseHelperOptions`, `Counter1`, `QueryCreator`, `AnyEntity`, `StoryContext`, `USampler2DTerm`, `FileInfo`, `sdk.SpeechRecognizer`, `DetectorRecipeDetectorRule`, `TransformerFactory`, `Uint`, `CurrencyFractions`, `msRest.CompositeMapper`, `HookCallback`, `TKeyboardShortcutsMapReadOnly`, `CircleProps`, `FunctionDefinitionConfig`, `IconPosition`, `prng`, `TID`, `GalleryService`, `VdmActionImport`, `FlowPostFinally`, `CachedBuildRequestOptions`, `bitcoin.payments.Payment`, `ListFHIRExportJobsCommandInput`, `WebPhoneSession`, `CandidatePersonalQualitiesService`, `NavigateOptions`, `IPacketHeader`, `SearchProps`, `AbstractMaterialNode`, `coreClient.OperationSpec`, `GameEntityObject`, `SavedObjectsExportTransform`, `url.Url`, `RawMessage`, `FiniteIEnumerator`, `Contributors`, `Hierarchy`, `RnM2BufferView`, `DepthStyleProps`, `PanelActionParams`, `IEpisode`, `IPropertyListDescriptor`, `MergeItem`, `SizeResult`, `IAppointment`, `PageConfig`, `DeletePresetCommandInput`, `IIteratee`, `LazyExoticComponent`, `FMAT`, `SearchType`, `ITopic`, `BattleCommitment`, `fromUserActions.GetReviewersStatisticsCollection`, `Slide`, `ParsedFunctionJson`, `SlackMessageArgs`, `ImageSize`, `InterfaceName`, `DefaultTreeNode`, `PlayerType`, `NAVTestObject`, `BlueGreenManifests`, `MouseManager`, `VNodeProperties`, `ObservableVocabulary`, `PromiseWithProgress`, `PCLike`, `DeleteClusterResponse`, `interfaces.Newable`, `Models.LeaseAccessConditions`, `ZosAccessor`, `BufferState`, `NullableT`, `InteractionManager`, `sdk.ConversationTranslator`, `TypeDecorator`, `Lane4`, `IVector`, `StyleErrors`, `ListResult`, `ReleasesClient`, `ts.FunctionLikeDeclaration`, `ts.Type`, `RpcCallParameters`, `ModuleMock`, `messages.GherkinDocument`, `TransformMessage`, `LayerFromTo`, `HashHistoryManager`, `Category`, `VideoTileState`, `IFullItemState`, `BudgetSummary`, `BindingName`, `CustomSkill`, `Starter`, `MaybeProvider`, `Rope`, `TreeItemModel`, `PromiseDelegate`, `WriteConditionalHeadersValidator`, `ICommandBarItemProps`, `SignalListener`, `STMultiSort`, `ModuleName`, `IWarning`, `WaitContext`, `NotifyQueueStore`, `android.content.DialogInterface`, `CohortComposition`, `ts.Signature`, `ReadStream`, `JobExecution`, `ExecutionErrorProperties`, `TaskDefinition`, `PointSeriesColumn`, `TaskDraft`, `InvokeArgument`, `FSPath`, `Memoized`, `HsToastService`, `ClientGrpcProxy`, `TraceId`, `Fund`, `SignalingConn`, `GetInput`, `TranslationString`, `LoginComponent`, `Models.ModifiedAccessConditions`, `MergeEl`, `AlbumEntity`, `Chapter`, `ITagHandler`, `LogAnalyticsSourceMetadataField`, `RX.CommonProps`, `DataResolverOutputHook`, `Materialize.ChipDataObject`, `UserDeposit`, `Datastore.Transaction`, `LoadCallback`, `P2PEnhancedPeerInfo`, `EdgeImmut`, `AnySchemaObject`, `StackItem`, `ChainableTransform`, `IEventHandler`, `TilemapProject`, `SnapshotIn`, `NextService`, `StackInfo`, `Shorthand`, `AuctionViewItem`, `PossiblePromise`, `MdcSnackbarService`, `ACM`, `TabViewItem`, `ScriptDataService`, `CommandInput`, `ViewContainerPart`, `ReferenceNode`, `DelugeTorrent`, `KeyResultUpdate`, `Byte`, `ServiceContainerConfig`, `MerkleTree`, `HookEvent`, `Builders`, `GLintptr`, `d.HydrateDocumentOptions`, `Bridge`, `NotificationInfo`, `ValidationArguments`, `BindingInputBase`, `P2PRequestPacket`, `FlowAssignmentAlias`, `ts.ExpressionWithTypeArguments`, `DeleteRepositoryPolicyCommandInput`, `CalendarFieldsOptions`, `DaffCategoryFilter`, `DocumentUri`, `MatchInfo`, `ListenerFunction`, `MTD`, `Target`, `StyleManagerService`, `FeatureService`, `Agreement`, `ScaleTime`, `ConvexPolygon2d`, `FileOptions`, `OpenSearchClient`, `HMACKey`, `Learnset`, `TemplateParameter`, `EventBody`, `FormElement`, `MyDirectoryTree`, `Species`, `AudioModule`, `NetworkDiff`, `CliManipulator`, `RelativePlaceAnchor`, `StringifyOptions`, `LegacyOpenSearchError`, `ParserRuleContext`, `Arguments`, `RuleObject`, `RequestApprovalService`, `IDynoCollectionKeyValue`, `GitFileChange`, `HTMLElement`, `Stop`, `FormConfigProps`, `TypeScriptConfigurationBuilder`, `IMP4AudioSampleEntry`, `ServiceDownloadProvider`, `PlayerViewState`, `RiskViewEntry`, `InvalidParameterCombinationException`, `ThingView`, `PhysicsCollider`, `TooltipOperatorMenu`, `ReturnTypes`, `BridgeProtocol`, `SelectInfo`, `TinaFieldInner`, `CSSStyleRule`, `ColorInput`, `Utils`, `HeaderBag`, `ArraySchema`, `ChainInfoWithEmbed`, `AppStateTree`, `QueryResolvers.Resolvers`, `ErrorUtilitiesService`, `IHooks`, `SeparableConv2D`, `GraphQLEnumValueConfigMap`, `CanvasDepth`, `Locales`, `CacheAdapter`, `Coupon`, `CheckerResult`, `GunMsgCb`, `TestClass`, `BrowserNode`, `CustomRequest`, `ListJobsResponse`, `BrandModuleBase`, `DebugProtocol.Message`, `CodeQualityInformation`, `CreateOperation`, `RumPerformanceResourceTiming`, `WebGLCoreQuadOperation`, `ts.ImportSpecifier`, `TestChannel`, `CaseItem`, `BitMap`, `ReconnectingWebsocket`, `IReducers`, `PaperSource`, `SourceInformation`, `DeviceSelector`, `LiteloaderVersion`, `INorm`, `DateWidget`, `DialogData`, `IArmy`, `ContainerRuntime`, `GUITheme`, `ModbusConnection`, `UnidirectionalTransferAppAction`, `IProjectMetadata`, `IAccountDataStore`, `CLM.AppBase`, `TypographStyle`, `UserAgent`, `QueryDeploymentsRequest`, `PhysicalTextureType`, `SaveDialogReturnValue`, `vscode.DebugAdapterExecutable`, `IStep`, `SchemaDifference`, `DaffProductDriverResponse`, `DecodingTransformer`, `V1ExpressionModel`, `CompletionItemKind`, `FBSDKSharing`, `Angulartics2GoogleAnalytics`, `RectangleNode`, `NetworkInfo`, `DitherKernel`, `WeakGenerativeCache`, `ICached`, `QualityLevel`, `ProofRequest`, `NotificationsService`, `Def`, `Dispatched`, `WlDocs`, `Database.User`, `GasTokenValidator`, `ReadonlyVec2`, `GT`, `angular.IWindowService`, `ConnectionDataEnvelope`, `DirType`, `IDeploymentCenterPublishingContext`, `FieldElement`, `NonArpeggiate`, `ClassFacts`, `PermissionItem`, `OutputTargetDocsJson`, `SFCBlock`, `LongHeader`, `DatabasePool`, `IdentityIndex`, `IndexType`, `IPartitionLambdaConfig`, `ResourceNotFoundFault`, `CalendarType`, `IListFormResult`, `PointerOverEvent`, `MultiLineStringDataVariant`, `ContactEmail`, `NoInputAndOutputCommandInput`, `TaskExecution`, `ExtendedClient`, `PGTransform`, `UnknownError`, `ControlInterface`, `TimeOpStatementContext`, `SidebarMenuItem`, `NetworkRequestInfo`, `IntermediateToken`, `ResourceLimitExceededException`, `GenericComboBoxProps`, `Traversable2`, `PluginFunction`, `IConsoleResponse`, `I18nService`, `IArtTextCacheData`, `ModifyDBParameterGroupCommandInput`, `requests.UpdateConnectionRequest`, `IBaseTransaction`, `NetconfForm`, `FalsyPipe`, `InitStoreState`, `Matrix2D`, `Service$`, `ModuleBase`, `UserMembership`, `ConverterContext.Types`, `OutgoingSSNResetRequestParam`, `ConvertComponent`, `DateRangeValuesModel`, `DaffCartReducerState`, `ThemeGetter`, `AnimationEvent_2`, `R.Morphism`, `PipelineResult`, `SupRuntime.Player`, `ConversionResult`, `GetUserInfoSuccessCallbackResult`, `HttpContextConstructorContract`, `UpdateDataSourceCommandInput`, `PositionalArgument`, `MentionDefaultDataItem`, `QuakemlService`, `RGBAColor`, `GeoInput`, `DefaultAnchors`, `IFieldProps`, `RendererStyleFlags2`, `GetConnection`, `HTMLIonRadioElement`, `FormState`, `StoredTransaction`, `SearchOptionModel`, `LoggerInterface`, `CTransactionSegWit`, `FirmaWalletService`, `MockAdapter`, `MongoDB.Filter`, `BulkApplyResourceAction`, `MDCTabScrollerAdapter`, `ArtifactFilePaths`, `config.Data`, `Refinement`, `GroupedRequests`, `ListResourcesCommandInput`, `KeyModifierModel`, `Subst`, `TransformOptions`, `SpacesServiceStart`, `TransmartSubSelectionConstraint`, `CID`, `CurrentHub`, `Color4`, `AppNotification`, `IApiOperation`, `DeveloperExamplesPlugin`, `TransportEvent`, `FieldBase`, `ExtensionManager`, `ParsedArgs`, `BullBoardQueues`, `PlayerContext`, `SettingsContextProps`, `TxHash`, `ethers.Contract`, `guildInterface`, `SearchDetails`, `PartnersState`, `Cypress.ObjectLike`, `GetJobResponse`, `GX.TevScale`, `IElem`, `UnitHelper`, `LocalStorageAppenderConfiguration`, `DirResult`, `MeetingAdapterState`, `FleetStartServices`, `KeyedTemplate`, `B16`, `Heater`, `Breakpoint`, `QuestionDotToken`, `TiledObject`, `GlobalLogger`, `IMatches`, `DataViewHierarchy`, `Doctor`, `NEOONEProvider`, `Dungeon`, `TmdbMovieDetails`, `GToasterOptions`, `NgxGalleryOptions`, `StackHeaderInterpolationProps`, `LanguageOption`, `ResourceIdentifier`, `PutScalingPolicyCommandInput`, `DP`, `PromptType`, `turfHelpers.Feature`, `AlertingAuthorization`, `WorkerFunction`, `WizardStep`, `IWireMessage`, `ResourceReturn`, `MetadataError`, `Indexer`, `SpeechRecognitionResult`, `AsyncIterable`, `VideoListQueryDto`, `ThrottlingException`, `TFLiteWebModelRunner`, `IApplicationHealthStateFilter`, `ClientError`, `VoiceFocusSpec`, `ComponentHTTPClient`, `ALong`, `PreprocessingData`, `protocol.FileRequestArgs`, `TextEditorDecorationType`, `OpenChannelEvent`, `UrlConfig`, `HeadConfig`, `EventQueueItem`, `Int8`, `ItemT`, `FunctionObject`, `BentleyCloudRpcParams`, `CssToken`, `vscode.FormattingOptions`, `OpenEdgeConfig`, `PatchResult`, `messages.FeatureChild`, `AudioContext`, `StoreST`, `ARecord`, `DeleteVolumeCommandInput`, `KubeContext`, `ITimeOffPolicy`, `GaxiosOptions`, `BindingDirection`, `UserInterface`, `StorageInfo`, `ViewService`, `FSNode`, `StepBinding`, `DirectionConstant`, `DragactLayoutItem`, `DeleteUserRequest`, `SelectableValue`, `KeyValue`, `JsonDocsMethodReturn`, `DataSourceItemGroup`, `JwtKeyMapping`, `MouseEventInit`, `socketIo.Socket`, `EdgeConfig`, `CustomControlItem`, `ComboTree`, `Darknode`, `CppBuildTask`, `Diff`, `TradeContext`, `AuxPartition`, `EntitySchema`, `TemporalArgs`, `NzNotificationRef`, `AssetMap`, `Pet`, `HardwareConfiguration`, `NodeID`, `GlimmerAnalyzer`, `Security`, `ParentContexts`, `cc.Button`, `AlertExecutorOptions`, `IndexedPolyfaceVisitor`, `SqrlConstantSlot`, `ArrayBufferReference`, `requests.ListUserAssessmentsRequest`, `TwitchChatMock`, `requests.ListComputeCapacityReservationsRequest`, `Initialized`, `DueReturn`, `NetworkKeys`, `SpeechGenerator`, `MatchingFunc`, `d.ConfigFlags`, `Output`, `RuntimeTransaction`, `IntentSchema`, `Configurations`, `Timezone`, `TranspileResult`, `Edit`, `ClusterService`, `FileWatcherCallback`, `Nil`, `types.CodeError`, `WWAData`, `PAT0`, `XhrRequest`, `NavigatorGamepad`, `ISideEffectsPayload`, `GX.TexFormat`, `DropEvent`, `ESLToggleable`, `IRealtimeEdit`, `ConceptTypeDecl`, `Reply`, `ClickEvent`, `CoreTheme`, `MultilineTextLayout`, `OrderDetailService`, `Production`, `IAuthOptions`, `ILog`, `Bar`, `PairSet`, `NodeChildAssociationEntry`, `ItemEventData`, `CodeEditor.IEditor`, `IntegrationCalendar`, `PopupComponent`, `ContractDefinitionContext`, `LocationStrategy`, `TKeyArgs`, `SlotStatus`, `IdeaId`, `IsInstance`, `DBQuery`, `InputDataConfig`, `Config.Path`, `ContentNode`, `UIAnalytics`, `StringContext`, `ISpecialStory`, `AllocationUpdatedArg`, `DataTable.Column`, `IGitProgressInfo`, `CharSet`, `CursorPopupInfo`, `UnsupportedBrowsers`, `ConnectionDetails`, `IQuery`, `RustPanic`, `UtilService`, `PDFContentStream`, `MatIconRegistry`, `DownloadJob`, `JoinMode`, `AbstractContract`, `ITerminalContext`, `LifecycleRule`, `thrift.TList`, `BMDData`, `selectorParser.Node`, `RouteCache`, `GenericModel`, `CanvasLayerModel`, `JQueryStatic`, `Yoga.YogaNode`, `PdbStatusDetails`, `IChannelState`, `PathState`, `WorkspaceFolderContext`, `ModelConstructorInterface`, `SendPropValue`, `IConfirmedTransaction`, `AttrMap`, `PolylineProps`, `CompoundStatementListContext`, `JupyterLabPlugin`, `cpptools.Client`, `FakeShadowsocksServer`, `CodeChangedEvent`, `InternalOpExecutor`, `RPCPayload`, `IExportFormat`, `DescribeImageVersionCommandInput`, `TokenAddressMap`, `BookStoreService`, `ex.PreCollisionEvent`, `ParamsSpec`, `CreateDBClusterSnapshotCommandInput`, `RegisterX86`, `AreaNode`, `TaskCacheSession`, `OmvFilterDescription`, `AppResourcesModel`, `ApplicationGateway`, `DiagnosticSink`, `PutItemInput`, `MockDeviceManager`, `SharedArrayBuffer`, `BaseHistory`, `Aspects`, `Environment`, `TinaCloudCollectionEnriched`, `DomModule`, `MultiKeyStoreInfoWithSelectedElem`, `TransactionOrKnex`, `SocialSharing`, `Overlord`, `CreateDBClusterEndpointCommandInput`, `Screenshot`, `AxisConfig`, `UserMetadata`, `UIViewController`, `RemovePermissionCommandInput`, `SitemapXmpOpts`, `RDQuery`, `ExchangePriceService`, `IoLog`, `FinalizeHandler`, `WebSocketSubject`, `DropTargetSpec`, `Intl.NumberFormatPart`, `NzNoAnimationDirective`, `DropViewNode`, `CircleModel`, `OrganizationalUnitResource`, `GfxInputStateP_GL`, `BSPNode`, `BlockMarketCategory`, `AwsS3PutObjectOptions`, `XNA_Texture2D`, `ProtocolExecutionFlow`, `LuaDebug`, `VRMFirstPerson`, `OpenSearchDashboardsReactPlugin`, `TokenContext`, `IGenericObject`, `KeyConnectorService`, `VideoSource`, `TilePath`, `UserResponse`, `BuildingColorTheme`, `Multiplexer`, `JsonDiffNode`, `ConditionalTransferUnlockedEventData`, `ShaderProgram`, `NoteContent`, `Mat`, `BulletOption`, `ComponentDocument`, `NodeInjectorFactory`, `CalendarUnit`, `WorkerTestHarness`, `ModifierType`, `CounterDriver`, `XAudioBuffer`, `NavigationProvider`, `PlannedOrganizationalUnit`, `ValidationChain`, `YieldEveryOptions`, `PointerPosition`, `UploadInfo`, `ComponentInfo`, `IWorkflowExecuteAdditionalData`, `ContractPrincipalCV`, `ImportRules`, `types.FormatTransfer`, `ContractCallResults`, `FabricSmartContractDefinition`, `HdBitcoinCashPaymentsConfig`, `GnosisSafeContract`, `JPACVersion`, `DaffCartTotal`, `TransactionBase`, `PredicateModel`, `MilkdownPlugin`, `OptionsMap`, `CommunOptions`, `PropsFromRedux`, `ApiTypes.Feed.Like`, `AngularFireObject`, `PoolData`, `SendableMsgBody`, `MatchingRoute`, `DescribeReplicationInstancesCommandInput`, `App.Context`, `DeviceManagerState`, `ListTagsForResourceCommandOutput`, `RRect`, `IsolationStrategy`, `ParamDef`, `IDataFilterResult`, `Field_Group`, `ShareButtonsConfig`, `amqplib.Options.Publish`, `CategoryItem`, `ComponentServer`, `EditorEvent`, `DeleteUserCommand`, `JsonPath.ExpressionNode`, `MainProps`, `RpcClient`, `BackupDestinationDetails`, `NodeEventTypes`, `MissingError`, `CreateMigrationDetails`, `MinimalViewPortConfig`, `StudioModelData`, `ListProjectsCommandOutput`, `VariableDeclarator`, `SMTExp`, `ProofMateItem`, `NodeType`, `DataConvertType`, `ThyPopover`, `Hideable`, `CellProps`, `IServerModel`, `IPersistence`, `Neovim`, `TestStateBase`, `PolicyResult`, `requests.ListInstanceagentAvailablePluginsRequest`, `MyState`, `IProcedure`, `ExpNumBop`, `HsSensorUnit`, `DeploymentTable`, `IdentityMap`, `HandlerContext`, `Ok`, `MetaverseService`, `TensorListMap`, `TEntityRecord`, `WithItemNode`, `InputManager`, `NumberNodeParams`, `InMenuEvent`, `ConstantBackoff`, `NoopExporter`, `RulesetVariable`, `TimelinePoint`, `ConfigureLogsCommandInput`, `angular.IPromise`, `t.CallExpression`, `ComponentLoaderFactory`, `GetPropertiesResponse`, `CommandConfig`, `JassTimer`, `ExtremaOptions`, `BindGroupLayout`, `AbiItemModel`, `IExtensionActivationResult`, `ClassStruct`, `ModelLifecycleState`, `AliasHierarchyVisitor`, `WsHttpService`, `PageBuilderContextObject`, `Attributions`, `IValidatorConfig`, `JSXElementAnalysis`, `L13Element`, `IconInfo`, `Transaction.Info`, `UpgradePlugin`, `Comp`, `HttpRequest`, `cdk.GetContextValueResult`, `ICategoryBin`, `AndroidAction`, `DangerResults`, `TextEdit`, `RewardTicket`, `ObjectTypeDefinitionNode`, `AssertTrue`, `CallbackFunction`, `MDCChipActionAttributes`, `MatchedRoute`, `TextDelta`, `ITransport`, `GreenBean`, `DocumentSettings`, `Message`, `ClientSocket`, `SignatureProvider`, `SpecialKeyMatchResult`, `HTMLSourceElement`, `CreateGroupCommand`, `specificity.Specificity`, `RoleState`, `TypeWithInfo`, `Start`, `MeshData`, `ChatThreadClientState`, `LimitItem`, `Direction`, `IConnections`, `FormatCodeOptions`, `CdsInternalOverlay`, `ScriptLikeTypes`, `Fork.Fork`, `WebKitEntry`, `ApplicationStateMeta`, `ReBond`, `ConceptServer`, `WebGLSampler`, `NoOpStep`, `EntireGame`, `amqplib.ConfirmChannel`, `SlackOptions`, `IFunctionIdentifier`, `RegisterParams`, `Renderer2`, `IOriginNode`, `d3Selection.Selection`, `AnalyticsProperties`, `RepoNameType`, `CategorySummary`, `MultiMap`, `InfiniteScrollDirective`, `JSONCacheNode`, `Drawable`, `ScalarCriteriaNode`, `VulnerabilityAssessmentPolicyBaselineName`, `SourceNodesArgs`, `iam.Role`, `PDFCrossRefStream`, `CheckSearchSessionsDeps`, `AsyncArrayCallback`, `DefaultReq`, `Level3`, `XMenuNode`, `G6Event`, `CommentKind`, `VariantHandler`, `MethodDocumentationBlock`, `Outline`, `Ref`, `VariableExpression`, `WKNavigation`, `WriteValueOptions`, `BodyAndHeaders`, `SEErrorRefresh`, `BillDebtor`, `ServiceSpy`, `InternalCoreSetup`, `FeeOption`, `TreeModelSource`, `CarouselConfig`, `EngineResponse`, `WorldCoordinates`, `SystemIconProps`, `Crdp.Runtime.StackTrace`, `ParseQueryOutput`, `BitbucketUserRepository`, `NetworkDefinition`, `ScheduledCommandInfo`, `CoingeckoApiInterface`, `SeriesConfig`, `ExtrudedPolygonTechnique`, `SearchableContainerInput`, `LoggerProxy`, `RLYTTextureMatrix`, `TaskQueue`, `REPLServer`, `NormalizedVertex`, `Expression`, `StateLeaf`, `AxiosResponse`, `TextEditorSelectionChangeEvent`, `LucidModel`, `PutRetentionPolicyCommandInput`, `UpdateTargetDetectorRecipe`, `PositionContext`, `TrackerEvent`, `mod.TargetGroup`, `messages.Feature`, `BlockAtom`, `StructureRoad`, `HapiAdapter`, `AnyCurve`, `TrackedImportFrom`, `MessageData`, `TransmartDimension`, `ElMessageBoxOptions`, `ThyTableColumnComponent`, `FoamGraph`, `ApiProxy`, `Contracts`, `FoldersService`, `SvgIconProps`, `IDistro`, `StoreView`, `AvatarOverload`, `skate.Component`, `SelectProps`, `VoilaGridStackPanel`, `Interval`, `requests.GetWorkRequestRequest`, `PointInfo`, `ActionEvent`, `UseLazyQueryReducerAction`, `IDSLCodeState`, `CellDrag`, `PrivilegeFormCalculator`, `IdQuery`, `TypeConsApp`, `ShadowController`, `MeaningfulDependency`, `CreateObservableOptions`, `Line2`, `MockStream`, `ReduxAppState`, `AttrEvaluationContext`, `StateAction`, `SqlManagementClient`, `ExtUser`, `http.OutgoingHttpHeaders`, `TestViewController`, `ProjectDto`, `VCSConnector`, `TScheduleData`, `AggParamsAction`, `MediaStreamAudioSourceNode`, `XYZNumberValues`, `CaseNode`, `AuthPermissions`, `ILogService`, `com.google.firebase.firestore.FirebaseFirestoreException`, `MenuApiResult`, `KeystrokeAction`, `RelationClassDecorator`, `GrpcResponseMessageData`, `TemplateChildNode`, `ElementProperty`, `VideoPlayer`, `ILayerDefinition`, `requests.ListDedicatedVmHostsRequest`, `HeadingSize`, `ProofCommand`, `TodoState`, `DMMFPAS_Directives`, `InsertDelta`, `SpyTransport`, `Base64`, `PersonService`, `ValueToken`, `Polygon`, `Shell`, `PathStyleProps`, `IGetContentOptions`, `ISettingsState`, `RLYTPaneBase`, `DataTypeFieldConfig`, `IBaseImageryPluginConstructor`, `IPluginOptions`, `MachinomyOptions`, `TemplateState`, `TokensBuffer`, `ToplevelT`, `SwitchStatement`, `CalendarData`, `HitDatabaseEntry`, `Table`, `LatestControllerConfigType`, `CropperTouch`, `ChatErrorTarget`, `CallbackDisposable`, `IColorableSequence`, `NotifyOpts`, `HSLColor`, `AWSLambda.Context`, `MetricResult`, `requests.ListIPSecConnectionTunnelRoutesRequest`, `ContractDefinition`, `commonLib.IExtra`, `Directive`, `AuthScopeValues`, `ReactRef`, `IDateRange`, `config`, `SpeakerInfo`, `FileAccessData`, `MatDialogConfig`, `Pipette`, `ITestFluidObject`, `EventInitDict`, `IComputedValue`, `DialogInput`, `IMarkerData`, `UnitType`, `Texture_t`, `Badge`, `TransformFactoryContext`, `DaffPaypalReducerState`, `UseTransactionQuery`, `Inspection`, `KeyHandler`, `UiLanguage`, `GX.CullMode`, `AsyncThunkPayloadCreator`, `PartialBot`, `CopyTranslateResult`, `ProjectInformation`, `ITionPlatformConfig`, `DecodedSignature`, `ModalManager`, `Agency`, `NamedImports`, `AllPackages`, `LocationReference`, `BackstageItemState`, `IDataObject`, `BrandService`, `DeleteInstanceCommandInput`, `Allure`, `PipelineStageUnitAction`, `LexContext`, `OfficeFunction`, `EvalResponse`, `RowFormatter`, `ThemeName`, `EmusakEmulatorsKind`, `ContractAddressOrInstance`, `IOdspAuthRequestInfo`, `TextureId`, `Tensor4D`, `NavigationLocation`, `StorefrontApiContext`, `IClothingStore`, `RouteDependencies`, `ISettingsDataStorePayload`, `StorageContainer`, `IApiInfo`, `DeleteParameterGroupCommandInput`, `RadixTreeNode`, `ISelEnv`, `MacroHandler`, `TargetGroup`, `TimelineKeyframeStyle`, `OAuthTokenResponse`, `NumberContext`, `ExpressLikeRequest`, `NetworkFilter`, `DescribeAutoScalingGroupsCommandInput`, `ImageEffectDirector`, `DictionaryKeyEntryNode`, `StructResult`, `LogMatchRule`, `DocumentMigrator`, `SavedObjectsService`, `RequestBuilder`, `HSD_TECnst`, `DesignedState`, `FacadeConverter`, `MockedRequest`, `Levels`, `Http`, `TTypeName`, `NavigateFunction`, `d.MsgToWorker`, `ScriptCache`, `GitHub`, `NodeSnapshot`, `QueryOpts`, `IMenuState`, `MDCTextFieldOutlineAdapter`, `PartSymbol`, `BasicScene`, `BitcoinishPaymentTx`, `AstExprState`, `RootDispatch`, `types.NestedCSSProperties`, `ReadModelRequestEnvelope`, `TemplateClient`, `BackupSummary`, `ValidateFn`, `MgtTemplateProps`, `ObjectValue`, `WorkflowStatus`, `SuitDone`, `FileEntity`, `SwapParams`, `EffectHandlers`, `NodeContainer`, `requests.ListCrossconnectPortSpeedShapesRequest`, `AnnotationRectProps`, `MarkerDoc`, `IWalletContractServiceStrategy`, `IPackageJson`, `ThyTooltipDirective`, `OutputTargetDistCustomElementsBundle`, `IParsedPackageNameOrError`, `Directories`, `IWorldObject`, `SynthesisVoice`, `requests.ListIPSecConnectionTunnelsRequest`, `CdkToolkit`, `DynamicEllipseDrawerService`, `KeyboardDefinitionSchema`, `CursorDirection`, `PreviewDataImage`, `TreeNodeInBlock`, `FoodsFilter`, `IInspectorListItem`, `UpdateChanges`, `EitherAsync`, `ParamContext`, `ZonesManager`, `ServerStyleSheets`, `StripePaymentSession`, `FolderPreferenceProvider`, `Break`, `DraggableInfo`, `TypedColor`, `webpack.Compilation`, `FieldNamePath`, `OrganizationPostData`, `RequestPolicy`, `ProviderResult`, `SprottyDiagramIdentifier`, `TransliterationFlashcardFieldName`, `Types.SocPromise`, `Answer`, `PiInstance`, `ts.CompilerHost`, `OutlineCreateTag`, `LitecoinAddressFormat`, `AudioResource`, `IFunctionIndex`, `Services`, `NotificationsState`, `FallbackProps`, `IRelatedEntities`, `BootJsonData`, `NamedTensor`, `BatchWriteRequest`, `DecoderOptions`, `RouteInfo`, `NativeCallback`, `MenuPositionY`, `ThumborMapper`, `IERC20ServiceInterface`, `MigrateOptions`, `PutPublicAccessBlockCommandInput`, `TypeWithId`, `MalType`, `ITexture`, `TheTask`, `Sender`, `MetricModalProps`, `JsonRpcResponse`, `W4`, `TokenEndpointResponse`, `WorkflowMap`, `CreatePhotoDto`, `React.TransitionEvent`, `KeyResultTemplate`, `BranchInfo`, `ComponentCompilerPropertyComplexType`, `ts.CallExpression`, `CreatedTheme`, `SectionModel`, `Yaz0DecompressorWASM`, `requests.ListSecretBundleVersionsRequest`, `IUserProfileViewState`, `Database.Replica`, `ConfirmProps`, `ActionService`, `FunctionSignature`, `LogAnalyticsParserFunction`, `LoginAccountsValidationResult`, `LegendEntry`, `Quadrant`, `perftools.profiles.IProfile`, `PositionTranslate`, `iI18nConf`, `BinaryShape`, `AType`, `ResourceFile`, `SaveManager`, `serializedNodeWithId`, `UrlState`, `Int64Value`, `Warrior`, `XYChartScrollbar`, `Headers`, `IUILayoutViewController`, `Field.PatchArgs`, `EventTouch`, `AuthorizationPayload`, `LayoutComponent`, `ListPolicyVersionsCommandInput`, `Range1d`, `MotionInstance`, `TransformerHandle`, `OrderedSet`, `PackageEntry`, `ICandidateCreateInput`, `ToolbarItemsManager`, `TimefilterContract`, `ConsumerExtInfo`, `AddressBook`, `GitHubRepo`, `BlendOperation`, `ITransactionRequestConfig`, `IncompleteSubtypeInfo`, `SortedPatchList`, `TypeResolvingContext`, `NetworkRequestId`, `TreeDiagramNode`, `SensorType`, `ConvoState`, `InfoType`, `IServerFS`, `InputEventMouseMotion`, `SyntaxModifier`, `TKeys`, `CdsButton`, `DATA`, `cToken`, `LiteralType`, `TextContextTypeConvert`, `UseContextStore`, `CustomSecurityService`, `EmojiType`, `GridCellBox`, `ResponseData`, `Render`, `ContainerWarning`, `TSettings`, `SwapFn`, `GX.CA`, `PromiseOr`, `yauzl.Entry`, `DaffProductFactory`, `StructDeclaration`, `RTCRtpSimulcastParameters`, `VectorLike`, `AuthReducerState`, `next.Origin`, `Suggestion`, `InetLocation`, `IGLTF`, `TileContentRequestProps`, `code.Range`, `NgmslibService`, `SagaGenerator`, `listenerHandler`, `ClassDescription`, `NativeClarityBinProvider`, `PIXI.Point`, `MiddlewareResultFactory`, `StringAsciiCV`, `PinModelData`, `GX.IndTexStageID`, `ServiceResponse`, `Int`, `ParticipantInfo`, `Cli`, `LeftCenterRight`, `FormFieldProps`, `StyleSheetData`, `IPumpjack`, `apiClient.APIClient`, `BuildVariables`, `IFileRequest`, `ChannelPresenceEvent`, `ValueKey`, `SearchServiceSetupDependencies`, `angular.ui.IStateParamsService`, `ZenObservable.Observer`, `MapObjectAdapter`, `VertexBuffer`, `DeleteArchiveCommandInput`, `INpmDependency`, `ColorRgb`, `ApiKeyHandler`, `DebugProtocol.NextResponse`, `ApiDeclaration`, `TransationMessageOrObject`, `api.ISummaryTree`, `ClarityValue`, `ts.BuilderProgram`, `BuildrootUpdateSession`, `NgModuleMetadata`, `SpeciesName`, `HostWithPathOperationCommandInput`, `EnumId`, `StreamableRowPromise`, `LabDirectory`, `SignatureProviderResponseEnvelope`, `AMapService`, `INote`, `ToneOscillatorType`, `CorsOptions`, `GfxSampler`, `IDatabaseApiOptions`, `NativeError`, `IDBPObjectStore`, `TileMapAssetPub`, `ScreenViewport`, `ComplexError`, `ElementContent`, `IDatabaseDataDocument`, `DartDeclarationBlock`, `CandidateFeedbacksService`, `ParamInfoType`, `TicketsState`, `monaco.languages.FormattingOptions`, `SpanContext`, `Events.stop`, `BufferCV`, `ARRotation`, `MDCChipAnimation`, `TSTypeAnnotation`, `MPPointF`, `IPersona`, `CreateDeliverabilityTestReportCommandInput`, `MaskModel`, `IUserOptions`, `IBeaconConfig`, `TexMtx`, `Month`, `TodoTask`, `XmppChatConnectionService`, `DependencyContainer`, `SpaceProps`, `DispatchedAction`, `DocumentPosition`, `DayPeriod`, `EdgeCalculatorHelper`, `ListAssetsCommandInput`, `ReadState`, `Funnel`, `Types.KeyValue`, `CompatibleValue`, `LayoutParams`, `TimeHistory`, `EditableBlock`, `FriendList`, `EventSink`, `TRecursiveCss`, `AvatarService`, `Mutation`, `ILocalizationFile`, `IExcludedRectangle`, `RequestResponseLog`, `ICellData`, `CompilerSystemCreateDirectoryResults`, `LifecyclePolicy`, `LotTypeOption`, `HashEntry`, `SSRMiddleware`, `ThrottlerHelper`, `Tsoa.Metadata`, `HTMLChar`, `CustomQueryModel`, `MultilevelSensorCCReport`, `BinaryType`, `requests.ListDbHomePatchHistoryEntriesRequest`, `IProcessedStyleSet`, `ProviderRange`, `MockPlatform`, `TestFileInfo`, `IFakeFillerOptions`, `StoreOptions`, `PositionDirection`, `DeleteRepositoryCommandInput`, `NodeDecryptionMaterial`, `StringTokenFlags`, `TestMessage`, `AppStackOs`, `SeekProcessor`, `ArgumentInfo`, `ArtifactFrom`, `PixelMapTile`, `HTMLScriptElement`, `OperationMetadata`, `ControlSetItem`, `DIDDocument`, `NodeInputs`, `Node_Struct`, `FlowVariableAnnotation`, `TransactionEnvelope`, `SDLValidationContext`, `ListRetainedMessagesCommandInput`, `ALL_POSSIBLE_CHART_TABS`, `ControllerValidateResult`, `OffersState`, `PairTree`, `EndUserAgreementService`, `SimplePath`, `ValidatedOptions`, `requests.GetRRSetRequest`, `ApmFields`, `LabelCollector`, `ChildExecutor`, `ItemsOwner`, `SelectionsBackup`, `PartialReadonlyContractAbi`, `IWorkerChannelMessage`, `MessageDoc`, `ts.ResolvedModuleFull`, `GraphData`, `NominalTypeSignature`, `TextRangeWithKind`, `FileStorage`, `CoreProcessorOptions`, `PubKey`, `MDNav`, `ScannedMethod`, `ExportedData`, `FabricEnvironmentTreeItem`, `ReadableStreamDefaultController`, `TypeVarScopeId`, `VideoGalleryRemoteParticipant`, `KBN_FIELD_TYPES`, `CoinHostInfo`, `INodeMap`, `UISession`, `PoiTableEntryDef`, `CompilerWatcher`, `PerpMarketInfo`, `ControlType`, `AuthActionTypes`, `StagePanelLocation`, `ParsedResult`, `SavedObjectsMappingProperties`, `Compilation`, `LocaleTree`, `CreateDatasetGroupCommandInput`, `DidactPanel`, `PDFStream`, `Fees`, `EventDoc`, `ISearchDataTemplate`, `CriteriaFilter`, `VpnClientParameters`, `AccountRepositoryLoginResponseLogged_in_user`, `ExchangeContract`, `PNLeaf`, `QueryCommandOutput`, `MatchedSelector`, `PositionLimitOrderID`, `BandcampSearchResult`, `VNodeChild`, `Bytes`, `Field`, `Secured`, `DeleteIntegrationCommandInput`, `CanvasFontSizes`, `ICeloTransaction`, `SelectSeriesHandlerParams`, `d.VNode`, `VisiterStore`, `React.FocusEvent`, `ColdObservable`, `InternalStores`, `WidgetResolveResult`, `SentenceNode`, `RouterConfig`, `ko.Observable`, `CourseStore`, `ExecutableCallRegular`, `Suggester`, `pxtc.ExtensionInfo`, `Cubemap`, `AsyncOrderedHierarchyIterable`, `TestIntegerIterator`, `IPanelProps`, `GltfPreviewPanelInfo`, `CookieOptions`, `RelayerTypes.PayloadEvent`, `ColorLike`, `ITransitionActions`, `ElementStyle`, `AutoUVBox`, `CoursesService`, `ISiteState`, `ChannelHandler`, `OneHotVector`, `ApiError`, `RailsWorkspace`, `HighlighterCellsProps`, `RelationModel`, `MustacheFile`, `IBrowsers`, `PaymentState`, `WebsocketRequestBaseI`, `Measure`, `StateData`, `HashSetStructure`, `TokenSigner`, `DateFilter`, `EventDecorator`, `UnparseIterator`, `ODataSchema`, `Dim`, `DSTInfo`, `Snapshots`, `SqrlParserState`, `VideoDetails`, `AccessTokenInterface`, `PartialGestureState`, `requests.ListAppCatalogSubscriptionsRequest`, `TkmLogger`, `TinyCallContext`, `UpdateExpression`, `FontMetrics`, `CPoolSwap`, `Type_AnyPointer_Parameter`, `MakeHookTestStep`, `License`, `SavedObjectsBaseOptions`, `MessageAttributeValue`, `UnaryFunction`, `CommandOptions`, `VSCodeBlockchainOutputAdapter`, `MatchJoin`, `InstanceKey`, `GitHubRepositoryModel`, `BRepGeometryFunction`, `UseBodilessOverrides`, `BuilderRuntimeNode`, `AstNodeMerger`, `EsmpackOptions`, `android.os.Bundle`, `ConsoleInterface`, `sinon.SinonStatic`, `RpcProgram`, `MapDispatchToPropsParam`, `BriefcaseDbArg`, `SequelizeOptions`, `CreateBotVersionCommandInput`, `DialogPropertySyncItem`, `TextStylePropsPart`, `IWaveFormat`, `MakeRequest`, `SModelRootSchema`, `OperationMethod`, `MIREntityType`, `StandardResponse`, `PropertyASTNode`, `Size`, `SavedObjectsBulkResponse`, `SankeyDiagramNode`, `PDFOperator`, `NzIconService`, `ProjectedXYArray`, `QuestionService`, `ThemeSpec`, `WithName`, `TimesliceMaskConfig`, `BasicRoller`, `Spy`, `TSESTree.Node`, `RedisCommand`, `BusinessAccount`, `SFATexture`, `BoxVo`, `EventSourceHash`, `SlashCreator`, `$N.NeighborEntry`, `CartItem`, `Checksum`, `core.App`, `PiProjection`, `Provider`, `ScannedImport`, `CategorizedOption`, `Interface`, `ArgumentContext`, `IAuthor`, `Appointments.AppointmentProps`, `CmsStructureConfig`, `RemoveGroupControlAction`, `BaseEventOrig`, `UserContext`, `WebAppStack`, `IModelOptions`, `ApiDefinitions`, `SectionItem`, `BirdCount`, `VisualizationProps`, `BinarySensorCCAPI`, `OrderedMap`, `UniqueNameGenerator`, `MigrateFunctionsObject`, `ContentRect`, `d.EntryModule`, `ChatPlugContext`, `FieldAgg`, `Triplet`, `YearProgressService`, `TaskType`, `item`, `CircleResponderModel`, `FormatterSpec`, `FetchedPrices`, `IPCResult`, `StorexHubApi_v0`, `Board`, `LockedGoldInstance`, `EnumHelper`, `SystemMouseCursor`, `GX.TexFilter`, `DebugProtocol.PauseResponse`, `CompilationResult`, `IssueSummary`, `Inner`, `MlRouteProps`, `ContextBinding`, `PutAccountsValidationResult`, `PopulatedFolderDoc`, `FaceletT`, `BatchSerialization`, `PokerHandResult`, `PluginNamingConfiguration`, `RecursiveXmlShapesCommandInput`, `MachineParseResult`, `Rx.Subject`, `TspClient`, `InputParallelism`, `StringAnyMap`, `DAL.DEVICE_ID_LIGHT_SENSOR`, `LoadStrategy`, `cg.Role`, `HealingValue`, `PLSQLSymbol`, `LanguageServerConfig`, `SerializerState`, `DialogOptions`, `EventArgDeclaration`, `DocumentDecoration`, `BrowserWindow`, `ClientAssessments`, `FilePickerBreadcrumbItem`, `FactoryKey`, `Model.Project`, `XmlNode`, `PluginEvent`, `apid.ReserveEncodedOption`, `FragmentSpreadNode`, `Page`, `ts.FormatDiagnosticsHost`, `Diagonal`, `DragPanHandler`, `PackageNode`, `ParsedValue`, `parse5.DefaultTreeDocument`, `SpywareClass`, `WithNumber`, `LoginData`, `IconSize`, `Path3`, `LinkTransport`, `IndexPatternsFetcher`, `ManagementOption`, `Brackets`, `ResponderExecutionStatus`, `TemplatePatcher`, `IModalProps`, `firebase.database.Reference`, `RefreshService`, `ISendOptions`, `OperationArguments`, `ERC1155PackedBalanceMock`, `NothingShape`, `ReactiveEffect`, `MemberMethodDecl`, `ICustomField`, `ElementRunArguments`, `RenderService`, `TargetDetectorRecipe`, `ThyIconRegistry`, `AnimationState`, `IDinoContainerConfig`, `ToastConfig`, `TestStruct`, `INodeWithGlTFExtensions`, `Draw`, `CreateExceptionListItemSchema`, `SelectPartyToSendDelegate`, `IContextLogger`, `StatusPublisher`, `IDatabaseDataAction`, `CheckPrivilegesPayload`, `TypeInference`, `PiNamedElement`, `RefInfo`, `TestERC20Token`, `OperationResponseDetails`, `Vertice`, `ReLU`, `IMatchingCriterions`, `Subscriptions`, `IMyDateModel`, `TCmdData`, `SModelElement`, `StreamPipelineInput`, `DCollection`, `UpdateAppCommandInput`, `Lit`, `SpriteWithDynamicBody`, `NpmFileLocation`, `StringValue`, `IndicatorValuesObject`, `Crdp.Runtime.RemoteObject`, `ZeroExTransactionStruct`, `WS`, `SUPPORTED_FIELD`, `CW20Currency`, `NjsActionData`, `BoxShadowItem`, `BarChartOptions`, `ng.auto.IInjectorService`, `LocalFilter`, `EsQueryAlertParams`, `IInputProps`, `SubscriptionHandler`, `CardTagsProps`, `GroupsGetterFn`, `ColorOp`, `GeneratorResult`, `ts.TransformerFactory`, `DeleteApplicationResponse`, `ChangePassword`, `ListNotebookSessionsRequest`, `FetchLinks`, `FSMCtx`, `AzureTokenCredentialsOptions`, `BasicIteratorResult`, `ValidatorsFunction`, `FluentNavigator`, `ValueConstraint`, `OnModifyForeignAction`, `GeneralStorageType`, `model.Range`, `WorldgenRegistryKey`, `SidenavState`, `ExpressionRenderDefinition`, `Vector4d`, `AtomOptions`, `InventoryStore`, `SVGRenderer`, `Configs`, `ModulePath`, `ListApplicationsCommandInput`, `OPCUAServer`, `QueryByBucketMethod`, `DeleteWorkflowCommandInput`, `GetRowIdFn`, `TextOp`, `Deployment`, `MappingParameters`, `StorageUtility`, `TextDocumentSyncOptions`, `PlatformRef`, `ItemCount`, `TerminalProcess`, `Listeners`, `OwnerKeyInfoType`, `Photo`, `DbResult`, `SxChar`, `WalletProviderInfo`, `SpaceQuery`, `ITableMarker`, `TileDocument`, `GraphRewriteBuilder`, `MultiStepInput`, `IDatabaseDriver`, `VoiceFocusTransformDeviceObserver`, `NSURLSession`, `CollisionStartEvent`, `FeeEstimateResponse`, `Accounts`, `RelationEntry`, `RestyaboardItem`, `HTMLBodyElement`, `LROperation`, `IReaderState`, `ChildGraphItem`, `Vec4`, `BrowserExceptionlessClient`, `ASSymbolType`, `WechatyInterface`, `InterfaceRecursive`, `FlowFlags`, `ESLNote`, `MultisigAddressType`, `GmailResponseFormat`, `ModelSchemaInternal`, `Web3Callback`, `GetConnectionCommandInput`, `TimelineDragEvent`, `TeamWithoutMembers`, `AuthenticateAppleRequest`, `ARAddBoxOptions`, `SortableSpecService`, `OrderTemplatesDetailsPage`, `UpdateExperimentCommandInput`, `MockS3`, `UserRepository`, `Movimiento`, `BaseClusterManager`, `Vector2D`, `InitialArgv`, `Circuit`, `Discussion`, `DeleteResourcePolicyCommand`, `ForumActionType`, `validateTrigger`, `PhysicsHandler`, `puppeteer.ConnectOptions`, `mapTypes.YandexMap`, `CSharpResolversPluginRawConfig`, `ValidationParamSchema`, `grpc.Client`, `InternalServiceError`, `ActionFactoryDefinition`, `TreeModelNode`, `IOSIconResourceConfig`, `VariantCreateInput`, `DomRenderer`, `SnapshotDiff`, `d.DevServer`, `VdmFunctionImportReturnType`, `AvatarSource`, `TestObserver`, `DayOfWeek`, `InitiateResult`, `NgRedux`, `Box2Abs`, `LoaderAttributes`, `ParsedIdToken`, `DeleteAttendeeCommandInput`, `DiagnosticSeverity`, `Trackable`, `IPlDocVariablesDef`, `ɵɵInjectableDef`, `IEBayApiRequest`, `MerchantUserService`, `SnakeheadDataTable`, `Subnet`, `MapRendererParameters`, `QueryDeploymentRequest`, `PersistencyPageRange`, `VisualizationContainerProps`, `EbmlElement`, `ContainerInstance`, `TypedData`, `LGraphCanvas`, `ReacordInstance`, `DocumentTypes`, `FakeDatasetArgs`, `WatchService`, `BuildProps`, `d.HydrateAnchorElement`, `BaseFunction`, `ScoreRecord`, `Validation.Result`, `IRowMarker`, `UnivariateBezier`, `PublicAppDeepLinkInfo`, `PyteaServer`, `RadioButtonViewModel`, `Oscillator`, `TerminalCommandOptions`, `runnerGroup`, `MongoEntity`, `PDFAcroForm`, `ComponentInstance`, `BoundingSphere`, `PatchDocument`, `DatabaseConnection`, `MicrosoftDocumentDbDatabaseAccountsResources`, `EmitResult`, `HttpServerOptions`, `Selectors`, `AbstractHttpAdapter`, `AllocatedNode`, `CurriedFunction5`, `RoomInterface`, `FuncKeywordDefinition`, `CodeGenExecutionItem`, `GaugeEvent`, `EthApi`, `RedioPipe`, `TaskState`, `TNSPath2DBase`, `FABRuntime`, `PageInterface`, `ProcessedPublicActionType`, `ArrayBufferSlice`, `UniversalRouter`, `Uint8ClampedArray`, `SearchResourcesCommandInput`, `PropInfo`, `WorkspaceLeaf`, `InvalidConfig`, `EditorView`, `ThemeTypes`, `IGetEmployeeJobPostInput`, `TemplateResult`, `IDropboxAuth`, `Recordable`, `SynWorkspace`, `AlgWithIssues`, `ParamMetadataArgs`, `VideoTile`, `GameManager`, `HomeState`, `Notification`, `SelectMenuItem`, `ThingDescription`, `ExpressionParseResult`, `ICompilerOptions`, `Pages`, `SelectOptionConfig`, `Viewer.Texture`, `CreateConnectionResponse`, `ApiOperationOptions`, `PluginMetadata`, `QuickFixQueryInformation`, `IAssets`, `SecurityGroup`, `DbLoadCallback`, `DataTablePagerComponent`, `TupleIndexOpNode`, `VersionStatusIdentifier`, `PyTypedInfo`, `CustomFieldDefinition`, `RepositoryEsClient`, `ClipPlaneContainment`, `FragmentDefinitionNode`, `StateCallback`, `PythonShellError`, `PlanNode`, `VariableInfo`, `StepIterator`, `AuthState`, `SWRKey`, `SpreadSheetFacetCfg`, `blockClass`, `IFabricGatewayConnection`, `IDBPCursorWithValue`, `OtherActionsButtonProps`, `SubjectDataSetJoin`, `FindOptions`, `JRPCEngine`, `TypedClassDecorator`, `IViewer`, `EmptyAsyncIterable`, `MouseDownAction`, `ConsensusMessage`, `ExtensionProperty`, `TimeChartSeriesOptions`, `electron.BrowserWindow`, `RectDataLabel`, `T10`, `ContentConfigurator`, `ServerWrapper`, `SubscriptionData`, `KeyPairBitcoinCashPaymentsConfig`, `JumpState`, `JWT`, `Address`, `SessionContent`, `ContentType`, `FieldDef`, `PromiseState`, `TypeAssertionSetValue`, `BinaryMap`, `PartiallyParsedPacket`, `Json.Value`, `GetComponentCommandInput`, `restify.Next`, `SqlTuningAdvisorTaskSummaryReportIndexFindingSummary`, `JavaDeclarationBlock`, `TypeDefs`, `LinkFacebookRequest`, `OcsNewUser`, `BackendDetails`, `d.JsDoc`, `DocSegmentKind`, `DeployStatusExt`, `CreateArticleDto`, `GitInfo`, `AudioBufferSourceNode`, `NextRequest`, `HTMLIonSegmentButtonElement`, `Giveaway`, `NotificationComponent`, `AsyncSystem`, `UiCalculator`, `ValidationProfileExt`, `TeamsMembersState`, `IChannelStorageService`, `AtomId`, `AsyncFluidObjectProvider`, `Jest26Config`, `DirectoryReader`, `DomElementGetter`, `IWorkflowPersona`, `Admin`, `IReferenceSite`, `PackagePolicyInput`, `Odb`, `DebugElement`, `RPCRequestPayload`, `BackgroundFilterOptions`, `ControlBarButtonProps`, `Jenkins`, `GetFindingsCommandInput`, `theia.Task`, `TutorialService`, `Bool`, `ConfigureResponse`, `StorageMeta`, `Pass`, `BackstageManager`, `Progress.ITicks`, `ITemplateBaseItem`, `ITypescriptServiceClient`, `ITableField`, `StreamingClientInfo`, `UseTransactionQueryReducerAction`, `EnumerateType`, `AllMdastConfig`, `NodeJS.WriteStream`, `TlaDocumentInfos`, `RevocationReason`, `AppHistory`, `Artifact`, `WeChatInstance`, `ODataClient`, `IdentNode`, `btRigidBody`, `FoodReducerState`, `SpineHost`, `TypingIndicatorStrings`, `CleanupType`, `ForeignInterface`, `BluetoothServiceUUID`, `RoundArray`, `ConnectionRequest`, `TagType`, `ICodeGenerationOutput`, `Construct`, `requests.ListBdsApiKeysRequest`, `Fault`, `RequestError`, `PackageDependencies`, `TestFrontstage`, `vscode.DocumentFilter`, `GLTexture`, `NumberFormatter`, `ProblemType`, `StringColumn`, `IncomingWalletConfig`, `GachaDetail`, `Deno.Listener`, `FormErrorProps`, `TableListViewProps`, `DescriptorProto_ExtensionRange`, `ILatLng`, `ArangoDB.Collection`, `DidState`, `TData`, `CSSLength`, `RawExpression`, `PrivateEndpointConnection`, `AsyncOperation`, `FilteredHintItem`, `Analysis`, `SwapTable`, `Bracket`, `FlowWildcardImport`, `AxeScanResults`, `SorterResult`, `FaucetConfig`, `Entire`, `InterfaceType`, `CryptoWarsState`, `Sig`, `HeadProps`, `StatusReport`, `SequenceTypes.Participant`, `Highcharts.AnnotationEventEmitter`, `EntityCacheSelector`, `SimulationState`, `GetVpcLinksCommandInput`, `AoptB`, `MetricsGraphicsEventModel`, `AggConfigsOptions`, `TestTracer`, `ModuleInterface`, `SPClientTemplates.FieldSchema_InForm`, `PreConfiguredAction`, `ITreeEntry`, `SortDirection`, `CombineOutputResult`, `_TsxComponentV3`, `RGBA`, `SensorGroup`, `NamedObject`, `DBProperty`, `IFeatures`, `BitcoinPaymentsUtilsConfig`, `IAddOrInviteContext`, `CollectionsService`, `BackendMock`, `Suffix`, `TrackedBuffEvent`, `PeerApiResponse`, `JFlap`, `Equalizer`, `MyComp`, `OpenIdConfig`, `RepositoryCommonSettingDataType`, `GetParseNodes`, `SymbolDataContext`, `HitResult`, `UpdateApiKeyCommandInput`, `GetExportCommandInput`, `HTMLParagraphElement`, `fromRepositoriesStatisticsActions.GetRepositoriesStatisticsCollection`, `CivilHelper`, `ForkStatus`, `LineDataSet`, `GenericMerkleIntervalTreeNode`, `ElementMixin`, `AuthorizationResult`, `ErrorCollection`, `TriumphFlatNode`, `Io.Reader`, `IResizeEvent`, `AudioDeviceInfo`, `AnnounceNumberNumber`, `RepositoryWithGitHubRepository`, `sourceT`, `ObjectMetadata`, `TSpanStyleProps`, `ILaunchSetting`, `LinkSession`, `Participants`, `TagName`, `StrategyParameterType`, `NavTree`, `PlatformBrowser`, `ChartsPluginStart`, `IViewInstance`, `PQueue`, `DetachVolumeCommandInput`, `NexusInputObjectTypeDef`, `FullOptions`, `messages.TableRow`, `BarStyleAccessor`, `CdkDragDrop`, `ScopedDocument`, `ComponentCompilerTypeReference`, `TypeQueryNode`, `SafeResourceUrl`, `FileService`, `EnumInfo`, `Slur`, `ITemplatedComposition`, `MicrofabComponent`, `FileEmbedder`, `ObjectMultiplex`, `ObiDialogNode`, `GetVpcLinkCommandInput`, `ResourceInfo`, `TransitionEvent`, `SASQueryParameters`, `ActionCreatorWithNonInferrablePayload`, `UnorderedStrategy`, `ObjectRelationship`, `TupleCV`, `HistoryOptions`, `DequeueSharedQueueResult`, `AuthEffects`, `StartChannelCommandInput`, `WebAppCollection`, `supertest.Test`, `InformedOpenLink`, `DownloadStationTask`, `UpdateInfo`, `com.stripe.android.model.PaymentMethod`, `WebGLShader`, `AnimationSampler`, `AzExtLocation`, `TextDirection`, `pxt.TargetBundle`, `XhrDetails`, `Screenshoter`, `LuaInfo`, `UnknownType`, `HeadingCache`, `JWTPayload`, `ApiModel`, `WeuData`, `Aux`, `IndexerError`, `requests.ListDbNodesRequest`, `JSDocTupleType`, `MongoError`, `IMailTransferAgent`, `ProofResponseCoordinator`, `SearchEsListItemSchema`, `GetRRSetResponse`, `ElasticsearchFeatureConfig`, `ICitableSource`, `requests.ListResolverEndpointsRequest`, `ExtractorContext`, `UploadAssetOptions`, `fnVoid`, `KeyPath`, `Number`, `ParsedMessagePart`, `TelemetryPluginSetup`, `ListTaskRunLogsRequest`, `ABLMethod`, `GuideEntryType`, `P4`, `ISimpleGraphable`, `BaseTelemetryProperties`, `commandParser.ParsedCommand`, `TaskRepository`, `MaybeRef`, `HTMLIonLabelElement`, `StandardChip`, `OctoKitIssue`, `RecordOf`, `Messaging.IPublish`, `TransformerContext`, `DAL.KEYMAP_MODIFIER_POS`, `PropertyConfig`, `ShipSource`, `Limit`, `Proto`, `RouteNotFoundException`, `StringUtf8CV`, `ThemeConfig`, `TokenKind`, `PieVisParams`, `WaiterConfigurationDetails`, `ViewValue`, `FormValue`, `NvRouteObject`, `AppsService`, `XPCOM.nsICategoryManager`, `Enforcer`, `GetParams`, `DeleteDomainNameCommandInput`, `SelectedUser`, `ethers.Wallet`, `OutputCache`, `LoggerContextConfigType`, `HarnessAPI`, `StyledDecorator`, `IntrinsicFunction`, `IRepositoryModel`, `GameWorld`, `RefreshOptions`, `MachineData`, `ClientRule`, `reflect.ClassType`, `RenderInput`, `ManagementAgentPluginDetails`, `ExtensionOptions`, `LovelaceCard`, `HierarchicalNode`, `PostProcessingFactory`, `InternalServerError`, `ContextMasquerade`, `ExpressLikeResponse`, `KeplrGetKeyWalletCoonectV1Response`, `ERenderMode`, `ExtHTLC`, `DirectedScore`, `AbortSignalLike`, `ManagementAppMountParams`, `AxisDataItem`, `UpdateDetectorRecipeDetectorRule`, `DefaultRequestReturn`, `ICommentData`, `RestApi`, `ScaleThreshold`, `DOMProxy`, `TDispatch`, `DataModel.CellRegion`, `StepState`, `requests.ListSendersRequest`, `CreateParameters`, `InvoiceItemService`, `DataTransfer`, `ListGroupsRequest`, `pulumi.ComponentResourceOptions`, `ActionButtonProps`, `PostRef`, `protos.common.IMSPRole`, `DescribeDBInstancesCommandInput`, `InvoiceQuotation`, `ConfigurableForm`, `ExtendedTypeScript`, `QueryFetcher`, `WechatOfficialAccountService`, `SqlTuningTaskStatusTypes`, `Span`, `IUserRepository`, `AccessListEIP2930Transaction`, `UI5Type`, `ChoiceSupportOption`, `TypeTreeNode`, `GlobalNameFormatter`, `WebSocket.Data`, `ArtifactEngineOptions`, `UITableViewCell`, `MockWebSocketClientForServer`, `puppeteer.Browser`, `ReaderTaskEither`, `StatementsBlock`, `TransmartHttpService`, `ComponentData`, `NavigationProp`, `Reserve`, `RefactorEditInfo`, `TradeablePoolsMap`, `DeferIterable`, `PackageJsonData`, `QueryMnemonic`, `server.AccessKeyId`, `TSFiles`, `IEntityModel`, `PackageJson`, `CommandDefinition`, `PullIntoDescriptor`, `Knex.JoinClause`, `DynamicFormNode`, `Trampoline`, `SecService`, `Ants`, `NgGridItemConfig`, `Ohm.Node`, `IGetItem`, `RequestChannel`, `nodes.Identifier`, `TypeAlternative`, `AccountItem`, `GetStageCommandInput`, `ApiDecoration`, `MainPageStateModel`, `ResolvedDeclarations`, `FolderInfo`, `Friend`, `Ed25519KeyPair`, `IExecutorHandler`, `UpdateCallback`, `ExportTypeDefinition`, `DOMRectReadOnly`, `BaseCommand`, `QueryFunctionContext`, `GraphQLDatabaseLoader`, `HealerStatWeightEvents`, `TableResult`, `CodeGenField`, `TimelineSpaceState`, `ITeamCardState`, `ResponseHeaders`, `BillingGroupCosts`, `DBSymbol`, `TileType`, `ManglePropertiesOptions`, `ErrorPropertiesForName`, `Float32ArrayConstructor`, `StyleManager`, `ICluster`, `ChangePasswordCommandInput`, `CreateDiagnostic`, `Axis`, `ArgumentType`, `TagEntry`, `Sinon.SinonStub`, `ProcessErrorEvent`, `RegionCardinality`, `Python`, `MarginCalculatorInstance`, `ApiTypes`, `CronJob`, `UpdateRuleCommandInput`, `DidCloseTextDocumentParams`, `DescribeConfiguration`, `DynamicLinkParameters`, `TaskManagerStartContract`, `Call`, `LabwareCalibrationAction`, `UpdateParams`, `SidePanelTransitionStates`, `SpawnSyncOptionsWithStringEncoding`, `IGetCountsStatistics`, `K.TSTypeKind`, `SetWindowProps`, `HapCharacteristic`, `DbPull`, `option`, `throttle`, `MIRGuard`, `CreateIndexCommandInput`, `SymVal`, `PoseNet`, `HealthStateFilterFlags`, `LeaderboardRecordList`, `html.Node`, `MiddlewareStack`, `EthereumERC721ContextInterface`, `PutDedicatedIpWarmupAttributesCommandInput`, `GetWebACLCommandInput`, `BlobWriter`, `Expr`, `FabSettings`, `ListRulesRequest`, `Tsoa.ReferenceType`, `DeleteDBClusterSnapshotCommandInput`, `ParserRule`, `Reflection`, `EnvelopeGenerator`, `PickingRaycaster`, `Universe`, `MatProgressSpinnerDefaultOptions`, `AxisMap`, `BatchType`, `EPNode`, `PathDefinition`, `ShippingEntity`, `LoadingState`, `ITransferProfile`, `DatabaseSession`, `StateWithNewsroom`, `YouTube`, `EmbeddableChildPanelProps`, `INodeInterface`, `ClrHistoryModel`, `Enumerable`, `PrimitiveStringTypeKind`, `CAInfo`, `ChatThreadProperties`, `IPercentileRanksAggConfig`, `Shape`, `ComplexSchema`, `Translations`, `GenerateTimeAsyncIterable`, `DocumentFormattingParams`, `ParsedTranslationBundle`, `TransportOptions`, `IDraggableProps`, `EquatorialCoordinates`, `HitBlockMap`, `Moods`, `AppThunkAction`, `EntryCollection`, `SubReducer`, `TransactionReceipt`, `Author`, `GetProfileCommandInput`, `ResultReason`, `mb.EntityType`, `AppMetaInfo`, `NT`, `XMLBuilder`, `RewriteMapping`, `MouseData`, `DescribeChannelMembershipForAppInstanceUserCommandInput`, `VisualizerInteractionTypes`, `HttpServiceBuilderWithMeta`, `WaitInfo`, `EosioActionTrace`, `JSDocTypeExpression`, `UIMenuItem`, `UserTenantRepository`, `FactoryState`, `SecurityClassOwner`, `SchemaType`, `HTMLStyle`, `IMyValidateOptions`, `ILangImpl`, `DefaultPrivacyLevel`, `SCXML.Event`, `DeleteFunctionCommandInput`, `ValueReadonly`, `IFormFieldData`, `InstancePoolPlacementSecondaryVnicSubnet`, `ComputedAsyncValue`, `ReadConditionalHeadersValidator`, `HttpProbeProtocol`, `paper.Point`, `WriterType`, `BoxSizer`, `InitObject`, `FileReference`, `ItemSearchResult`, `IExtension`, `Highlight`, `GameDataState`, `RunHelpers`, `GuiObject`, `JSONSchemaObject`, `CreateTag`, `AggregationFrame`, `BadgeStyle`, `WorkspaceFolderSetting`, `IObject`, `Intf`, `EditorsService`, `ServiceKey`, `FavouritesState`, `ast.SeqNode`, `GoToProps`, `MultipartFileContract`, `PatternSlot`, `MpqHash`, `SMTVar`, `ISshSession`, `MockStore`, `CallHook`, `ConnectionStatus`, `XRReferenceSpace`, `IEntityInfo`, `TimelineKind`, `SuiModalService`, `News`, `OptionsReceived`, `LanguageHandlers`, `PassthroughLoader`, `PanelMode`, `IMonthAggregatedEmployeeStatistics`, `Queued`, `SMTConst`, `MyServer`, `TasksEntityStore`, `IPublish`, `UIDatePicker`, `EnvSection`, `MeterCCSupportedReport`, `Memory`, `NodeJS.ProcessEnv`, `ContentRef`, `ModelPath`, `PublishState`, `UseGeneric`, `SerializedHouse`, `NodeView`, `GetShapeRowGeometry`, `ECPair.ECPairInterface`, `token`, `IStreamChunk`, `SendMessagePayload`, `T.Action`, `Commands`, `IndexTreeItem`, `SolutionToSolutionDetails`, `PluginAPI`, `DescribeChannelCommandInput`, `CoreTypes.TextDecorationType`, `BatchSync`, `RequestData`, `FlattenLevel`, `AssociationCCReport`, `TelemetryPluginConfig`, `Predicate2`, `Geopoint`, `ODataEnumType`, `Aabb2`, `pxt.Package`, `HttpCacheService`, `Point2DData`, `InputEvent`, `CreateDatasetCommandInput`, `SessionEvent`, `LedgerWriteReplyResponse`, `DefaultKeys`, `TextInputVM`, `Building`, `EncodedPaths`, `fopAcM_prm_class`, `Consensus`, `VirtualModulesPlugin`, `GridDataState`, `ClassNames`, `AsyncEvent`, `FrontmatterWithDefaults`, `ACTION`, `DocumentData`, `ValidResourceInstance`, `TopicForIndicator`, `nconf.Provider`, `TheSimpleGraphQLServiceStack`, `CubeFace`, `DBClusterRole`, `PacketHandler`, `RSV`, `TransitionType`, `ValueJSON`, `UrlParams`, `UnsignedOrder`, `TransformationResult`, `Squiss`, `ISubprocessMessageBase`, `GainNode`, `JSONSchema`, `WritingSettingsDelegate`, `vscode.TreeView`, `AccountsInstance`, `Duration`, `FcCoords`, `DIDDataStore`, `DVector3d`, `IObserverCallback`, `ParsedRequestUrl`, `FullscreenOptions`, `TriggerForm`, `NodeInfo`, `ODataApiOptions`, `FieldState`, `ObjType`, `IsRegisteredFeatureHandlerConstraint`, `DeleteResourceCommandInput`, `ChatCommand`, `AppDataType`, `IosTargetName`, `SyncMemoryDebe`, `GLProgram`, `MessagingSessionObserver`, `TExpected`, `UpdateConnectivityInfoCommandInput`, `ISize`, `IGetSurveyModelsResponse`, `Participant`, `PowerPartial`, `StopHandle`, `HttpProvider`, `Typography`, `HashBucket`, `VisTypeTimeseriesRequestHandlerContext`, `StopApplicationCommandInput`, `BookingVariant`, `ExampleData`, `AaveV2Fixture`, `LContainer`, `PathFinderGoal`, `GaugeStatus`, `DiagnosticTag`, `AssetPropertyVariant`, `RTCRtpCodingParameters`, `AutomationEvent`, `MdastNodeMap`, `Deno.Conn`, `ControllerRenderProps`, `ProjectSummary`, `ApplicationShell.Area`, `WatcherOptions`, `ISimpleType`, `AnimDesc`, `DescribeEventsCommandOutput`, `SecureTrie`, `UrlOptions`, `DecisionPathPlotData`, `CreepActionReturnCode`, `NetworkSecurityGroup`, `PublishedFurniture`, `MenuOptions`, `SerialAPIVersion`, `PlaneBufferGeometry`, `NamedMember`, `MalVal`, `ExpressionNode`, `AdaptElement`, `_MessageConfig`, `StreamLabsMock`, `SonarQubeApiComponent`, `StaticFunctionDecl`, `AnimationChannel`, `UserConfigSettings`, `EmailModuleOptions`, `LinterGetOffensesFunction`, `RequestHeaders`, `PointerEvent`, `DomSanitizer`, `MemoryAppenderConfiguration`, `HoverProvider`, `ConstInterface`, `IProjectNode`, `RouteLocationRaw`, `IEntityError`, `PDFParser`, `CardCollection`, `STPCardValidationState`, `thrift.Thrift.Type`, `FormBuilderConfiguration`, `URLSearchParams`, `VpnPacketCaptureStopParameters`, `Express`, `IsString`, `RequestProfile`, `SubMeshRenderElement`, `ISceneObject`, `RDBType`, `RowTransformerValidator`, `formatLinkHeader.Links`, `CosmosBalance`, `XPCOM.nsIXULWindow`, `OpenSuccessCallbackResult`, `ImageRef`, `IndexOpts`, `ListTagsForResourceResult`, `LoadableMeta`, `Ent`, `MutateInSpec`, `NVMOperationsResponse`, `CompilerContext`, `DataListProps`, `IAnimatedCallback`, `ApolloServer`, `IWarriorInstance`, `AdaptMountedElement`, `CollectionStore`, `Navigation`, `apid.RecordedId`, `WorkerConfig`, `ConversationItem`, `TreeSelectionModificationEventArgs`, `SimulatorDatabase`, `ResolveRecord`, `PathParameterValues`, `IPipeable`, `BlockchainHandler`, `YieldFromNode`, `TimeTravel`, `RoleIndexPrivilege`, `ImportInterface`, `HTMLIonAlertElement`, `FeatureSettings`, `jest.DoneCallback`, `IAmazonApplicationLoadBalancer`, `MouseButtonMacroAction`, `LayeredLayout`, `ExpressServer`, `SecureHeadersOptions`, `DocOptArgs`, `Ringmodulator`, `MetricsPublisherProxy`, `FunctionNode`, `RenderOptions`, `Deal`, `Recursion`, `FilterFunc`, `LogSeriesFragment`, `ModuleWrapper`, `MessageToWorker`, `ComponentOptions`, `VoidFunction`, `JSONObject`, `RowType`, `GrabOptions`, `OsuSkinTextures`, `TheoryDescriptor`, `ITypeEntry`, `DOMException`, `FutureWallet`, `SteeringPolicyRule`, `ValueValidator`, `MonoSynth`, `ContainerOptions`, `ApolloReactHooks.LazyQueryHookOptions`, `CallSignature`, `EventDeclaration`, `ColonyNetworkClient`, `AttributeFilter`, `GroupingCriteriaFn`, `Gettable`, `FocusTrap`, `AggTypeState`, `CompleteGodRolls`, `MappedTypeGuard`, `ParseMode`, `IHubRequestOptions`, `StartedTestContainer`, `Metadata`, `IClientConfig`, `MergeIntersections`, `IndexedReadWriteXYZCollection`, `IJsonPatch`, `DataTableColumn`, `EventProxy`, `FlowItemComponent`, `SequenceConfig`, `CraftProjectConfig`, `FcConnector`, `ProgressDashboardConfig`, `FcException`, `AckFrame`, `Alarm`, `PythonCommandLine`, `Sandbox`, `UIFunctions`, `SearchAllResourcesRequest`, `DummySpan`, `AppDependencies`, `TeamType`, `Terminator`, `ValidPropertyType`, `AuctionManager`, `JsonAstObject`, `TCollectionSchema`, `OptimizeJsInput`, `ZoomBehavior`, `PublicationRepository`, `Constants`, `IGameContextValue`, `XTableRow`, `TrigonometryBlock`, `PutEmailIdentityDkimAttributesCommandInput`, `d.CompilerBuildStats`, `DescribeOfferingCommandInput`, `UserSimple`, `UserDTO`, `BreadcrumbPath`, `TestAccounts`, `TemplateCache`, `DatePickerDayDateSource`, `Sqlite.Statement`, `CreateChannelRequest`, `TreeAdapter`, `RoomUserEntry`, `TokenMap`, `UnitTestTree`, `DayGridViewWrapper`, `DataSeries`, `ComponentCompilerVirtualProperty`, `ModbusForm`, `Ceramic`, `TSESTree.Literal`, `CellOutput`, `ElectronShutdownCommandOptions`, `ApplicationVersionFile`, `Keypoint`, `ExtensionInfo`, `BytesValue`, `StoreReadSettings`, `ClassDeclarationStructure`, `RecommendationLifecycleDetail`, `LineLeaf`, `IScheduler`, `IPFSDir`, `GzipPluginOptions`, `TraceOptions`, `WithSerializedTarget`, `SchemaArgInputType`, `SelectorMeta`, `QueryManager`, `ManyToMany`, `ExtendedLayer`, `PrRepository`, `ILanguageState`, `EntityAttributes`, `InstanceLightData`, `UIImageView`, `MatPaginatorIntl`, `MediaPlayerState`, `SettingItem`, `Share`, `ICreateUpdateLanguageConfig`, `TextStringContext`, `GfxRenderTargetDescriptor`, `TwoFactorProviderType`, `BarcodeScannerConfig`, `LocalDirName`, `ListShapesRequest`, `Market`, `ServersState`, `CapsizeOpts`, `QueryCertificatesRequest`, `RoleRepresentation`, `AttributeInfo`, `SwingTwistSolver`, `DropLogFile`, `CustomPriceLine`, `SchemaKey`, `Reg`, `EditablePoint`, `babel.Node`, `DOMPointInit`, `Compact`, `StyleMap`, `TeliaMediaObject`, `NodeImmut`, `Income`, `SchemaResult`, `TextGeometry`, `Ticks`, `IsCommon`, `PrivKeySecp256k1`, `ListaTarefas`, `JobHandler`, `AsyncRequestHandler`, `TestBedStatic`, `Lock`, `DtlsServer`, `Instruction`, `CompilerHost`, `SortType`, `ListsState`, `SerializeImportData`, `DefaultRollupBlock`, `CompilerFileWatcherEvent`, `NgxsRepositoryMeta`, `request.OptionsWithUri`, `IconifyIconBuildResult`, `ConsoleAPI`, `ContentGroupProps`, `GovernanceMasterNodeRegTestContainer`, `LinearProgress`, `SelectItemDescriptor`, `JsonRpcHttpClient`, `LayoutCompatibilityReport`, `RenderPassDescriptor`, `ShaderSocket`, `CodeBuilder`, `ThemeColorable`, `vscode.TestController`, `IBazelCommandOptions`, `ListDataSetsCommandInput`, `INeonNotification`, `ast.UnaryNode`, `IconStorage`, `FilterRule`, `requests.ListDbVersionsRequest`, `EncryptedObject`, `RangeBucket`, `CallAgent`, `DynamoDbPersistenceAdapter`, `RestMultiSession`, `ChromeMessage`, `GQtyError`, `DisplayErrorPipe`, `VideoDownlinkObserver`, `Parsed_Result`, `BigSource`, `LocalNetworkDevice`, `Geolocation`, `BisenetV2CelebAMaskConfig`, `NetWorthSnapshot`, `ResultProgressReporter`, `DynamicFormValidationService`, `JOverlap`, `TodoListRepository`, `DocumentTree`, `ConfigOptions`, `SettingsState`, `DeployParams`, `RollupAggregator`, `RemoveEventListenerFunction`, `DynamicDialogConfig`, `FormFieldModel`, `DockerAuthObj`, `MIRInvokeFixedFunction`, `ResolvedRouteInfo`, `Handlebars.TemplateDelegate`, `Monad`, `ActivityComputer`, `ProjectChangeAnalyzer`, `DeleteBackupCommandInput`, `DataProxyAPIErrorInfo`, `ISlackPuppet`, `ListenerCallbackData`, `ISubImage`, `RoomInfo`, `UpdateCustomEndpointDetails`, `TransactionVersion.Testnet`, `ImageEncoder`, `Die`, `INode`, `EquipmentSharingPolicyService`, `SourcemapPathTransformer`, `QComponentCtx`, `ListrContextFinalizeGit`, `ContainerGetPropertiesResponse`, `HydrateImgElement`, `Deps`, `Properties`, `ReducerArg`, `QueryEntityKey`, `DocgeniHostWatchOptions`, `ContentRequestOptions`, `ThySelectionListChange`, `ChannelsState`, `AccountsContract`, `lambda.Function`, `CtrEq`, `UI5Namespace`, `Kind3`, `DialogStateReturn`, `ml.Attribute`, `SocketEvent`, `Parts`, `ISessionRequest`, `EntityCollectionDataService`, `GetRRSetRequest`, `IItemRendererProps`, `IRemote`, `M2ORelation`, `DashboardPlugin`, `IStoryItemChange`, `PixelType`, `Zoom`, `WebAssemblyInstantiatedSource`, `NavigationActions`, `HostComponent`, `EdaDialogCloseEvent`, `InternalFailureException`, `CliOutput`, `PutObjectRequest`, `GraphTxn`, `DaffCountry`, `iTickEvent`, `UseFormReturn`, `PathCursor`, `OwnPropsOfRenderer`, `ExchangePair`, `IListenerAction`, `HighlightRange`, `SerializedGame`, `BlockHash`, `MlClient`, `Behaviour`, `CommonMaterial`, `UnscopedEmitHelper`, `CodeMirrorEditor`, `RTDB.Get`, `BadRequestErrorInfo`, `FileSystemCache`, `PropertyCategory`, `HttpProbeMethod`, `LinkI`, `runtime.HTTPQuery`, `Contest`, `GroupConfig`, `PromiseJsExpr`, `TouchEvent`, `LetterSpacing`, `Serializable`, `BasePackage`, `CustomElementRegion`, `Color`, `SetBreadcrumbs`, `interfaces.Context`, `PetStoreProduct`, `ClassWriter`, `ListTagsForResourceMessage`, `EnhancedSku`, `CSSEntries`, `LockType`, `STWidgetRegistry`, `SpeculativeContext`, `ListTablesResponse`, `NodePrivacyLevel`, `Ext`, `ITerminalProvider`, `EventInterface`, `ThemeCss`, `Types`, `RTDB.Subscribe`, `GeoBox`, `BinarySensorType`, `SchemaBuilder`, `IRequestConfig`, `XUL.contentWindow`, `OrganizationPolicySummary`, `SuccessfulParsedMessage`, `ColumnFormat`, `AuthConfig`, `IconType`, `CosmosOperationResponse`, `FolderDoc`, `AppError`, `ExecutionContextInfo`, `IDeclaration`, `VerifyJwtOptions`, `Purse`, `PrefBranch`, `CreateFileOptions`, `LoginUriView`, `Linear`, `ComponentTypeEnum`, `WebViewExt`, `IScriptingDefinition`, `ast.IfNode`, `SourceIntegrationInterface`, `PipelineRelation`, `FlowCondition`, `ITextDiff`, `CeloTokenContract`, `VercelConfig`, `ViewData`, `FaunaUDFunctionOptions`, `PackageManager`, `Instrument`, `flatbuffers.Offset`, `IJSONInConfig`, `iAction`, `ConfirmChannel`, `PluginDeleteActionPayload`, `K4`, `FoamWorkspace`, `ResultT`, `RegisteredSchemas`, `WeakRef`, `HeatmapDataSets`, `IFactor`, `TranslatePropertyInput`, `AnimationChannelTargetPath`, `EvmType`, `Snapshot`, `ToplevelRecord`, `PostConditionMode.Deny`, `MemberNode`, `LastValues`, `UpdateType`, `RequestTemplate`, `CollectionConfig`, `ReferenceMonth`, `DataModels.Kpi.ActiveTokenList`, `PolusBuffer`, `ExpansionResult`, `ListDatabasesRequest`, `SiteClient`, `ResponseMessage`, `LoggerService`, `PluginPackage`, `CategorizationAnalyzer`, `YAMLMapping`, `NoncurrentVersionTransition`, `CategoricalColorScale`, `CellPosition`, `TPageConfig`, `d.TypesMemberNameData`, `Dependence`, `IPrompter`, `MessageDataOptions`, `ShadowboxSettings`, `ValuedRivenProperty`, `ResourcePropsWithConfig`, `TextureConfig`, `DictionaryFile`, `ContractManifestClient`, `ITranslationMessagesFile`, `IndexDiff`, `SuperAgentTest`, `TS.Node`, `CssRule`, `Simulate`, `DownloadRef`, `TaskItem`, `GlobalPropertyStruct`, `NodeCheckFn`, `SkeletonTextProps`, `Gen`, `ExtendedAreaInfo`, `UpdateChannelReadMarkerCommandInput`, `AsyncWaterfall`, `AuthType`, `a`, `EntityProperty`, `ExtractClassDefinition`, `VerifiedCallback`, `CalcObj`, `TexturedStyles`, `DMMF.TypeInfo`, `LogicalQueryPlanNode`, `Workspace`, `FixOptions`, `StringToken`, `ProfileX`, `ConstraintSolver`, `RegistryPolicyTemplate`, `SVGGElement`, `Loggable`, `TimelineActivity`, `StartServices`, `ThresholdedReLU`, `MessageToken`, `ModelData`, `H.Behavior`, `KibanaRequest`, `FilteredLayer`, `SystemVerilogImportsInfo`, `EntitySelectorsFactory`, `BemSelector`, `DeploymentDisconnectStatus`, `DeleteIntentCommandInput`, `tf.LayersModel`, `TwingSourceMapNode`, `IRenderDimensions`, `DirectedEdge`, `Mocha`, `BinaryTree`, `EncodedQuery`, `ICheckOut`, `FileDeleteOptions`, `ResourceCacheData`, `WorkspacePlugin`, `AggTypeConfig`, `SelectionsWrapper`, `ComponentsCompiler`, `BuildData`, `CameraController`, `LyricLanguage`, `ComparatorFn`, `SubdivisionScheme`, `Listenable`, `CalendarPatterns`, `ClientSubLocation`, `t_As`, `Screen`, `PiLimitedConcept`, `GaugeRenderProps`, `TableSeg`, `IGenericTaskInternal`, `BodyParser`, `DocumentGenerator`, `Selector`, `ListAutoScalingPoliciesRequest`, `StaticFunctor`, `OptionsMatrix`, `VRMSpringBone`, `GitUrl`, `SourceMap`, `Props`, `d.HydratedFlag`, `ExportedConfigWithProps`, `GraphDataProvider`, `NodeDependency`, `P1`, `LeafletElement`, `requests.ListZoneTransferServersRequest`, `RelationshipPath`, `Poker`, `Yendor.Console`, `PackageJsonOptions`, `EditPageReq`, `ISummaryContext`, `GfxQueryPool`, `Volume`, `OutputWriter`, `estypes.AggregationsAggregationContainer`, `IStatusView`, `OutputCollector`, `INormalEventAction`, `RenderBatchKey`, `I18n`, `DeleteRetentionPolicyCommandInput`, `ts.Map`, `ProgressMessage`, `ClientImpl`, `Angulartics2GoogleGlobalSiteTag`, `EnvProducer`, `STS`, `WebPartContext`, `SingleConsumedChar`, `AddressNonces`, `XActorRef`, `FunctionCallArgumentCollection`, `CustomText`, `GfxBufferBinding`, `HintResults`, `NzDrawerRef`, `Labware`, `FriendRequest`, `QuestService`, `RoutingRule`, `IPathfindersData`, `InstrumentationLibrarySpans`, `EntityOp`, `ListUserProfilesCommandInput`, `Powerlevel`, `MIRRegisterArgument`, `ethers.providers.JsonRpcProvider`, `LoadedTexture`, `Charge`, `ProgramCounterHelper`, `MagicOutgoingWindowMessage`, `TransactionEventType`, `AtRule`, `GlobalDeclaration`, `IEditEntityByMemberInput`, `NestedOptionHost`, `InfluntEngine`, `ClassRefactor`, `MetamodelService`, `ChartjsComponentType`, `PortObject`, `Guy`, `ValidationResultsWrapper`, `SwitcherItem`, `requests.ListCloudAutonomousVmClustersRequest`, `LLVMNamePointer`, `DalgonaState`, `DiagnosticsOptions`, `CreateAppointmentService`, `SecondaryIndex`, `FormType`, `SubscriberEntity`, `S3Source`, `EntityDefinition`, `PositionProps`, `NexeCompiler`, `MiddlewareFnType`, `SetState`, `MeetPortalAnchorPoint`, `GestureUpdateEvent`, `ImportData`, `GlyphSet`, `TimelineActivityKind`, `TableOptions`, `OutdatedDocumentsTransform`, `NodeI`, `BuildApiDecOpts`, `models.ISegement`, `TransactionResult`, `MinimalNodeEntryEntity`, `GetJobCommandInput`, `Path0`, `PanEvent`, `VfsEntry`, `IStorageSyncOptions`, `GenericAsyncFunc`, `AuthToken`, `SignedByDecider`, `StepChild`, `LinkedList`, `SymExp`, `DebugProtocol.ConfigurationDoneResponse`, `PropertyFlags`, `LoaderManager`, `RpcNode`, `TextureOverride`, `Pass1Bytes`, `WebpackAny`, `Loadable`, `ArgumentMetadata`, `ZipMismatchMode`, `PDFAcroPushButton`, `Toggleable`, `ICurrentControlValidators`, `Tally`, `TAction`, `FromViewOpts`, `AddAtomsEvent`, `TaskSchema`, `Node.Identifier`, `ArrayExpression`, `DropdownOption`, `ILoggedInUser`, `yubo.PlayOptions`, `d.MinifyJsResult`, `CheckboxValue`, `PinoLogger`, `AttributeType`, `CommonStyleProps`, `UserDto`, `ParsedQueryNode`, `FunctionParameter`, `OptiCSSOptions`, `TimeAveragedBaseRateOracle`, `ITokenInfo`, `NameObjFactoryTableEntry`, `VaultTimeoutService`, `ColumnBands`, `InputTypeComposer`, `SymbolWriter`, `OpenChannelObjective`, `AsyncIterableX`, `ChatError`, `ListServicesResponse`, `ArrowFunctionExpression`, `PlayerAggHistoryEntry`, `Record`, `AWS.CloudFormation`, `UserSettingsModel`, `btSoftBody`, `ClassExportDoc`, `StatsService`, `ICloudFoundryServerGroup`, `RequestCancelable`, `ApmPluginContextValue`, `IAresData`, `DMMFClass`, `Certificate`, `CreateHitTesterFn`, `TagEdit`, `VstsEnvironmentVariables`, `FetchEnd`, `DragDropIdentifier`, `ExecutionLogSlicer`, `WorkflowInputParameterModel`, `ContextMenuParams`, `FileBlock`, `AuditResult`, `ReturnModelType`, `ShoppingCart`, `Offsets`, `Country`, `OrderDirection`, `SignInPayload`, `TransitionDescription`, `CommonToolbarItem`, `SpaceService`, `Errno`, `InitTranslation`, `BabelPluginChain`, `RequestSuccessAction`, `rp.OptionsWithUrl`, `Batch`, `Debug`, `PathFragment`, `BitcoinTransactionInfo`, `BSplineCurve3dH`, `CombatVictorySummary`, `Note`, `CrochetCapability`, `d.LogLevel`, `TrueGold`, `ImageService`, `IBranch`, `PumpState`, `DemoService`, `Rule.RuleListener`, `_IRelation`, `DoorFeatureType`, `CommandReturn`, `IAdministrationItem`, `ResourceComponent`, `ExecutableSpec`, `KeyBindingCommandFunction`, `SelectedState`, `EngineArgs.DevDiagnosticInput`, `BookmarkHelperService`, `AST.SubExpression`, `DocumentConnectionManager`, `NamePosInfo`, `ObjectAllocator`, `ColorHelper`, `ProjectedDataItem`, `Math2D.Box`, `ReleaseDefinitionSchema`, `IPageNode`, `RegularizationContext`, `Closeable`, `WithStringLiteralProperties`, `ApplicationMetadata`, `ExtensionDefinition`, `CasesClientArgs`, `RevealConfig`, `IJSONResult`, `EntityMapEntry`, `AppModels`, `StreamQuery`, `gameObject.Bullet`, `JsonDocsTag`, `VFileCompatible`, `StatusBarWidgetControlArgs`, `cPhs__Status`, `Speaker`, `FakePlatform`, `AuthenticatedUser`, `HttpResources`, `Placement`, `BaseConfig`, `t.STSelector`, `DescribeEventAggregatesCommandInput`, `AccountTransfersService`, `Crypto`, `OrthogonalDirection`, `FormatCodeSettings`, `ActionCallback`, `RespondersThemeType`, `LayerState`, `ConfigurableEnumConfig`, `DevicesButtonStrings`, `Config`, `TestReport`, `Router.RouterContext`, `MultiChannelAssociationCCRemove`, `MediationRecord`, `ElectrumNetworkProvider`, `IFBXLoaderRuntime`, `PythonDependency`, `CarouselProps`, `ShapeModel`, `TagNode`, `Regularizer`, `ITestsService`, `api.IZoweDatasetTreeNode`, `Insight`, `IconTheme`, `CountableTimeInterval`, `sinon.SinonSandbox`, `OutputFormat`, `CloudWatchDestination`, `ImportInterfaceWithNestedInterface`, `UntagResourceRequest`, `CallAndResponse`, `PromiseFast`, `JsxClosingElement`, `AsyncThunk`, `WebGL`, `RicardianContractProcessor`, `ForkEffect`, `RenderState`, `BottomSheetOptions`, `ModelInterface`, `ObservableQuery`, `CustomHttpResponseOptions`, `TaskRecord`, `ProxySide`, `CarouselService`, `TSpan`, `CreateScope`, `CourseState`, `DeleteGatewayCommandInput`, `Sample`, `ShapeGeometry`, `PiTriggerType`, `CreateFilterCommandInput`, `SavedObjectsCreatePointInTimeFinderDependencies`, `PieceAppearance`, `Segment3`, `requests.ListApplicationsRequest`, `TypingGenerator`, `ActionState`, `DOMExplorerDashboard`, `CeloTxReceipt`, `IShadowGenerator`, `ColumnMapping`, `ColumnSchema`, `PostToken`, `FunctionType`, `TypeAttributeKind`, `SwitcherResult`, `ActiveMove`, `ListComprehensionIfNode`, `ColonyExtensionsV5`, `VMContext`, `ReadTarball`, `PointerInfoBase`, `Resolvable`, `CreateWidgetDto`, `CardType`, `Jws`, `UpdateRouteCommandInput`, `S2Options`, `CommandResult`, `IGBPackage`, `BaselineResult`, `EToolName`, `BitmapFont`, `ThenableReference`, `BRepGeometryCreate`, `DomainPanel`, `PolicyContext`, `ClozeDeletion`, `Transaction.Options`, `CompilerInput`, `ContextName`, `SourceRootInfo`, `XYLayerConfig`, `ListenerCallback`, `ILexoNumeralSystem`, `UserMatched`, `LayerValue`, `JoinGroupRequest`, `DataRequestMeta`, `EditorOptions`, `FileMetaData`, `ControlState`, `TranslationLoaderService`, `CustomMerge`, `PrevoteMessage`, `JWKInterface`, `WideningContext`, `OpenApiSpec`, `HoverSettings`, `NixieEquipment`, `GenericMonad`, `SecondaryUnit`, `FullName`, `VirtualKey`, `EitherExportOptions`, `HsLogService`, `LunarInfo`, `SpeechConfig`, `d.HostRef`, `Cipher`, `requests.ListAcceptedAgreementsRequest`, `NetworkType`, `DMChannel`, `Oas20Parameter`, `ResourceQuota`, `WorkerResult`, `App.windows.window.IXulTrees`, `IPayloadAction`, `SingleKeyRange`, `IAPProduct`, `ISearchSource`, `ImageSource`, `CustomTemplateFindQuery`, `UpgradeDomain`, `TypePath`, `EventNameFnMap`, `AutoCompleteProps`, `Plyr`, `EnvironmentSettings`, `IGherkinOptions`, `SelectionModel`, `AnyClass`, `GetUserSuccessPayload`, `BoxBuffer`, `IRangeResponse`, `ColorInputProps`, `DistinctOptions`, `TransformHeadersAgent`, `ClipboardService`, `Descriptions`, `LinkedEntry`, `TAny`, `QualifiedOTRRecipients`, `StateStore`, `IGeometryProcessor`, `PhysicalKeyboardKey`, `RoamBlock`, `Tristate`, `TrackGroupIndex`, `Bleeps`, `AList`, `CalendarEventStoreRecord`, `LogicCommand`, `LogBoxLayout`, `StaticEllipseDrawerService`, `UpdateAlbumDto`, `HTMLStencilElement`, `ClientErrorResponse`, `MinAdjacencyListDict`, `InstallOptifineOptions`, `TArgs`, `RequestPopupModelAction`, `OptimizedSubSetKey`, `T.Position`, `RendererFactory3`, `DescribeGlobalClustersCommandInput`, `ShellOptions`, `MainPackage`, `IApplyJobPostInput`, `GetAccountSettingsCommandInput`, `ListConfig`, `PrismaClientClass`, `PluginCallbacksOnSetArgument`, `ODataPathSegments`, `LanguageVariant`, `ObservableProxy`, `JSDocState`, `OtherInterface`, `GlobalSearchResultProvider`, `IApplicationOptions`, `optionsInfo`, `BrowserPlatformUtilsService`, `CustomNode`, `AssetManifest`, `EmojiListObject`, `MIDIControlListener`, `AggregationResultMap`, `LoaderProps`, `ForceDeployResultParser`, `FrontendLocaleData`, `WellKnownTextNode`, `DraftHandleValue`, `DescribeDeviceCommandInput`, `ISwissKnifeContext`, `FeaturesDataSource`, `ITimezoneMetadata`, `CloudKeyStorage`, `ValueValidationFunc`, `IApp`, `XmlMapsCommandInput`, `HypermergeNodeDetails`, `ViewEntityOptions`, `IHandlers`, `GetDomainCommandInput`, `DriverMethodOptions`, `CartesianChart`, `ConfigStore`, `ValidationErrors`, `CipherCreateRequest`, `RemoveTagsFromResourceCommandOutput`, `TagDescription`, `Utf8ToUtf32`, `ValuesProps`, `ResolvedTupleAtomType`, `LastInstallFlag`, `BitWriter2`, `IObservableObject`, `IMethodHandler`, `Thrown`, `EvaluationScopeNode`, `MVTFieldDescriptor`, `StrategyParameter`, `IMutableVector2`, `EMSTermJoinConfig`, `INodeIssues`, `IDraggableList`, `ObjectDefinition`, `CookieParseOptions`, `LengthPrefixedString`, `FunctionBreakpoint`, `React.ReactChild`, `PortalInjector`, `RpcServerFactory`, `DropdownOptions`, `DynamicIndentation`, `MDXRemoteSerializeResult`, `EquipmentSharingService`, `DisplayCallbacks`, `ConstraintMember`, `SVFloat`, `sinon.SinonSpyCall`, `ParamWithTypeMetadata`, `MetricDimensionDefinition`, `KubeArgs`, `MetadataTypeGatherer`, `HandlerDelegate`, `ArrayLiteral`, `LockOptions`, `ListTranscriptionJobsCommandInput`, `HierarchyOfArrays`, `AttachedModule`, `ApiDefinition`, `MenuModelConfig`, `InboundMessageContext`, `ColorResolvable`, `GDIContext`, `FieldMap`, `GfxSamplerBinding`, `RoomClient`, `Prediction`, `DateFnsInputDate`, `AddressProtocol`, `TrueSkill.RankState`, `ArrayOrSingle`, `StateManager`, `TestAccount`, `NumberShape`, `KontentHttpHeaders`, `PostDocument`, `DOMElementType`, `IPageHeader`, `requests.ListCatalogsRequest`, `ServiceKeyType`, `FormRenderProps`, `IMembership`, `TileMapArgs`, `StableTokenWrapper`, `SelectMenuItemProps`, `UniformsType`, `CodeEditor`, `HoverTarget`, `EffectsInvocationContext`, `AppProduct`, `SankeyDiagramLink`, `CreateChildSummarizerNodeFn`, `OptionedValueProp`, `StateEither`, `RxFormGroup`, `SplitStructureAction`, `IResponseAggConfig`, `Measurement`, `RecordingTemplate`, `AutocapitalizationInputType`, `WorkerOptions`, `userData`, `NcTemplate`, `CommonCrypto`, `PermissionOverwrite`, `RequestObject`, `IntrinsicType`, `DxTemplateHost`, `Phaser.Scene`, `BytecodeLinkReference`, `indexedStore.Store`, `OnboardingService`, `GaiaHubErrorResponse`, `ArangoSearchView`, `CdkVirtualScrollViewport`, `CreateGroupResponse`, `IsvDebugBootstrapExecutor`, `ISearch`, `Trilean`, `MeasureSpecs`, `IALBListenerCertificate`, `TTargetReference`, `ItemRequest`, `messages.Rule`, `ColumnMetadata`, `NexeFile`, `FilePreviewDialogRef`, `RoomStoreEntryDoc`, `GreetingWithErrorsOutput`, `UnwrappedObject`, `Manager`, `MotionChartData`, `TreemapSeriesOptions`, `FilterResult`, `EchartsProps`, `tf.Tensor4D`, `WidgetModel`, `DefaultSession`, `VMLClipRectObject`, `ITestConfig`, `IniFile`, `InteriorInternal`, `CredentialPreviewAttribute`, `LoginState`, `NodeModule`, `ApiItemContainerMixin`, `GfxrRenderTargetID`, `ParserOutput`, `OrderByDirection`, `DebugContext`, `ConsoleLike`, `Slice`, `TabbedAggResponseWriter`, `IClassExpectation`, `TopUpProvider`, `SVGElement`, `CacheStorage`, `AppMenuItem`, `StackElement`, `PositionChildProps`, `LinearFlowFunction`, `IDropdownOption`, `FatalErrorFn`, `Figure`, `ShadowAtlas_t`, `requests.ListCategoriesRequest`, `GfxInputLayout`, `Semiring`, `Width`, `ComplexNode`, `sdk.Connection`, `RawTextGetter`, `IdentifierListContext`, `CloudfrontMetricChange`, `FeedbackContextInfo`, `IndexPattern`, `CacheContextContract`, `ColorRulesOperator`, `JustValidate`, `ISerializedResponse`, `ComputedStateCreationOptions`, `IResults`, `OP`, `ReverseIndex`, `DestinyInventoryItemDefinition`, `BufferMap`, `ParsedGenerator`, `TraversalContext`, `ProtocolRequest`, `ITfsRestService`, `IConnectionsIteratorOptions`, `WorkspaceSchema`, `LengthUnit`, `VariantFunction`, `UpdateIntegrationResponseCommandInput`, `PatternSequenceNode`, `InternalCallContext`, `IGuardResult`, `ShellComponent`, `VorbisDecoder`, `thrift.Int64`, `ObservableTitleTopBar`, `SongResult`, `AccountClient`, `DynamicValue`, `BaseText`, `SfdxFalconInterview`, `AvatarCustomization`, `PartyService`, `Pixel`, `MulticallClient`, `SnotifyToast`, `CustomersService`, `AttributeViewInfo`, `EntityCollectionReducers`, `SignatureInformation`, `DropType`, `AdamOptimizer`, `ClassField`, `IProjectConfig`, `OperationRequest`, `RibbonButton`, `IndexColumnModelInterface`, `Tool`, `AnyGradientType`, `ExpBool`, `ClassBody`, `ProjectTaskProperties`, `ClaimData`, `VMoneyOptions`, `ContractCalls`, `Design`, `Themes.Theme`, `NoiseModule`, `MapboxMap`, `PayloadDictionary`, `DependencyResolved`, `AnalyzeOptions`, `Navigator`, `StoredItem`, `DataLabelOption`, `egret.DisplayObjectContainer`, `GameSize`, `TextInputOptionProps`, `DAL.KEYMAP_ALL_KEYS_UP_POS`, `chalk.Chalk`, `LanguageSettings`, `CompilerProvider`, `RecognizerConfig`, `EntitySubjectStore`, `GMxmlHttpRequestEvent`, `Functor3`, `AsyncStepResultGenerator`, `SearchClient`, `TermSet`, `IChatJoinProperties`, `Location`, `CheckState`, `ProjectedEdge`, `PartitionOptions`, `Referenced`, `AffineFold`, `CreateDemandDTO`, `DbPush`, `CssClassMap`, `AXNode`, `SlidingWindow`, `StateMap`, `VinVout`, `ControlButtonProps`, `MetaDataCollector`, `LazyScope`, `Polymer.Element`, `ImportDeclarationStructure`, `ITaskChainFn`, `AreaProps`, `DGuard`, `QueueConfiguration`, `vfs.FileSet`, `VerificationGeneratorDependencies`, `ModifierFlags`, `ProtobufValue`, `VAF1`, `TransferOffchainTx`, `IDocumentStorageService`, `requests.DeleteProjectRequest`, `UsePaginatedQueryMergeParams`, `T.MachineContext`, `sourceTextureFormat`, `RegistrationForm`, `ExtractionResult`, `RenderMethod`, `AnalysisConfig`, `TileStyle`, `StatusState`, `ITour`, `GLTF.IAccessor`, `GridNode`, `AssertionTemplateResult`, `ReplacementBuilder`, `FileEditAction`, `FaunaId`, `MySQLConnection`, `FzfOptions`, `AccessRuleCriteria`, `AccountStellarPayments`, `OrganizationUnitDto`, `GX.ColorSrc`, `IUploadResult`, `ParseErrorCode`, `THREE.Raycaster`, `Vector3`, `LoaderConfig`, `SalesSearchOptions`, `SelectionEvents`, `DispatchProps`, `SyncedActivityModel`, `Stock`, `IMdcRadioElement`, `ThyDragDirective`, `FiberRoot`, `VisualizeEmbeddableFactory`, `IngredientOrResult`, `SsrcDescription`, `DocumentOptions`, `MetricUnit`, `RenderingDeviceId`, `ILecture`, `GLTFLoader`, `MpqFile`, `ITarget`, `RemoteBaseMock`, `vile.IssueList`, `mat3`, `RestServerConfig`, `IActionTrackingMiddleware2Call`, `ComponentRuntimeMeta`, `AssembledPipelinesGraphics`, `MessageThreadStrings`, `AccountsOperationIO`, `AuthTokenRequestSigner`, `OverloadedFunctionType`, `NzDrawerService`, `DeclarationBase`, `ScoreDoc`, `MultipartFile`, `StateMapper`, `FkDstrGridData`, `MassetDetails`, `EmitHint`, `EsHitRecordList`, `WildlingsAttackGameState`, `d.ConfigBundle`, `PointToPointLine`, `CronJobOptions`, `Composition`, `QRFunction`, `EmptyEventCreator`, `BlockSyntaxVersion`, `FetcherContext`, `TransformOrigin`, `MarketDataProvider`, `InstanceWithExtensions`, `RemoteConfigTemplate`, `VaultStorageService`, `FilesService`, `FirebaseError`, `ZoneSwitch`, `DataServiceError`, `ts.PostfixUnaryExpression`, `Mustering`, `TerminalState`, `TypeReference1`, `MatchExecutor`, `MLKitVisionOptions`, `mixed`, `ModelName`, `AtemConfiguration`, `BufferColumn`, `LockTime`, `WindowFrameName`, `KeySet`, `IsSpecificRowFn`, `PluginsClient`, `MetaQuestion`, `CliProfileManager`, `StreamingCmd`, `PSIInteger`, `Pallete`, `AngularFireUploadTask`, `DescribeResourcePolicyCommandInput`, `CallErrors`, `ReflectContext`, `MapViewInset`, `ThemeSetup`, `NodeList`, `Electron.IpcRendererEvent`, `TickFormatterOptions`, `MapShape`, `ActionsList`, `RentalService`, `NodeRecord`, `ResizerMouseEvent`, `NodeRpcService`, `TableInfo`, `UserStateService`, `WhereExpressionBuilder`, `S1GRDAWSEULayer`, `PiePoint`, `IRCMessage`, `RtpPacket`, `TerraformAuthorizationCommandInitializer`, `KeyAlgorithm`, `IObservableArray`, `ThemeInterface`, `SectionDataObject`, `INetworkInfoFeature`, `BarycentricTriangle`, `RepositoryCommonSettingType`, `Value.Of`, `InvalidState`, `PatternEnumPropertyOption`, `InputsType`, `MigrateStatus`, `CalendarMode`, `CallHierarchyDefinition`, `ActionPayload`, `ListCustomVerificationEmailTemplatesCommandInput`, `CompilerSystemRealpathResults`, `UserInterests`, `RotationSettings`, `KeyStop`, `SimpleType`, `DesignTimeProperty`, `JupyterKernel`, `ThyOptionComponent`, `SelectableDataPoint`, `PluginOpaqueId`, `PanGestureEventData`, `AwsCloudProvider`, `ExecaSyncReturnValue`, `TinyTranslatorService`, `ObjectOrArray`, `IFB3DOM`, `LambdaDataSource`, `ITimesheet`, `SHA256`, `GraphqlData`, `IIssue`, `eventInterface`, `EventListenerOrEventListenerObject`, `QuotePreference`, `SelectOptions`, `WeakSet`, `JSDocVariadicType`, `AsyncFrameworkFn`, `ethereum.Event`, `IColorSet`, `CurrencyObject`, `FileWatcherEventHandler`, `AddressRecord`, `USER`, `TodoDataService`, `ComponentSize`, `DisplayValue`, `ClassMap`, `ObjectValidator`, `PackageJsonLookup`, `ImmutableObjectiveGroup`, `SymbolTickerOrder`, `AuthType.Sponsored`, `MapScalarsOptions`, `TestERC721Token`, `AliasesMeta`, `JsonApiDocument`, `DescribeUserCommandInput`, `Eci`, `Pswp`, `FreezerContract`, `GQLEventSearchResultSet`, `ByteData`, `IMainState`, `TestAdapter`, `StoryLabel`, `SearchStrategyRequest`, `IAureliaComponent`, `CreateWorkspaceCommandInput`, `SinonStubbedInstance`, `SegmentClient`, `PageTemplate`, `ChartDataSet`, `ISettings`, `PromptOptions`, `ConfigurableFocusTrapConfig`, `TestSuite`, `TaskReport`, `PyrightJsonDiagnostic`, `DateTimeOffset`, `SurveyObjectItem`, `GroupRepresentation`, `WebSiteManagementModels.SiteConfigResource`, `HeaderMapManipulator`, `IGeneralFunctions`, `DatabaseInfo`, `CreateAssetProps`, `HandlerDomProxy`, `vscode.NotebookCell`, `StorageCacheService`, `ExportTraceServiceRequest`, `InventorySocket`, `RhoProcessor`, `StopInstanceCommandInput`, `ICordovaAttachRequestArgs`, `HuffmannNode`, `HasFancyArray`, `MinorEvent`, `DefaultValue`, `GraphicsLayerOptions`, `SavedSearchSavedObject`, `RenderResult`, `BoolArray`, `ElmType`, `ContainerAdapter`, `IWrappedEntityInternal`, `ArchiverError`, `GetAuthorizationTokenCommandInput`, `ApiExperiment`, `FnN5`, `SceneActor`, `IterableChangeRecord`, `ChromeStart`, `LanguageInfo`, `BlockDefinition`, `Answerable`, `AuthRequest`, `FormLabelProps`, `Persister.IPersist`, `SideNavComponent`, `SynthesisContext`, `Points`, `SpriteFrame`, `GoogleDriveSyncMetadata`, `Metric`, `Pooling1DLayerArgs`, `TCommand`, `CommonAlertParams`, `IntermediateTranslation`, `WrapExportedEnum`, `GDQOmnibarListItemElement`, `AssetWithMeta`, `DaffCategoryPageLoadSuccess`, `AddressSpace`, `TranspileResults`, `IconDefinition`, `LineView`, `QLabel`, `ChartState`, `GitBranchReference`, `BuildNoChangeResults`, `GX.FogType`, `SocketMessage`, `DynamicInputModel`, `FSM`, `StatePropertyAccessor`, `TextSpan`, `SCN0_Camera`, `IVector2Like`, `DatabaseType`, `BitcoinNetwork`, `TNew`, `ZAR`, `DataItems`, `Left`, `GetDomainDeliverabilityCampaignCommandInput`, `CGPoint`, `IEventSubscription`, `Scanner`, `BookingService`, `OpenYoloInternalError`, `CharList`, `WorkspaceSettings`, `DataKeyTypes`, `AddressChainType`, `OAuthAuthCode`, `ConnectedSpaceGraphics`, `GlobalStyleComponent`, `InitState`, `LanguageServerInterface`, `ClothingProps`, `DataPumpExcludeParameters`, `MiddleColumnPadCalculator`, `ViewQueriesFunction`, `IconProp`, `Arrayable`, `StarPiece`, `LayoutChangeEvent`, `TReturn`, `QRCodeNode`, `PrStatistics`, `CpuInfo`, `HsLayerManagerService`, `HasAttributeExpr`, `ManifestBuilder`, `PromptModule`, `Migration`, `RestEndpoint`, `PaginateConfig`, `ParsedColorValue`, `SerializationOptions`, `TextPlacements`, `UnitNormArgs`, `VerifyConditionsContext`, `Degrees`, `LayerPanel`, `TestCallback`, `OhbugConfig`, `EntitySchemaField`, `EntityActionFactory`, `SqlHelper`, `I18nFeature`, `SavedObjectReference`, `ServiceModule`, `ApiRx`, `DescribeCodeReviewCommandInput`, `ServerClient`, `HighContrastMode`, `BackendService`, `IRead`, `PersistedStore`, `ICompileOptions`, `RuntimeEnvironment`, `LogStackedLayout`, `SpriteBaseProps`, `IParticleSystem`, `LegacyAPICaller`, `OutputPort`, `TXReport`, `DispatcherEmitter`, `PrepareOptions`, `ThemeSettingsBreakpointAny`, `DockerFacade`, `JSDocNullableType`, `SecureNoteData`, `SpotMarketConfig`, `EncoderOptions`, `UpdateClusterResponse`, `FilterExpression`, `StorageManagementClient`, `ContractAddresses`, `LiteralTypeNode`, `Readme`, `DisplayOptions`, `SystemManagerImpl`, `egret.Shape`, `RedisStore`, `TestingWindow`, `LitvisDocument`, `VideoType`, `HubProduct`, `ModelCache`, `CSC`, `NotificationRequest`, `Statistics`, `WriteOptions`, `RTCRtpSendParameters`, `Try`, `OpenSearchDashboardsReactNotifications`, `DocgeniHost`, `RBNFSetBase`, `ListenerOptions`, `Locatable`, `PureTransitionsToTransitions`, `GfxInputLayoutP_GL`, `CreateWebACLCommandInput`, `PrivateAuthenticationStore`, `ProfileState`, `MikroORMOptions`, `IUserDto`, `GeomGraph`, `TransactionsBatch`, `ConfigHandler`, `MatchedPointType`, `AppTheme`, `LogObject`, `ViewportCallback`, `DateFormat`, `LiveMap`, `EntityCompanionDefinition`, `CorrelationIdGenerator`, `ELEMENT`, `IVConsoleNode`, `KCDLoader`, `IBooleanFlag`, `StackItemLike`, `PositionNode`, `Diffs`, `NotificationDataOptions`, `DomainBudget`, `PreKeyBundle`, `SCN0_LightSet`, `IChoiceGroupOption`, `ts.ForInStatement`, `TimeTrackingEntryIded`, `UrlWithStringQuery`, `VariableStatement`, `ObjectContext`, `Gui.Widget`, `AttributeReader`, `IVirtualDeviceValidatorResultItem`, `RQuota`, `NavigationProps`, `CreateIdentityProviderCommandInput`, `RestResponse`, `IdempotentParameterMismatchException`, `CapacityReservation`, `ChannelUpdateMessage`, `FieldRenderProps`, `IMemoryDb`, `MapFnOrValue`, `JSONSchemaSettings`, `IDeltaManager`, `FriendshipPayload`, `VTTCue`, `TypingsData`, `React.FormEventHandler`, `InstantComponentTransformation`, `NearestPointOnLine`, `ApiDoc`, `SimpleItemPricing`, `Pagerow`, `MappingItem`, `SelectorItem`, `TriumphRecordNode`, `OpenSearchDashboards`, `KeyCurve`, `Point3d`, `SeriesParam`, `Index`, `MarkdownService`, `HTMLTableElement`, `ToRunType`, `ReadModelStore`, `Array2DHashSet`, `VisualizeInput`, `FileWriter`, `TransactionInfo`, `ViewStateProps`, `ItemValue`, `Dishes`, `AddApplicationReferenceDataSourceCommandInput`, `SearchConfig`, `PlayerId`, `PopupDispatcher`, `ModifyEventSubscriptionResult`, `Attr`, `ALObjectWizardSettings`, `InstanceSummary`, `UtilityService`, `IBsLoadingOverlayOptions`, `MatRadioButton`, `DocumentSelector`, `TestingProject`, `ProviderItem`, `ResizeOptions`, `HistoryQuery`, `FilterMetadataStatusValues`, `BlockType`, `RepositoryRepository`, `EditorInspectorService`, `SessionRequest`, `FormBuilderService`, `Repeat`, `IAmazonNetworkLoadBalancerUpsertCommand`, `GherkinDocument`, `Quaternion`, `LangType`, `DataLayout`, `RumInitConfiguration`, `MinionStatus`, `DAL.DEVICE_ID_DISPLAY`, `PullState`, `SpacePropValues`, `Moon`, `VisibilityGraph`, `ClearingHouse`, `Benchmark.Event`, `FilterHeadersStatusValues`, `RedirectTask`, `IPackagesService`, `SpriteService`, `ConversationRecognizer`, `AutoconnectConfig`, `IAppDef`, `UpdateVpcLinkCommandInput`, `GLfloat2`, `BodyInit`, `StagePanelsManager`, `IParallelEnumerable`, `ifm.IHeaders`, `FeeType`, `postcss.Container`, `AzureNamingServiceOptions`, `request.Response`, `SymbolVisibilityResult`, `LngLatBounds`, `DBusClient`, `EventOptions`, `DataSourceService`, `MatrixItem`, `ErrorToastOptions`, `SplitAreaDirective`, `SelectionState`, `ConfigRuntime`, `HTMLIonContentElement`, `IWorkflowDb`, `ActionTicket`, `IUIField`, `MultiRingBufferReadableStream`, `QueryLanguage`, `SparqlItemService`, `AsyncQuery`, `TreeViewExpansionEvent`, `RadioGroup`, `SliderState`, `CommerceLayerConfig`, `DebugProtocol.AttachResponse`, `BuildPageRangeConfig`, `apid.RuleSearchOption`, `PokemonSet`, `ElementGeometryResultOptions`, `SubscribeResult`, `callback`, `CustomState`, `Next`, `Ids`, `OcsShare`, `ReplyChannelRangeMessage`, `IdType`, `BinaryValue`, `FieldView`, `OpenAPIParser`, `DescribeServicesCommandInput`, `FaastError`, `BrowserWindowRef`, `dia.Paper`, `SWRInfiniteKeyLoader`, `TerminationStrategy`, `AddArrayControlAction`, `SDKBase`, `Boolean`, `SwitcherItemWithoutChildren`, `Nuxtent.Query`, `TileDescriptor`, `ApplicationCustomizerContext`, `SpeechContext`, `TaskEither`, `BinaryExpression`, `IMyOptions`, `SplitTest`, `LineString`, `SVSize`, `TileMeta`, `NavigationTreeViewModel`, `PaymentsError`, `NodeInstance`, `ITranslation`, `ModuleNode`, `DeleteObjectCommandInput`, `CreateListenerCommandInput`, `ISimpleGridEdit`, `ZeroXPlaceTradeDisplayParams`, `SelectorCache`, `PlotAreaOptions`, `TypeElement`, `JsonRpcSigner`, `KanbanSplitResult`, `DecoderResult`, `TimeBucketsConfig`, `IgnoresWrappingXmlNameCommandInput`, `KeyType`, `apid.ProgramGenreLv1`, `QuicTags`, `DataMapper`, `EfParticle`, `OncoprintModel`, `FileSystemAdapter`, `Watching`, `virtualFs.Host`, `MaestroTipoModel`, `CoreDependencies`, `MapPartsShadowType`, `ClientLibraryState`, `ClassNameCollector`, `LocalFileName`, `FileUpload`, `DbList`, `CompleteLayerUploadCommandInput`, `OrganizationConfig`, `alt.Entity`, `WebHook`, `ForgedResponse`, `GX.IndTexBiasSel`, `DiffColumn`, `OnCameraFrameCallbackResult`, `CertificateDTO`, `tf.Tensor3D`, `InjectedIntl`, `EventTypes`, `AgentPolicy`, `ILocale`, `ArgonWebView`, `IdeaTags`, `EPerson`, `PlaybackState`, `IItemUpdateResult`, `IInstantiationService`, `EventBuilder`, `ISolutionWithFileIds`, `CompositeCollectionJavaIterator`, `ErrorCorrectionLevel`, `CameraContext`, `IWhitelistUserModel`, `ts.AnyObject`, `TextChunk`, `BemToBlockClassMap`, `DateHelperService`, `CkbTxInfo`, `UniListItem`, `PendingSuiteFunction`, `TexChunk`, `Suite`, `SelectedGroups`, `SonarQubeMeasureResponse`, `AuthenticationHeaderCloud`, `ResolvedGlTF`, `ConnectListener`, `IForwardIterator`, `SelectionMode`, `FilterStateStore`, `MdcDialogConfig`, `d.TransformCssToEsmInput`, `CDPSession`, `IRawOperationMessage`, `DeleteWorkspaceCommandInput`, `FilterComponentSettings`, `DialogSource`, `PlasmicLoaderConfig`, `msRest.HttpRequestBody`, `RxjsPipeline`, `CdkTableDataSourceInput`, `DataDirection`, `SequenceExpression`, `FunctionToMemoize`, `PrimaryFeaturePrivilege`, `TCacheKey`, `ScreenState`, `ResourceFetcher`, `s.CodeGeneratorRequest`, `HdPrivateKey`, `TSFile`, `RumPerformanceEntry`, `VertexAnimationEffect`, `HierarchyParents`, `MaybePatterns`, `ActionsService`, `ElasticsearchBoolQueryConfig`, `GrabListener`, `SchemaProvider`, `RARCFile`, `Matrix2x3`, `AWS.DynamoDB.DocumentClient.Key`, `OpenSeaPort`, `DesugaringContext`, `SessionOnDisk`, `SavedObjectsClientProvider`, `FieldFormatter`, `TypedDictEntry`, `UpdateDistributionCommandInput`, `ListSourceApplicationsRequest`, `AnimatedClock`, `IComponent`, `TypeAnnotationNode`, `UserMedia`, `UrlPropertyValueRenderer`, `PublicAppInfo`, `NZBResult`, `IMyDate`, `AbiOwnershipBody`, `Air`, `DeviceClass`, `IntersectionObserver`, `TrackingInfo`, `DirectSpiral3d`, `LoginSuccessCallbackResult`, `ListServiceQuotasCommandInput`, `ts.GetAccessorDeclaration`, `AddTagsInput`, `ClassifyService`, `TokenFlags`, `RoleContext`, `ScopeMap`, `ChannelEthContract`, `AutoImportSymbol`, `SpreadAnalysisResult`, `ChunkContentCallbackArgs`, `DrawerControl`, `DecodedToken`, `ClientStatus`, `GithubGlobalConfig`, `IInputList`, `DefineComponent`, `UITextPosition`, `PrivateUser`, `CombinedJobWithStats`, `ReduceArguments`, `IStateContext`, `FramerAPI`, `Dialog`, `IExecutionContextProvider`, `Affect`, `FrameEntryType`, `ImagePipeline`, `IntegrationTenantService`, `Articles`, `RenderRule`, `TypedAxiosResponse`, `IPlugin`, `ContributionProposal`, `StartStopSingle`, `IndexerManagementModels`, `TransferDetails`, `ACLService`, `IParameterDefinition`, `ValidationRuntimeOptions`, `TLE.FunctionSignatureHelp`, `UnusedAttribute`, `FilterBuilder`, `SupervisionContext`, `ConversionType`, `RequestApproval`, `SnackbarType`, `ResolutionConfig`, `Aggs`, `FadingFeatureParameters`, `THREE.OrthographicCamera`, `MessageResp`, `ISetCategoricalFilter`, `LegendPosition`, `THREE.WebGLRenderTarget`, `FTPResponse`, `SuiLocalizationService`, `CiBuildInfo`, `RangeFieldMeta`, `RenameModuleProvider`, `UnformattedListItem`, `HealthCareApisClient`, `PermissionOverwrites`, `ProjectLocale`, `IAssetTag`, `ProductControlState`, `ObjectId`, `SugiyamaLayoutSettings`, `InterleavedBufferAttribute`, `DeleteDatasetResponse`, `ViewerEventType`, `ITagsState`, `CurrentMoveInfo`, `TouchList`, `IMask`, `RecurringBill`, `CSSStyleDeclaration`, `HomogeneousPatternInfo`, `TransitionDoneFn`, `SubscriptionDiagnosticsDataTypePriv`, `ConnectController`, `WorkspaceConfiguration`, `GenericType`, `OauthSession`, `IProfile`, `VertexDeclaration`, `TFLite`, `LinearGradient`, `ProcessQueue`, `Peer`, `ClassAndSelector`, `EPerspectiveType`, `TableState`, `Projector`, `ts.TransformationContext`, `RangeContext`, `Decorations`, `TimeSeriesMetricDataPoint`, `ICustomFunctionParseResult`, `DateRangeInputProps`, `HSD_TEArg`, `ForwardingConfig`, `RpcRouter`, `App.storage.IStorageApiWrapper`, `Chart`, `CallbackEntryHelper`, `BooleanNode`, `SGroup`, `Patch`, `ElasticsearchConfigType`, `QueueModel`, `IVisibilityJobPostInput`, `DecoratorFn`, `MetronomeNote`, `BundlingOptions`, `CacheContext`, `ethersProviders.Provider`, `PrimaryButtonProps`, `UniLoginSdk`, `AnalyzableProperty`, `BatchProcessResponse`, `L.List`, `TextToSpeechClient`, `LastfmTopTracks`, `StorageState`, `AnalysisResult`, `StringListNode`, `nock.Scope`, `CreateProjectRequest`, `StyleClasses`, `RPCRequest`, `IConfigurable`, `DeleteYankChangeAction`, `SVGPolygonElement`, `TransformId`, `GX.TexGenMatrix`, `TwoFactorEmailRequest`, `StubBrowserStorage`, `IFooter`, `ConnectionEvent`, `RenderOutput`, `CookieService`, `BinaryEngine`, `TimePoint`, `TagModel`, `RoverWorkload`, `TryPath`, `CodeBuild`, `Intl.DateTimeFormat`, `ExecutionState`, `SignatureData`, `Continue`, `UserPositionsAccount`, `ShorthandProperty`, `FilterFormatterFunction`, `RMSPropOptimizer`, `MetaData`, `AuthTokens`, `GanttGroupInternal`, `AnyState`, `HomebridgePlugin`, `ThyOptionSelectionChangeEvent`, `Db`, `ITimelineData`, `ExtractControlValue`, `Host`, `TypeScriptServerHost`, `OrderBy`, `IFormatterParserResult`, `ace.Editor`, `ChannelMessageUpdate`, `IDEntry`, `EvaluatorFlags`, `InitializationData`, `CephLine`, `SampleUser`, `NineZoneStagePanelManager`, `EditPhotoDto`, `FeedbackActions`, `InitAckChunk`, `comicInterface`, `GethRunConfig`, `paper.CompoundPath`, `VercelClientOptions`, `ProjectVersionMeta`, `DeleteStorageObjectsRequest`, `CurrencyOption`, `TransportTime`, `puppeteer.JSHandle`, `SubscribeState`, `MiddlewareType`, `MutableColorRgba`, `RunContext`, `CtxLike`, `ReminderFormatType`, `SignatureHelpParams`, `NineZoneStagePanelManagerProps`, `Before`, `ImportRecord`, `MethodVisitor`, `PropertyDeclarationStructure`, `NgModule`, `MessageKind`, `ResourceField`, `TMethod`, `AggregatedColumn`, `Magma`, `MouseEvent`, `UpdateStreamCommandInput`, `EnvoyHttpRequestInit`, `TimestampManager`, `PartsType`, `TodoListModule.Actions`, `ExtractActionFromActionCreator`, `Languages`, `SymbolIntervalFromLimitParam`, `sdk.SpeechRecognitionCanceledEventArgs`, `AppImages`, `IClusterContext`, `Networks`, `MetadataSchema`, `HTMLHRElement`, `I18nStart`, `DeserializeWireBaseOptions`, `HttpHandler`, `ContractTransactionOverrides`, `SystemPortalSelectionTag`, `DotnetInsights`, `DebugProtocol.ThreadsResponse`, `MigrationLifecycleStates`, `MessengerData`, `WritePayload`, `ParamsOfAppDebotBrowser`, `DatasetResource`, `PrincipalTokenCurveTrie`, `chrome.runtime.Port`, `MapPoint`, `Filler`, `DigitalComponent`, `Entity`, `UserRoleService`, `TransactionFormState`, `JsxAttributes`, `DropdownProps`, `Clipper`, `AssetEvent`, `OutputType`, `Arity`, `Dictionary`, `TestResource`, `ConsoleTransportInstance`, `IncrementalQuinTree`, `UseGoToFormConfig`, `UIFont`, `triggeredTrap`, `FlowExhaustedMatch`, `vscode.OpenDialogOptions`, `FormFieldPreviousValueObject`, `AuthActions`, `VideoRateType`, `ISnapshotOptions`, `GitBuffer`, `Contributor`, `AvailabilitySlotsService`, `AccountStellarPaymentsConfig`, `ViewSize`, `BrowseCloudBatchJob`, `SearchItem`, `VideoPreference`, `NextCallback`, `Processed`, `LambdaFunction`, `DropResult`, `IModDirection`, `IApiStashTabSnapshot`, `OrganizationalUnit`, `ClientCredentialsResponse`, `StateReaderObservableEither`, `VersionArray`, `TrackedAbility`, `NormalizeContext`, `SubscribedObject`, `OutputChannel`, `BuildingFacade`, `LocationDescriptor`, `NotificationCallback`, `StickyVirtualizedListProps`, `Unbind`, `ICommitAuthor`, `Models.OrderStatusUpdate`, `StateWrapper`, `PkgJSON`, `ModelSpec`, `IMedia`, `RouteAction`, `BindingDescriptor`, `ELineTypes`, `LimitOrder`, `HotModuleReplacement`, `IOwnProps`, `ITaskAgentApi`, `BotTelemetryClient`, `TypeDefinition`, `MessageStatus`, `GenericTagId`, `RBNFRule`, `LnRpc`, `BoosterConfig`, `babel.ObjectExpression`, `IProblem`, `ContractMethodDescriptorClient`, `TaskResult`, `FunctionArgument`, `IAchievement`, `database.DataSnapshot`, `Formula`, `FindListOptions`, `EnabledPoliciesPlan`, `BufferArray`, `EnvoyContext`, `EntityMaterialParameters`, `Sync`, `CheckNodeResult`, `ODataPathSegmentsHandler`, `CodeBlock`, `ICredentialType`, `PlayOptions`, `WindowProtocol`, `UserRepresentation`, `IExtraArgument`, `SyncDBRecord`, `RecursivePartial`, `TriggerType`, `IconifyBrowserCacheType`, `coreClient.FullOperationResponse`, `AuthorizedClientRequestContext`, `ScriptLoaderService`, `BindingMetadata`, `MatDialogContainer`, `ServerRegion`, `CryptoCurrency`, `ProgressHandler`, `StringTable`, `SelectableListState`, `DataflowState`, `SplitLayoutNode`, `PoseNetConfig`, `UseFormValues`, `ConditionTypeEnum`, `UpdateUserCommandInput`, `SectionComponent`, `IModify`, `WifiNetwork`, `IKeyboardFeatures`, `IScalingPolicy`, `TestFormComponent`, `FormattedExecutionResult`, `WorkflowModel`, `Namespace`, `AnnotationProviderBase`, `FirebaseApp`, `StylableTransformer`, `EidasResponse`, `CppRequestSpan`, `LangiumLanguageConfig`, `Tests`, `ParsedData`, `Flattened`, `DragHandle`, `TransitionService`, `FormatterConfig`, `Crumb`, `ListSettings`, `CompilerTargetHandler`, `HandPoseOperatipnParams`, `THREE.Vector3`, `OpeningHour`, `CookieSerializeOptions`, `DemoMeta`, `StringToUtf32`, `fs.ReadStream`, `ValidateResult`, `AggsStartDependencies`, `DropAction`, `CGAPIResourceHandle`, `ColorObject`, `DraftEditorCommand`, `PvsResponse`, `ManagementDashboardForImportExportDetails`, `MqttClient`, `Singleton`, `ErrorMessages`, `Facebook`, `bindable.BindingOptions`, `PlayerViewCombatantState`, `t.AST`, `Attendee`, `StatefulChatClientWithEventTrigger`, `OperatorToken`, `Ped`, `requests.ListViewsRequest`, `PanelSide`, `ListWorkRequestErrorsRequest`, `JsonClassTypeOptions`, `TDiscord.MessageReaction`, `ParsedNumber`, `KnownFile`, `NodeOutput`, `PDFTextField`, `QueryCreateSchema`, `CancellationId`, `IICUMessageTranslation`, `SqliteStatement`, `EdmxEnumMember`, `IHotKeyConfig`, `ValueAxis`, `ChangesType`, `LayoutElement`, `FeatureManager`, `LCH`, `ex.Scene`, `KeyVaultManagementClient`, `StyleResourcesLoaderNormalizedOptions`, `VerifiedStateUpdate`, `Taint`, `IAureliaClassMember`, `Toggle`, `ITargetReference`, `NofloComponent`, `RequestQueryParser`, `WorldBuilder`, `TestPage`, `CellRenderer`, `MediationRecipientService`, `BehaviorDescription`, `IApiServer`, `FindWithRegexCb`, `TrezorTransport`, `ICreatorOptions`, `ObjectRemover`, `ActivityService`, `FibaroVenetianBlindCCSet`, `WithdrawStakingRewardUnsigned`, `InternalServerErrorException`, `FeatureItem`, `V1DeleteOptions`, `ObservableThese`, `CodeMirror.Position`, `JsxAttribute`, `NzNotificationService`, `ConfigMigrator`, `GoogleAuthProvider`, `StateDecoratorAction`, `Marks`, `SVGStyle`, `UpdateDomainResponse`, `SafeParseReturnType`, `ArcadeBody2D`, `HalResource`, `BoardEvent`, `TreeviewItem`, `ParsingExtension`, `LinePointItem`, `TextVerticalAlign`, `ICircle`, `CreateGroup`, `NamedTensorMap`, `ExecuteResult`, `React.ReactNodeArray`, `server.TextDocument`, `LoadAction`, `UrlMapping`, `d.ComponentRuntimeMembers`, `PosSpan`, `SingleOrMultiple`, `DepListener`, `requests.ListStreamsRequest`, `JNICallbackManager`, `NavigationEvent`, `TSAudioTrack`, `ICancellable`, `SignalingClientSubscribe`, `ViewDefinition`, `Lane`, `ResourceConflictException`, `EventStore`, `AccountDetails`, `DOMInjectable`, `ErrorLike`, `ICompetition`, `NodeWithScope`, `BaseNode`, `DevtoolsInspectorState`, `RegionInfoProvider`, `C3`, `DebugProtocol.SetBreakpointsArguments`, `MVideo`, `MDCDrawerAdapter`, `ElasticSearchOptions`, `IProductCreateInput`, `IRating`, `MdxModel`, `apid.GetReserveListsOption`, `ExecutionRole`, `Stylable`, `BoosterGraphQLDispatcher`, `TuxedoControlCenterDaemon`, `RestElement`, `RaguServerConfig`, `RuntimeDatabase`, `PlaceholderReference`, `TrimmedDataNode`, `NavigationBarNode`, `TokenizerState`, `FormFieldType`, `KudosPollService`, `IConfirmProps`, `NamePath`, `ISubscription`, `requests.ListPublicationPackagesRequest`, `Archive`, `TextAlign`, `InstancedMesh`, `UserPhotosState`, `Z64Online_EquipmentPak`, `SnippetModel`, `SpriteVID`, `EncodeOption`, `GetDomainItemsFn`, `InterceptorManagerUseParams`, `ReportingDescriptor`, `JsxFragment`, `GroupInput`, `requests.ListConfigurationsRequest`, `EnhancementCache`, `ExtrusionFeature`, `BasicBlock`, `UnbindFn`, `TextDocumentContentProvider`, `CompileState`, `GroupMember`, `PageDependencies`, `HeatmapVisualizationState`, `MinMaxConstraint`, `UIDialog`, `CallSite`, `IMappingState`, `MockOptions`, `TranslatorService`, `ChemController`, `EffectPreRenderContext`, `ErrorTransformer`, `ToggleCurrentlyOpenedByRoute`, `MomentData`, `AgeRepartitionType`, `ITransitionData`, `TuplePage`, `PumpCircuit`, `CalendarContext`, `MspDataView`, `HdStellarPayments`, `ComputedStyle`, `IProjectWizardContext`, `TEX1_TextureData`, `MeiliSearch`, `CoreImageEnt`, `ID`, `ManyToManyPathMap`, `HookReturn`, `CasesClientMock`, `UA`, `Solar`, `PrismaClientRustPanicError`, `AnnotationControllable`, `EmbeddedViewRef`, `AsyncHierarchyQuery`, `ProjectionMetadata`, `NotificationStartedInfo`, `ISubView`, `Keymap`, `GetDeviceCommandInput`, `IterationTypes`, `BookmarkTreeItem`, `CursorQueryArgsType`, `requests.ListHttpRedirectsRequest`, `StaticConfig`, `Models.Timestamped`, `IEmailOptions`, `ELU`, `unwrapContext`, `SmallMultiplesSpec`, `NativeStorage`, `ast.QuoteNode`, `TestStepResultStatus`, `MatrixDynamicRowModel`, `GetTokenResponse`, `ITransactionData`, `AriaLivePoliteness`, `CliScriptGenerator`, `ThyFormValidatorGlobalConfig`, `IDynamicPerson`, `QObject`, `IHubSearchOptions`, `JestExtRequestType`, `PointModel`, `JsonUnionsCommandInput`, `PostProcess`, `Model.Element`, `TokenDocument`, `requests.ListIPSecConnectionTunnelSecurityAssociationsRequest`, `StepVariable`, `sdk.TranslationRecognizer`, `SupervisionCCGet`, `HostStatus`, `CmsService`, `J3DModelData`, `ServiceList`, `ApplicationCommand`, `IIconItem`, `Pick`, `RecvDelta`, `RemoteRenderInfo`, `AccountStatus`, `ClassProperty`, `ClassResources`, `PrismTheme`, `UnitOfWork`, `pxt.Asset`, `ContainerRegistry`, `CoreTypes.TextAlignmentType`, `InternetGateway`, `messages.TestStepResultStatus`, `AqlQuery`, `OptionsService`, `UserAsset`, `TreeViewInfo`, `Strings`, `OutputGroup`, `pf.StackContext`, `SchemaValidatorFunction`, `ListContext`, `DataEntity`, `IGetTimesheetInput`, `ModdedDex`, `html.Element`, `ts.ArrayTypeNode`, `ToggleType`, `PartyCreate`, `OptionalObjectSchema`, `TransportConfiguration`, `MapLeafNodes`, `ReadOnlyReference`, `PawnFunction`, `HostState`, `DeleteApplicationOutputCommandInput`, `ServiceBase`, `IEndpointSpec`, `DispatchFunction`, `String`, `IInvoice`, `RTCPeerConnection`, `Parser.SyntaxNode`, `TreeModelNodeInput`, `LoopConverter`, `TypeOrmHealthIndicator`, `TranslationWidth`, `Http3RequestNode`, `QuestionStatus`, `RelationPattern`, `ImportNameWithModuleInfo`, `ParsedTsconfig`, `WayPoint`, `SharedDirectory`, `InvalidArnException`, `IQService`, `LocationInfo`, `RoutableComponent`, `MuteConfiguration`, `AlainAuthConfig`, `CreateScriptCommandInput`, `XMLElement`, `FourSlash.Range`, `Accessibility.ChartComposition`, `StakingCall`, `HtmlTag`, `RouteParam`, `BrowserLaunchArgumentOptions`, `SavedObjectOpenSearchDashboardsServicesWithVisualizations`, `FontInfo`, `API.storage.PrefObserverFactory`, `ILoader`, `Timetable`, `SliceAction`, `TSelections`, `AsyncHooksContextManager`, `Multicast`, `NativeView`, `FeatureKibanaPrivileges`, `Variables`, `ImportLookupResult`, `SecretManagerServiceClient`, `GlobalEventDispatcher`, `IVideoPlayerState`, `RedditComment`, `THREE.ShaderMaterialParameters`, `PathParams`, `CopyResults`, `requests.ListVnicAttachmentsRequest`, `Nameserver`, `AudioContextManager`, `Wiki`, `ConfigSetter`, `FSOperator`, `PyrightJsonResults`, `StreamReader`, `vscode.Selection`, `CreateEventSubscriptionCommandInput`, `VisitedItem`, `DiscordUser`, `InputType`, `IComponents`, `OctokitProvider`, `TestConfig`, `GenericRequestMapper`, `PropertyChangeData`, `MentionsState`, `paper.ToolEvent`, `KeyCode`, `L.Map`, `WlPeer`, `BaseAdapterPool`, `EnumTypeComposer`, `HypermergeWrapper`, `ProjectConfiguration`, `CompletionEntryDetails`, `IDOMRule`, `IGitAccount`, `IPluginAuth`, `V1CustomResourceDefinition`, `LocationChange`, `RulesProvider`, `AddressNode`, `requests.ListProtectionRulesRequest`, `Synthetic`, `UpdateCommand`, `UIViewAnimationTransition`, `Receipt`, `AddToLibraryActionContext`, `kChar`, `ZesaruxCpuHistory`, `PopupOptions`, `OwnProps`, `EventForDotNet`, `ListDeploymentsCommandInput`, `ContractsSection`, `IDatepickerLocaleValues`, `AuthorizationService`, `IOSDependencyConfig`, `StorageHelper`, `TimerInfo`, `ChannelMessageAck`, `CardRequirements`, `Danmaku`, `ListWorkRequestsResponse`, `INgWidgetEvent`, `ScaffdogError`, `PrimedGroup`, `TiledMapFeatureData`, `LogSampleTimestamp`, `DAL.DEVICE_ID_BUTTON_A`, `TLE.FunctionCallValue`, `ClippedRanges`, `AlignmentDirectional`, `AbstractControlState`, `ResolvedFunctionTypeParam`, `Technical`, `DirectiveHook`, `NTPTimeTag`, `FileBrowser`, `ICompareValue`, `MiRectConfig`, `AnyShape`, `ISeriesApi`, `EditModes`, `DecorateContext`, `TemplateExecutor`, `JSXContext`, `ContractFraudProof`, `BubbleSeries`, `LifelineHealthCheckResult`, `HitSensor`, `ViewAction`, `MatomoTracker`, `PanInfo`, `VectorOrList`, `Static`, `Distribution`, `KirbyAnimation.Duration`, `DAL.DEVICE_ID_BUTTON_AB`, `DeleteDetectorCommandInput`, `DeployLocalProjectConfig`, `RouterConfigOptions`, `SPDestinationNode`, `StandaloneDb`, `ClientAPI`, `MenuItemType`, `RouteComp`, `ConnectionPool`, `estypes.SearchHit`, `ContractInstance`, `Unregistration`, `IrecService`, `RouteSegment`, `AccessorCache`, `ConfigMap`, `OutHostPacket`, `FlipSetting`, `CookiesFilterParams`, `LiteElement`, `Htlc`, `SignalRConfiguration`, `NetworkPluginID`, `IMidwayContainer`, `Pair`, `ActionPlugin`, `DeleteSessionCommandInput`, `TransferItem`, `MessagingOptions`, `IUserRole`, `YearProgressModel`, `UpdateRegistryCommandInput`, `BinSet`, `TELibCall`, `FIRQuerySnapshot`, `PresentationTreeDataProvider`, `ITooltipProperty`, `Token`, `GatewayConfig`, `sinon.SinonSpy`, `MagitRemote`, `RequestPayload`, `TextOrIdentifierContext`, `IAuthUser`, `TestingUser`, `GUIController`, `FilterDefinition`, `SpriteArray`, `JsxChild`, `ExistingAccountError`, `ResponsiveProperties`, `HTMLIonToastElement`, `ObjectID`, `VsixInfo`, `DescribeHomeRegionControlsCommandInput`, `Tooltip`, `ImportNamespace.Interface`, `QuadrantDirection`, `RunLengthChunk`, `Keplr`, `DocumentSymbol`, `VideoInputDevice`, `common.Region`, `VisibilityMap`, `PopupManager`, `CallMethodResult`, `ListChannelMessagesCommandInput`, `CancelSubscription`, `PackageFiles`, `IConfiguration`, `TestEntry`, `EYaml`, `RouterDirection`, `TList`, `DeleteUser`, `CacheValue`, `PDFAcroTerminal`, `ImgAsset`, `StatefulCodeblock`, `SystemStats`, `ShareUserMetadata`, `SlideDirection`, `EventMessage`, `Dereferenced`, `PolymorpheusContent`, `IPageModel`, `InjectorServer`, `Events.pointerwheel`, `WorkspaceHost`, `TypesImportData`, `MalformedPolicyDocumentException`, `MigrationDiff`, `Vis`, `DiscogsReleaseInfo`, `SxParserState`, `jsPDF`, `WssRoom`, `SyncStore`, `HsLayerDescriptor`, `IdeaEntity`, `IBranding`, `CopyDescriptor`, `CallStatus`, `StatusAction`, `AggsCommonSetup`, `types.IActionContext`, `Hub`, `StellarSignatory`, `InteractionSettings`, `FlatVector`, `TextDocument`, `Contract`, `INestMicroservice`, `TestSourceIO`, `LinkedHashMap`, `Portable`, `TronUnlock`, `Generics`, `instantiation.IConstructorSignature8`, `PublicUser`, `PeerSetupWithWallets`, `vec4`, `Multi`, `RegInfo`, `monaco.editor.IStandaloneCodeEditor`, `XLSX.WorkBook`, `ZoomSettings`, `AbstractVector`, `StatusCodes`, `TransientBundle`, `GoogleAnalyticsService`, `uproxy_core_api.Update`, `GitTagReference`, `NotificationColumnFilters`, `Registration`, `EpochIteratorConstructor`, `TextureState`, `Colord`, `IVocabularyTag`, `BoardSlice`, `XYState`, `ImageData`, `FunctionC`, `MockModelRunner`, `ParserEnv`, `AnimGroup`, `InstanceNamedFactory`, `Tensor2D`, `JSX.TargetedKeyboardEvent`, `VisTypeDefinition`, `Operands`, `EChartOption`, `BackupRequest`, `IScalingProcess`, `ReactionMenuState`, `null`, `StudyConstraint`, `HsLayerSelectorService`, `StaticOperatorDecl`, `ApiKeyProps`, `d.CompilerJsDocTagInfo`, `FindManyOpts`, `ELBv2`, `BasePrismaOptions`, `InputControlVisDependencies`, `ErrorBarStrings`, `DiscussionReplyEntity`, `StoreEnhancerStoreCreator`, `WebGLRenderingContextExtension`, `EntityName`, `EnhancedGitHubEvent`, `ThyTableGroup`, `PiecePosition`, `InternalRouteInfo`, `IServerGroup`, `AssociationCC`, `CandleLimitType`, `HealthCheckService`, `LoadEvent`, `VersionedSchema`, `MissingItem`, `IGCNode`, `TokenVerifier`, `WillExecutedPayload`, `SomeInstance`, `BlockedRequester`, `ColorComponent`, `GithubAuthTokenRepository`, `LineItem`, `CellConfig`, `ResumeNode`, `MessageConversation`, `FakeNumericDataset`, `ApiChanges`, `MediaItem`, `EntityCollectionCreator`, `TimelineDivisionBase`, `SnapConfig`, `ReqWithUser`, `ColonToken`, `SkinId`, `BackstageItemsManager`, `ReadableStreamDefaultReadResult`, `StaticPathLoader`, `UpdateChannelResponse`, `Resolved`, `IconData`, `Tokens`, `DisposableObservable`, `ChartKnowledgeBaseJSON`, `LoadConfigInit`, `SelectionLocation`, `MIRInvokeBodyDecl`, `VisibleBoundary`, `GoogleWebFontData`, `WebhookPayload`, `MigrationsContract`, `KeyboardLayoutData`, `ComponentTable`, `d.SitemapXmpOpts`, `IMoveDescription`, `DirectoryWatcher`, `USampler3DTerm`, `KMSKeyNotAccessibleFault`, `MarkdownSimpleProps`, `IDelta`, `PropertyConverterInfo`, `FfmpegCommand`, `TypescriptServiceClient`, `StateTransition`, `MdcDialog`, `IAppState`, `SystemState`, `ClassLikeDeclaration`, `SymbolOptions`, `TokenConfigs`, `BinaryEncoding`, `IContainerType`, `PersistedLog`, `UsageCollectionPlugin`, `instantiation.IConstructorSignature6`, `IBlockchainObject`, `DecipherGCM`, `DecodeContinuouslyCallback`, `cloudwatch.Metric`, `TaggedState`, `AggTypeAction`, `JProject`, `LayoutOption`, `NETWORK`, `IFoundElementHeader`, `UserBuildConditionals`, `TreeResult`, `TensorOrArrayOrMap`, `EqualFunc`, `_Connection`, `ContentLayoutDef`, `CombinedField`, `Accent`, `SelectQueryBuilder`, `TransformerArgs`, `ItemContext`, `TrackInfo`, `ClickSource`, `IEmbedVideoOptions`, `ThyFlexibleTextComponent`, `PipelineNode`, `PayloadBundleSource`, `PaginationParams`, `vscode.Location`, `RepositoryCommonSettingValueDataType`, `TexturizableImage`, `ProviderInput`, `ICassExploreModuleState`, `HttpConfig`, `LanguageService`, `VariantType`, `HaliaPlugin`, `FeaturedSessionsActions`, `ChatFlowPack`, `LayoutPane`, `ThemesTypes`, `OrderedHierarchyIterable`, `MockResponseInit`, `MouseDownEvent`, `React.PropsWithoutRef`, `CollectionService`, `Blobs`, `ParameterToken`, `CaseReducerActions`, `Vec2Sym`, `PriceHistoryMap`, `DiffPatcher`, `DeleteContactCommandInput`, `JwtHeader`, `AnyTable`, `IMockEvent`, `ElementDefinitionContext`, `VersionConstraintContext`, `TruthTable`, `ISPTermObject`, `GfxrAttachmentClearDescriptor`, `HdLitecoinPaymentsConfig`, `Monad2`, `SchemaInput`, `TLeft`, `DisplayValuePropertyDataFilterer`, `CreateJoinQueryOptions`, `HeaderGetter`, `StorageModuleOptions`, `WorkspaceSetting`, `KintoObject`, `ReplayContext`, `HtmlProps`, `DocumentLink`, `ModLine`, `IAstElement`, `ValueResolver`, `IRequestHeaders`, `CellPlugin`, `WebWorkerEnvironment`, `ArrayBufferLike`, `Entity.Status`, `NextPage`, `ConfigInfo`, `ExternalSourceFactory`, `OpenSearchInterval`, `IStyle`, `SignedByQuantifier`, `DecodeOutput`, `NzTabSetComponent`, `PlayerStatus`, `CardCommon`, `ConfigRoot`, `ExecutionStatus`, `CephAngle`, `TasksState`, `QueryResultProps`, `Rating`, `ExtendedUser`, `RebirthWindow`, `LogSource`, `P3`, `GridItemHTMLElement`, `GroupBy`, `ICheckboxProps`, `FsWriteOptions`, `GitService`, `d.HostRule`, `EntityMap`, `TransformCssToEsmInput`, `NullableLocatable`, `XSLTToken`, `PartialExcept`, `CellRepo`, `JavaScriptDocument`, `GroupOrName`, `LQuery`, `InvalidateMask`, `LanguagesEnum`, `ListContentConfig`, `PodSecurityPolicy`, `NativePlaceTradeChainParams`, `Github.PullRequestsGetResponse`, `BuildingTree`, `ViewportSize`, `DepthwiseConv2DLayerArgs`, `CommandLineParser`, `ScanArguments`, `IconSettings`, `ArmService`, `IDataState`, `Branched`, `CompletionContext`, `Klass`, `ManualConflictResolution`, `T5`, `JsonfyDatasource`, `DefinerClauseContext`, `JssState`, `NoneType`, `BoardBase`, `ObjectUpdatesEntry`, `ExceptionType`, `IEcsServerGroupCommand`, `SetOpts`, `TaskSpec`, `RestOrderbookRequest`, `DOMMatrixInit`, `Parallelogram`, `QualifiedValueInfo`, `VisualizeSavedObjectAttributes`, `GlobalParametersService`, `IPostMessageBridge`, `HelmManager`, `Dog`, `SignalRService`, `XmppChatAdapter`, `DataSink`, `RawBlock`, `Ninja`, `HybridOffsets`, `BrowserControllerReturn`, `SwitchWatcher`, `IntersectionInfo`, `SyncState`, `TypeClass`, `EventsFactory`, `DayCellStyle`, `ParsedStructure`, `Bucket`, `FunctionFragment`, `PopoverPosition`, `IOrganizationDepartmentCreateInput`, `TxParams`, `requests.ListLoadBalancersRequest`, `Hsv`, `CuePoint`, `BreakpointMap`, `Node.Node`, `ContentReference`, `RecordData`, `DropListRef`, `ethereum.CallResult`, `CLM.Template`, `UpdateState`, `FastFormFieldMeta`, `GeometricElement3dProps`, `ContractFunctionEntry`, `DeleteServiceCommandInput`, `ECH.CommandClient`, `ScopeType`, `FileTransport`, `ts.SignatureDeclaration`, `Graphic`, `DejaViewPortComponent`, `http2.ClientHttp2Session`, `CSS.Properties`, `DirectiveList`, `ComponentEnhancer`, `TransactionCache`, `ActionResult`, `MiToolsSyncData`, `PacketChunk.TypeTCCStatusVectorChunk`, `ElementGeometryInfo`, `configuration.LaunchConfiguration`, `CreateManyInputType`, `ClientCardIded`, `SecurityRule`, `CANNON.Vec3`, `d.SourceTarget`, `CompositeSubscription`, `Place`, `OptionalDefaultValueOrFunction`, `IpcAPI`, `BitcoinBalanceMonitor`, `PublicRelayerConfig`, `JobId`, `Biota`, `NodeCreator`, `ConciseBody`, `OpenNodeTracker`, `Degree`, `CeramicCommit`, `CreateAppFunction`, `ConflictNode`, `ResourceSource`, `Option`, `IncludeRecord`, `Cart`, `IRouteMatch`, `ResponsiveService`, `ChatMessage`, `RpcMessageData`, `FloatFormat`, `NewWindowWebContentsEvent`, `HitDetail`, `NexusScalarTypeDef`, `UseCaseExecutor`, `IUserOrganization`, `SegmentAPIIntegrations`, `Broker`, `DMMF.ModelMapping`, `Oni.Plugin.Api`, `TypeKindEnum`, `CorePreboot`, `Snake`, `MarkdownTreeNode`, `GetMeetingCommandInput`, `YRange`, `QueryMap`, `PackagedNode`, `AcceptTokenResponse`, `TransportRequestOptionsWithMeta`, `d.TypeInfo`, `SMTCallSimple`, `ClipRectAreaModel`, `HistoryValue`, `Rest`, `FakerStatic`, `AZDocumentSymbolsLibrary`, `ProjectPost`, `RulesClientFactory`, `SymbolData`, `CreateEmManagedExternalExadataMemberEntityDetails`, `GherkinLine`, `Commune`, `RelationIndex`, `Translator`, `CommonState`, `StreamDescriptions`, `ReturnCode`, `GitUser`, `NetworkSubgraph`, `BaseStateContainer`, `IMutableGridCategoryItem`, `ListMigrationsRequest`, `GenerateInFolderOptions`, `DeleteAssociationCommandInput`, `S1`, `ImportAdder`, `TurnContext`, `IHttpInterceptController`, `BaseName`, `requests.ListConnectionsRequest`, `DrawEvent`, `JoinedEntityMetadata`, `IICUMessageCategory`, `RewriteAppenderConfig`, `GenericCompressorProperty`, `AnalyzableNode`, `NoticeToastRequest`, `CategoryChannel`, `SignedCipherObject`, `FKRow`, `MetricService`, `LiteralTypeBuildNode`, `FragmentElement`, `DocumentInterface`, `AuthorizeConfig`, `EthArg`, `T9`, `PointerCoords`, `IFuture`, `CompleterComponent`, `OpenSearchDashboardsLegacyPlugin`, `TemplateOutput`, `ProjectionType`, `Bm.Dest`, `AR`, `ListServersCommandInput`, `inquirer.Answers`, `ListReservationsCommandInput`, `ICircuit`, `GroupedTask`, `OperationLoader`, `ParamFunction`, `TxOutput`, `Gunzip`, `ImageTemplate`, `DataGroup`, `SlashingProtectionBlock`, `AuthenticatedSocket`, `requests.ListImageShapeCompatibilityEntriesRequest`, `ForceGraphLink`, `IJsonDocument`, `SchemaProps`, `ECPair`, `SubtitlesState`, `ErrorCode`, `JQuery`, `NamedFragmentDefinition`, `KratosService`, `ClassName`, `TTK1AnimationEntry`, `RelayModernEnvironment`, `BullBoardRequest`, `WebpackConfigurator`, `TestContract`, `CloudFrontRequestEvent`, `ColumnChartOptions`, `AClassWithSetter`, `GeoLocation`, `DateRawFormatOptions`, `LoadOpts`, `WudoohStorage`, `MigrationItem`, `AuthTokenService`, `Mode`, `DomService`, `CertificateConfigType`, `ABLDocument`, `IErrorsBySection`, `GridCellParams`, `IAbstractGraph`, `ErrorHttpResponseOptions`, `AnyExpressionTypeDefinition`, `MappingLine`, `PUUID`, `AdapterContainer`, `Generations`, `SBDraft2CommandLineToolModel`, `SpriteState`, `PromiseMap`, `LogicalType`, `HttpResponseCreated`, `MockCallback`, `CipherView`, `FloodProcessEnv`, `NodeStack`, `Events.pointerdragleave`, `HasShape`, `TenantSettingService`, `RawTransaction`, `TabRepository`, `SelfList`, `MeasureUnit`, `FileStatusBar`, `OutputContext`, `HelloMessage`, `E2EElementInternal`, `express.Handler`, `QueryListsCommandInput`, `TextLayoutStyle`, `TimeQuery`, `AggName`, `requests.ListStacksRequest`, `ResourceOptions`, `OidcProviderService`, `BooleanFilterFunction`, `KanbanBoardRecord`, `DeleteCertificateCommandInput`, `TraceSet`, `Response.Wrapper`, `GraphProps`, `IntersectionObserverCallback`, `GundbMetadataStore`, `ColumnNode`, `TestWorkspaceFactory`, `Operation`, `ApplicationContext`, `ml.Element`, `ExchangeQueryService`, `LogLevelValues`, `TestDoc`, `ApiResource`, `CreateResourceCommandInput`, `ProjectedPoint`, `DropdownItem`, `CALayer`, `BuildEntry`, `requests.ListNotebookSessionShapesRequest`, `ICategoricalLikeColumn`, `PropsWithChildren`, `SafeElement`, `DebugSession`, `INavigationData`, `ServerOptions`, `LendingPool`, `OutputTargetCopy`, `PusherChannel`, `JwtToken`, `pino.Logger`, `GroupDescription`, `requests.ListComputeCapacityReservationInstanceShapesRequest`, `ScrollItem`, `NodeLoadInformation`, `IPagination`, `ChartDataPoint`, `ThemeContextType`, `ZoomLevels`, `RegisteredMessage`, `PushContextData`, `CodeScopeProps`, `LanguageTag`, `ArticleState`, `ProfileInfo`, `CategoryProps`, `GeographicCRSProps`, `MatchedSegments`, `TrackQueryOpts`, `ProtocolNotificationType`, `jwt.SignOptions`, `ServerUtil`, `d.ScreenshotBuildData`, `ElementAction`, `IDataFilter`, `ISequencedOperationMessage`, `PayloadMetaAction`, `EventNames`, `TimerOptions`, `TableOfContentsEntry`, `JsonAtom`, `IPersonaProps`, `Sampler2DTerm`, `EdgeProps`, `AST.OperationNode`, `PlugyStash`, `OperatorEntry`, `VisualSettings`, `BinaryToTextEncoding`, `FSError`, `BB.Activity`, `HttpLinkHandler`, `Basis`, `DeleteJobTemplateCommandInput`, `ColumnMeta`, `Variance`, `ElementFinder`, `ListChannelMembershipsCommandInput`, `AccountActions`, `CommunicationParticipant`, `QueryParameterBag`, `HealthChecker`, `ValidatorFunctionType`, `NormalizedProblem`, `IRowProps`, `JIssue`, `PartialPerspective`, `PlainData`, `Authorizer`, `SqliteDatastore`, `MsgDeleteProviderAttributes`, `CoreTypes.TextTransformType`, `GuildDocument`, `MatchedItem`, `LocaleType`, `MqttOptions`, `HttpErrorResponse`, `Web3.TransactionReceipt`, `IConfigurationComponent`, `IExpenseCategory`, `ClassAst`, `BinanceConnector`, `Update`, `SubmissionService`, `SourceConfig`, `EtaConfig`, `SearchServiceStartDependencies`, `V1ConfigMap`, `ProcessedImportResponse`, `VueApolloRawPluginConfig`, `InvalidRestoreFault`, `IReport`, `XAxis`, `HttpStart`, `DbBlock`, `SortablePlayer`, `Abi`, `MdcDefaultTooltipConfiguration`, `ClassListing`, `BuildDefinition`, `LineAnnotationDatum`, `DinoRouter`, `IQueryInput`, `DeleteReplicationConfigurationTemplateCommandInput`, `GLclampf4`, `ILayer`, `ast.Node`, `Whiteboard`, `SendMailOptions`, `RAL.MessageBufferEncoding`, `ShadowRootInit`, `coreAuth.TokenCredential`, `ResourceLabelFormatter`, `SearchForLife`, `UpdateTargetMappingsWaitForTaskState`, `Attribs`, `ActionCreatorWithOptionalPayload`, `AddEventListenerOptions`, `Forecast`, `EdmTypeField`, `RangeSet`, `PLSQLConnection`, `Dealer`, `TreeType`, `ListIndicesCommandInput`, `GunScopePromise`, `CrudOptions`, `ActionTypeExecutorResult`, `STHConfiguration`, `TransmartConstraint`, `TFS_Build_Contracts.Build`, `DAL.KEY_T`, `DBDriver`, `GetInsightSummariesCommandInput`, `IPhase`, `CompilerErrorResult`, `DiagnosticOptions`, `WebSession`, `DeployProps`, `monaco.editor.IModel`, `SpreadSheet`, `StorageData`, `DiscordMessageProcessor`, `CalloutProps`, `ProductOptionGroup`, `UnitCheckboxComponent`, `CreateJobCommand`, `HeaderPair`, `ZBarInstance`, `IFieldPath`, `CircuitBreakerOptions`, `QueryHelperService`, `ResAssetType`, `TableColumnConfig`, `DeploymentSummary`, `ECSqlStatement`, `FirestoreAPI.Value`, `CurrentDevice`, `MdxModelInstance`, `SGItem`, `vscode.QuickPickItem`, `VfsObject`, `ApplicationListenerArgs`, `UpdateConnectionDetails`, `PropertyEditorInfo`, `MassMigrationCommitment`, `VectorArray`, `DRIVERS`, `StacksTransaction`, `VirtualData`, `WritableFilesystem`, `NotificationDocument`, `SwapOptions`, `ClientFile`, `HmiService`, `ListImportsCommandInput`, `HttpArgumentsHost`, `LegendStrategy`, `AspidaResponse`, `PeerService`, `AuthenticationDetailsProvider`, `OperatorDescriptor`, `RunCommandInput`, `Eq.Eq`, `PanelPoints`, `BottomBarArea`, `IMutableVector3`, `ConcreteRequest`, `MethodParams.ProposeInstall`, `MockUdpTally`, `ExpandableTreeNode`, `FileStat`, `AnimationEntryMetadata`, `ListIdentityProvidersRequest`, `Loop`, `LocaleTemplateManager`, `ValueOrLambda`, `Cached`, `ExecResult`, `STATUS`, `TraceSpan`, `JSDocNameReference`, `ts.VariableStatement`, `Toast`, `GetConfigCommandInput`, `MIRTupleType`, `StoredNetwork`, `OnDemandPageScanRunResultProvider`, `IFeatureComment`, `Finish`, `GetError`, `InfiniteData`, `FindSubscriptionsDto`, `ComponentTheme`, `MockAttributeMap`, `ZodType`, `AccountCustom`, `CommandExecutionContext`, `Scales`, `AnimVector`, `SettableUserCode`, `CancelSource`, `RawOperation`, `CoreConnection`, `ITreeNodeAttrs`, `t.SelectablePath`, `ISchemaGenerator`, `PCancelable`, `IQResolveReject`, `IButton`, `RenderPassContextId`, `I18nContextType`, `ListAssetsRequest`, `Installer`, `StylingBindingData`, `requests.ListKeysRequest`, `TestVectorResult`, `ITaskWithStatus`, `SyncTasks.Promise`, `ListReportDefinitionsCommandInput`, `AddonProperty`, `MsgCreateProvider`, `Workbench`, `ApplySchemaAttributes`, `ToolbarOrientation`, `SVGPath`, `CreateTestConfigOptions`, `SKFillItem`, `Foxx.Router`, `IProposalCreateInput`, `configuration.APIData`, `TestStream`, `SharedStreetsGeometry`, `EvaluatedMetric`, `KibanaPrivilege`, `FieldFormatId`, `GUI`, `HttpClientConfiguration`, `ExcaliburGraphicsContext2DCanvas`, `ImportCodeAction`, `DataFrame`, `FormFieldEditorComponent`, `MockResolvers`, `ComposedChartProps`, `WebpackChain`, `ListMultipartUploadsCommandInput`, `ResourceTag`, `RetryHelper`, `TreeNodeProps`, `ListTypeNode`, `CipherGCM`, `UpdateChannelMessageCommandInput`, `ConnectionConfiguration`, `DiffResult`, `BridgeContracts`, `DatabaseUser`, `SkillMapState`, `IEmailDomain`, `Logquacious`, `TypeRef`, `MergeStrategy`, `ProductModel`, `TokenRange`, `EmitterInstance`, `CurrencyCNYOptions`, `ProjectParser`, `StateTaskEither`, `MoveCheck`, `IPreviewProps`, `QueryProvidersResponse`, `providers.JsonRpcProvider`, `labelValues`, `IProjectRepository`, `Pen`, `BrowserHistory`, `React.ForwardedRef`, `RpcResult`, `BracketType`, `FnU4`, `Idl`, `OutputDefinitionBlock`, `PersonData`, `Mill`, `CustomQueryHandler`, `WorkspaceService`, `DoneInvokeEvent`, `ReleaseChangelog`, `IKeyboardDefinitionStatus`, `ConfigVersion`, `ts.server.ScriptInfo`, `JMap`, `MergeTree`, `requests.ListAvailableSoftwareSourcesForManagedInstanceRequest`, `GfxClipSpaceNearZ`, `AppInputs`, `Encryption`, `ELogLevels`, `Callsite`, `requests.ListAutonomousDbVersionsRequest`, `GenericDeviceClass`, `DisassociateFromAdministratorAccountCommandInput`, `pulumi.InvokeOptions`, `TexCoordsFunction`, `RenderPass`, `TEdge`, `EnumField`, `ArmSiteDescriptor`, `BoundMethodCreator`, `WalletService`, `ArcShape`, `IGESDocument`, `ObjectLiteralExpression`, `DAL.KEY_DOT`, `AWSPolicy`, `IServiceInjector`, `ServiceSummary`, `EffectResult`, `textFieldModule.TextField`, `OneOf`, `BuildInPluginState`, `InstancePoolInstanceLoadBalancerBackend`, `ExpressionAstExpressionBuilder`, `Knex.SchemaBuilder`, `AxisAlignedBounds`, `AppearanceMapping`, `VRMSchema.VRM`, `handler.Queue`, `TSerializer`, `Transformation`, `DataTypes`, `MapStoreState`, `ServerStyleSheet`, `IProfileModel`, `FormProps`, `NormalizedUrl`, `d.BuildCtx`, `TaskLabel`, `Yeelight`, `VisDef`, `EncryptionAtRest`, `BytecodeWithLinkReferences`, `GitReference`, `CLDRFramework`, `PyVariable`, `CloudFormationStack`, `TranslateList`, `ThemeProviderProps`, `Int16Array`, `DbMicroblock`, `IRegion`, `PmpApiConfigService`, `GroupState`, `NatF`, `RectangleSize`, `ReferenceIdentifier`, `MutableContext`, `SocketChannelServer`, `EncryptionType`, `JSONPropPath`, `OnDiskState`, `LookupFnResult`, `AzureTreeItem`, `ImportTypeNode`, `ODataQueryOptionHandler`, `TransistorEpisodeData`, `GithubUserResponse`, `CodeKeywordDefinition`, `RuleTester`, `IKeymap`, `GroupRegistryState`, `SessionProxy`, `AutorestLogger`, `FromTo`, `LangState`, `B`, `NetworkTraceData`, `RelationQueryBuilderContract`, `KeyboardEventInit`, `WorkBook`, `IsGroupIndentCellFn`, `SortBy`, `GenericClassProperty`, `DescribeRoutingControlCommandInput`, `ISoundSampleDescription`, `TextWithLinks`, `vscode.NotebookDocument`, `IServerParams`, `ImportRelativity`, `SWRHook`, `JobsService`, `FormikHelpers`, `Interview`, `ListHttpMonitorsRequest`, `Fuse`, `CreateForgotPasswordDto`, `ListNotebookSessionShapesRequest`, `EmailConfirmationHandler`, `ObserverLocator`, `AnimatedMultiplication`, `StackDeployOperation`, `windowPositionCalculationState`, `LevelUp`, `NumberLabel`, `IScheduleApiModel`, `DeviceConfig`, `_rest`, `ConfigTypes`, `CSSRuleList`, `CSSMotionProps`, `ConfigurationListItemType`, `DynamicModule`, `ElasticsearchError`, `InternalSettings`, `IDraft`, `DetailedCloudFormationStack`, `T1`, `FeatureCatalogueSolution`, `HandlerMetadata`, `ELO.RankState`, `ResolvedNode`, `RoxieResult`, `RequestHandler`, `GetRuleCommandInput`, `NetWorthItem`, `OpenSearchDashboardsReactOverlays`, `requests.ListInstanceConfigurationsRequest`, `XRangePoint`, `Frontmatter`, `PointerState`, `AnyFunction`, `PathItem`, `ConnectionStore`, `ScullyRoutesService`, `MultiSelectProps`, `VimCompleteItem`, `Blob`, `i18n.Node`, `CheerioOptions`, `SecurityGroupContextProviderPlugin`, `ReadValueIdOptions`, `IFormTemplate`, `HaredoChain`, `ISystemInfo`, `EventTopics`, `TransmartAndConstraint`, `ColorFactory`, `DeployOpID`, `requests.ListDbServersRequest`, `Organization`, `HashTable`, `UiActionsServiceEnhancements`, `PluginCodec`, `FlipCorner`, `Fs`, `TabbedAggColumn`, `ArcRotateCamera`, `NormalisedFrame`, `RSTPreviewConfiguration`, `ILogoProps`, `MockServiceClient`, `ResponseComposition`, `Quest`, `HlsManifest`, `LoadedExtension`, `ResourceInsightProjectedUtilizationItem`, `IWalkthroughStep`, `TimelineById`, `AdminAPI`, `GraphQLType`, `IRasterizedGlyph`, `PipeOptions`, `PedProp`, `ErrorPayload`, `SCN0_Light`, `TUser`, `CreateBackupResponse`, `GasComputation`, `ScrollEvent`, `AppStackMinorVersion`, `EDBEntity`, `SFValue`, `Rule`, `HalfEdgePositionDetail`, `StoredDocument`, `IpPort`, `CharacteristicValue`, `IndexGroups`, `XmlNodeNop`, `GraphError`, `BpmnContext`, `ITypeFilter`, `UpdateResults`, `ContextValueType`, `LoginUserDto`, `HttpRequestWithFloatLabelsCommandInput`, `ContractContext`, `MosaicNode`, `Rotation`, `ISuperBlock`, `RESTService`, `CarModel`, `GulpClient.Gulp`, `EventModelImplUnion`, `TimeRangeInformation`, `ReservedParameters`, `PlistValue`, `VitePluginFederationOptions`, `RegistryDataStream`, `SecretKey`, `StageInterviewRepository`, `FrontstageProps`, `CLM.TrainDialog`, `R2Publication`, `signalR.HubConnection`, `BaseThemedCssFunction`, `CloudFrontResponse`, `React.RefForwardingComponent`, `Internals`, `DataHandler`, `Models.User`, `requests.ListAvailableUpdatesForManagedInstanceRequest`, `TimePeriodField`, `SidePanelOpenDirection`, `ReadModelRuntimeEventHandler`, `NotebookSessionShapeSeries`, `DraftInlineStyle`, `ToggleConfig`, `PaginationInfo`, `RelationMeta`, `SessionTypes`, `IParserOptions`, `AVRInterruptConfig`, `PiCommand`, `ReactCrop.Crop`, `gcp.Account`, `Fx`, `TabItem`, `Evees`, `ActionListener`, `LoopNode`, `HomebridgeLgThinqPlatform`, `TEventRangeType`, `SharedGeometryStateStyle`, `ColumnOrder`, `ServiceURL`, `ArgumentListInfo`, `HostWatchEvent`, `SpacesClient`, `PrintableType`, `IntrospectionTypeRef`, `OperatorType`, `LineWithBound`, `CarouselState`, `StoppingCondition`, `AnimatorFlowValue`, `IReserve`, `WorkspaceInfo`, `HalfEdgeMask`, `core.Coin`, `CreateTableBuilder`, `PropertyEditorParams`, `GlobalStateT`, `TextRangeDiagnosticSink`, `ByteVectorType`, `InvocationArguments`, `protos.google.iam.v1.IGetIamPolicyRequest`, `SchemaObjectMetadata`, `SettingsProps`, `GenericStoreEnhancer`, `FlattenedType`, `RoleKibanaPrivilege`, `GetTestDestinationOptions`, `MessageParams`, `VarScope`, `GridValueFormatterParams`, `DepList`, `ListDataSourcesCommandInput`, `UseSidePanelProps`, `ng.IIntervalService`, `IInstrument`, `DefaultFocusState`, `LayoutSandbox`, `Tween24`, `PageMargins`, `CredDef`, `MessageDataType`, `TemplateOptions`, `ReadonlyJSONObject`, `SyncHook`, `DecoderError`, `OutputTargetWww`, `CausalRepoStore`, `SemanticClassificationFormat`, `StatsAsset`, `HTMLIonPopoverElement`, `VueQuery`, `RenderContext3D`, `ProgressProps`, `IControllerAttributeExtended`, `T8`, `ResolveOptions`, `ReadonlyMat`, `ECPoint`, `AnnotationSpec`, `EnumDef`, `ApiClient`, `UserPaypal`, `ts.IfStatement`, `BuildInstance`, `CloudFrontResponseEvent`, `Import`, `StateByProps`, `CallExpr`, `B12`, `ListChannelMembershipsForAppInstanceUserCommandInput`, `FeatureChild`, `NgbActiveModal`, `WatchEventType`, `SecurityClass`, `BlockClassSelector`, `TransformFnParams`, `VueAutoRoutingPlugin`, `TextData`, `StyleElement`, `IDynamicGrammar`, `SliceState`, `IndexImpl`, `CascaderContextType`, `PatternMappingExpandEntryNode`, `AssembledSubjectGraphics`, `IDictionary`, `AuthorizationCode`, `NotifierPluginFactory`, `SignalingOfferMessageDataChannel`, `FieldsInModel`, `ViewStore`, `SubEntityLocationProps`, `unchanged.Path`, `PerformDeleteArgs`, `IDispatchProps`, `TypePredicate`, `ProseNode`, `Conference`, `FullAgentPolicy`, `CucumberRunner`, `apid.StreamId`, `PaginationResponseV2`, `CalendarEvent`, `HsLaymanLayerDescriptor`, `HierarchyPointNode`, `ts.BindingElement`, `TabState`, `PythonPlatform`, `LineDashes`, `SnackBarOptions`, `ConfigImagery`, `TodoRepository`, `PromiseOrValue`, `Shortcuts`, `Twitter.User`, `ModelSpecBuilder`, `CursorProps`, `PersonChange`, `Description`, `RoomUser`, `ParseNodeArray`, `TouchBar`, `FileLocation`, `ProblemRowData`, `ITagInputProps`, `AnyGuildChannel`, `NoopExtSupportingWeb`, `SubsetPackage`, `IPackageDescriptorMap`, `FilterSettings`, `handleParticipantEvent`, `AST.AST`, `GrpcAuthentication`, `ExportProps`, `FunctionalUseCaseContext`, `Master`, `BackendAPIService`, `requests.ListIntegrationInstancesRequest`, `GetAllRequestBuilder`, `IContainerRuntime`, `TransferBuilder`, `LatestClusterConfigType`, `ConditionalBlock`, `requests.ListAnalyticsInstancesRequest`, `Selection`, `ESSearchSourceDescriptor`, `AsyncThunkAction`, `glm.mat4`, `TPluginsStart`, `TokenLevelState`, `ChainInfo`, `WebKitGestureEvent`, `InAppBrowser`, `TestEmbeddable`, `IPatient`, `AggregatePriceService`, `ImportStateMap`, `IMdcSliderElement`, `DateEnv`, `EncryptionProtectorName`, `NumericScaleLike`, `Filterer`, `Farmbot`, `DIDResolutionResult`, `ValuePredicate`, `SFPPackage`, `Spring`, `CompletionState`, `RetryStatus`, `DisplayInfo`, `PrimitiveAtom`, `ProjectStep`, `HTMLFieldSetElement`, `DocumentContents`, `Yendor.Context`, `Base64Message`, `EventModel`, `ViewportRuler`, `TransmartTableState`, `RepositoryCommonSettingEditWriteModel`, `SCTP`, `ConstantAndVariableQueryStringCommandInput`, `SelectColony`, `WatchEffectOptions`, `CandyDate`, `CoreSystem`, `CBCentralManager`, `FilterMap`, `RadioGroupProps`, `ResolvedValue`, `AwrDbWaitEventBucketSummary`, `FlowCall`, `SiteEntry`, `TreeDataSource`, `UniswapV1Client`, `TestExtension`, `GetAttributeValuesCommandInput`, `LevelDocument`, `CounterMetric`, `ODataRequest`, `OpenSearchRawResponse`, `ListTableColumnsCommandInput`, `protos.google.protobuf.IEmpty`, `IKeyQueryOptions`, `KeyExchange`, `LitecoinPaymentsUtilsConfig`, `am4maps.MapPolygon`, `HoverProviderItem`, `ISliderProps`, `WebdriverIO.Element`, `Kysely`, `AccessExpression`, `CallbackFn`, `AuthenticateModel`, `PromiseFunction`, `API.services.IChromeFileService`, `IScriptSnapshot`, `BitField`, `SerializeNodeToHtmlOptions`, `UpdateProfile`, `ExcludedRule`, `EAggregationState`, `ValVersion`, `InputText`, `IAddress`, `ShotRequestOptions`, `fromTimelineActions.GetTimeline`, `VolumeIndicatorCallback`, `WebStorage`, `Rx.Subscriber`, `Gallery`, `SatObject`, `CredentialProvider`, `IStage`, `ConditionResolution`, `VdmServiceMetadata`, `Point3D`, `CanvasGradient`, `EditSettingsCommand`, `T13`, `ControlContainer`, `DeleteDirectoryCommandInput`, `EuiComboBoxOptionOption`, `TreeContext`, `CreateBidDTO`, `Payload`, `EAVNField`, `EthAsset`, `StudentEntity`, `externref`, `AppViewRoute`, `JSONDocument`, `ResponseBody`, `TomcatServer`, `ArDB`, `DeveloperClient`, `DAL.DEVICE_ID_ACCELEROMETER`, `PanRecognizer`, `OverlaySizeConfig`, `Dimensionless`, `IProxy`, `Quantity`, `pd.FindSelector`, `StorageLocationModel`, `RequestTemplateDef`, `Int32`, `SchemaObject`, `SnapshotRestoreRequest`, `GetStateParams`, `GetDeclarationParameters`, `vscode.TestItem`, `GRUCell`, `ChannelSettings`, `AuthMetadata`, `MergedBuildFileTask`, `CreateParams`, `OnNumberCommitFunc`, `InterviewPrizePlaylist`, `ResolvedVersion`, `RgbaTuple`, `pointInfoType`, `PrunerT`, `Avatar`, `React.CSSProperties`, `V1`, `PDFRawStream`, `UserDomain`, `RegionFieldsItem`, `EventEnvelope`, `VfsStat`, `SNS`, `ServiceException`, `SubShader`, `GfxTopology`, `MqttMessage`, `UIAlert`, `ClassMemberLookupFlags`, `TypeConstraint`, `DisplayObjectWithCullingArray`, `HTMLBaseElement`, `InternalOpAsyncExecutor`, `ChartDataItem`, `ITextAreaProps`, `StoredAppChallenge`, `UpdateRuleGroupCommandInput`, `Req`, `IDateRangePickerState`, `UserOrganizationService`, `SourceASTBuilder`, `BaseConvLayerArgs`, `IPAddressEntry`, `UseBoundStore`, `Element_t`, `HostPort`, `StatusMessageService`, `TestModelVersion`, `EnumRow`, `EnhancedModuleGraph`, `PaddingMode`, `ITracerProfile`, `CoercibleProperty`, `IBindingWizardContext`, `RequestArguments`, `UpdateCampaignCommandInput`, `ProposalIdentifier`, `RequestQueryOptions`, `AveragePooling1D`, `DescribeContactCommandInput`, `ArrayMap`, `CreateBucketCommandInput`, `SignalingClientConnectionRequest`, `ImplicitImport`, `Measurements`, `NodeBuilderFlags`, `NodeLinks`, `TextDocumentEdit`, `PLIItem`, `OnboardingLightData`, `ISourceMapPathOverrides`, `ApexLibraryTestRunExecutor`, `ProcessedCDPMessage`, `TokenFields`, `SnippetOptions`, `VApiTy`, `FindTilesAdditionalParameters`, `TableListItem`, `ListViewEventData`, `DeployOptions`, `NgModuleData`, `IContainerRuntimeBase`, `TableOfContentsItem`, `EditorService`, `UserSettingsState`, `ListStorageObjectsRequest`, `ICollection`, `CGAffineTransform`, `GovernanceAccountType`, `EventParameter`, `SocketInfo`, `V1Certificate`, `IPost`, `OsdFieldType`, `SearchDevicesCommandInput`, `FunctionDefinition`, `AuthorizationData`, `TokenMarker`, `TunnelRequest`, `Skola24Child`, `MockAirtableInterface`, `CriteriaGroupType`, `SearchTimeoutError`, `StackMode`, `DemoItem`, `OverlayKeyboardDispatcher`, `AttributeWeights`, `Collator`, `QueryExpressionParensContext`, `TypedFragment`, `IValueConverter`, `RequestDetails`, `RecordSourceSelectorProxy`, `UpSetJSSkeletonProps`, `AggsAction`, `MpElement`, `VueAuthOptions`, `UpdateWorkspaceCommandInput`, `CompareType`, `TileKey`, `ResponseOptions`, `SelectionType`, `Level1`, `WindowLocation`, `SurveyElementEditorTabModel`, `DataModels.UserTasks.UserTaskResult`, `ValidationProblem`, `Bills`, `AbstractSqlConnection`, `IExtensionElement`, `IssuePriority`, `SliderProps`, `ColorKind`, `HdRipplePaymentsConfig`, `Clauses`, `CoronaData`, `SubmitTexture`, `RangeData`, `FieldMappingSpec`, `SecurityManager`, `SpacesPlugin`, `RelativeRect`, `TChunk`, `DecodedResult`, `SelectorsSource`, `IChatItemsState`, `AudioState`, `AuthTokenEntity`, `HttpResponseException`, `PluginDeployerResolverContext`, `MemberNames`, `Mob`, `PasswordHistoryResponse`, `SSOAdmin`, `d.ScreenshotDiff`, `Vc2cOptions`, `BundleDataService`, `requests.ListDedicatedVmHostInstanceShapesRequest`, `CustomHtmlDivFormatter`, `FolderId`, `ChartHighlightedElements`, `AzureClusterProvider`, `PopulateOptions`, `DevOpsAccount`, `SystemLayout`, `WordStyle`, `JSONSchema6`, `Icons`, `t_b1f05ae8`, `BITBOXCli`, `ChannelMessageList`, `Scheduler`, `ContentRecord`, `POIDisputeAttributes`, `NavigationIndicatorCriteria`, `PROVIDER`, `PluginContext`, `ReflectedValue`, `Shrewd.IDecoratorOptions`, `ModifierKeys`, `MyDefaultThunkResult`, `FetchAPI`, `IteratorOptions`, `QueryRenderData`, `EventInit`, `TSClientOptions`, `CallbackType`, `MerchantGoodsSkuEntity`, `CheckOriginConflictsParams`, `StoryListener`, `allContracts`, `AssembledReportGraphics`, `TESubscr`, `SurveyCreator`, `PgClient`, `SqlToolsServiceClient`, `EntityOperators`, `objType`, `GdalCommand`, `r`, `DataEvent`, `ShapeData`, `moment.Moment`, `ResultMeta`, `SampleExtractionResult`, `BluetoothRemoteGATTService`, `VideoQualitySettings`, `PNGWithMetadata`, `PrintableArea`, `ParameterMap`, `ExtendedKeyboardEvent`, `ExpressContext`, `ValidCredential`, `AppMetadata`, `TestFunctionImportSharedEntityReturnTypeCollectionParameters`, `DeprecatedHeaderThemes`, `Indices`, `ChainIdLike`, `JTDSchemaType`, `Rules`, `enet.IConnectOptions`, `HdLitecoinPayments`, `MessageSpecification`, `configuration.Data`, `TileDisplacementMap`, `ResilienceOptions`, `RemoteUpdateListener`, `RouteDryMatch`, `ScheduledDomain`, `ResourceSystem`, `SpectatorService`, `NodeDisplayData`, `IKeyIterator`, `PreferredContext`, `TypeGenerator`, `DataViewRow`, `AnyPersistedResource`, `BrickRenderOptionsResolved`, `WebSocketLike`, `DistinctValuesRequestOptions`, `StructProp`, `ActionGameState`, `PlaceholderProps`, `lgQuery`, `PrivateStyle`, `SoftwareModel`, `LegacyObjectToConfigAdapter`, `LinkOptions`, `SchemaContext`, `IncompleteTreeNode`, `GX.TevOp`, `DiffPanel`, `StringType`, `FailedJob`, `DescribeModelCommandInput`, `LookUpResult`, `Zerg`, `Secp256k1`, `ServerKeyExchange`, `AnyNode`, `PowerlevelCCSet`, `VisualizeAppState`, `UnitRecord`, `IConsul`, `TSupportedFaction`, `WebRequest`, `ByteMatrix`, `ConnectionBackend`, `Viewer.ViewerRenderInput`, `grpc.CallOptions`, `UnwrapRowsComputed`, `RecursiveAnnotation`, `d.PrerenderManager`, `THREE.Event`, `Instantiable`, `MessageHandler`, `ModuleImport`, `Rule.Node`, `Vendor`, `ComponentDescriptor`, `IERC20`, `MarkdownRenderer`, `TreeDataProvider`, `CodeRepository`, `DialogRef`, `IGherkinStreamOptions`, `EntityMetadataMap`, `NetlifyConfig`, `PostgrestResponse`, `InterfaceServerResponse`, `WechatMaterialEntity`, `ICharacterData`, `WebviewWidget`, `React.EffectCallback`, `fhir.Bundle`, `IChart`, `PanGesture`, `IReadOnlyFunctionCallArgumentCollection`, `PromiseCollection`, `TokenCredentialsBase`, `PluginState`, `OpenSearchDashboardsConfig`, `TestWalker`, `SvgProps`, `ThermocyclerModuleState`, `ODataBatchRequestBuilder`, `FullLocaleData`, `PipelinesGraphics`, `DangerDSLJSONType`, `ItemResponse`, `UpdateConfigurationDetails`, `IISystemProto`, `TileDataSourceOptions`, `PipelinesService`, `GetBalanceActivityOptions`, `GuidGenerator`, `PuzzleAction`, `RetryConfiguration`, `CalderaElement`, `Vulnerability`, `X12Transaction`, `FileSystemConfig`, `Ray3d`, `TextureDescriptor`, `WorkerRequestEntry`, `GetUserResponse`, `net.Endpoint`, `eris.Client`, `IZoweDatasetTreeNode`, `TextTransformType`, `ConditionExpression`, `ListChannelsRequest`, `TableQuery`, `IdentifierAttribute`, `StringDictionary`, `MusicbrainzArtist`, `CreateGroupCommandInput`, `WildcardIndex`, `WorkspaceFileWatcher`, `InvalidOperationException`, `CalendarApi`, `TaskInProgress`, `CreateRuleGroupCommandInput`, `ScanRunResultResponse`, `NoteData`, `InsertPosition`, `WrongDependencies`, `ConfigurationChangeEvent`, `PeerSet`, `GCPubSubServer`, `MissionElement`, `TypeParser`, `ISpan`, `LogSeriesFragmentPushRequest`, `PartyDataSend`, `ConnectionManagerState`, `MP4Box`, `ByteVector`, `TextStringLiteralContext`, `STFilterComponent`, `NextConnect`, `OrganizationUserBulkRequest`, `TiledObjectGroup`, `ThyTreeNodeCheckState`, `requests.ListAgreementsRequest`, `AreaGeometry`, `ITelemetryBaseLogger`, `IAuthStatus`, `GroupModel`, `NumberConfig`, `ObjectTypeComposer`, `Argon.SessionPort`, `ImageUpdate`, `TranslationPartialState`, `AnyIterableIterator`, `ng.IDirective`, `ICommandBus`, `DockerContainer`, `UnionTypeDefinitionNode`, `GestureState`, `CdkTree`, `DirtyDiff`, `PriceAxisViewRendererOptions`, `DiffState`, `rootState`, `ARAddModelOptions`, `ClientAndExploreCached`, `HasJSDoc`, `FileVersionSpec`, `AggTypeFilter`, `SourceGroup`, `LogoState`, `RestGitService`, `FieldSpec`, `Atom`, `AllowAction`, `HAP`, `DecoratorOption`, `Ch`, `OrderRepository`, `LastfmArtistShort`, `DeleteInputCommandInput`, `YAnnotation`, `ModifyReadResponseFnMap`, `PLSQLCursorInfos`, `FloatKeyframe`, `FieldDefinition`, `AppendBlobClient`, `CreateDatasetResponse`, `StoreService`, `EntityBuilderType`, `SplitInfo`, `VectorLayerDescriptor`, `DescribeServiceUpdatesCommandInput`, `IMiddlewareClass`, `XNumber`, `requests.ListVaultReplicasRequest`, `Chromosome`, `ListBuffer`, `EliminationBracket`, `ToolTipProps`, `StacksMainnet`, `SharedKey`, `FirebaseProject`, `ApplicationStub`, `ListExecutionsCommandInput`, `GovernElement`, `Http3FrameType`, `SubmissionSectionError`, `FontVariant`, `UserSessionService`, `MagitRepository`, `PreparationTool`, `DisplayValueMapService`, `DefaultVideoTransformDeviceObserver`, `EntityMetadata`, `Crdp.Runtime.ConsoleAPICalledEvent`, `SelEnv`, `NoteCacheItem`, `ISerializer`, `IAmazonServerGroupView`, `protocol.Request`, `PickleStep`, `SelectorArray`, `Containers`, `ITokenObject`, `ValueFormatter`, `AlertsByName`, `FilePickerProps`, `SpineBone`, `S3Configuration`, `ModuleRef`, `ReportingNotifierStreamHandler`, `OutlineSurveys`, `IAreaData`, `RawSavedDashboardPanel610`, `CreateCampaignCommandInput`, `AssetVersion`, `ArenaFormatings`, `WebMessageRawPayload`, `StateBase`, `BitExprContext`, `WorkerService`, `PerspectiveTransform`, `IntervalHistogram`, `SpaceBonus.TITANIUM`, `BindingPattern`, `native.Array`, `ListExportsCommandInput`, `IUtxo`, `IHashMapGeneric`, `WriteBufferToItemsOptions`, `MoveSeq`, `PostgreSQL`, `DaffPaypalTokenResponseFactory`, `ReduxActions.Action`, `ParseResult`, `VisType`, `IGBCoreService`, `DeleteStageCommandInput`, `TSError`, `TimeTrackerService`, `BlockchainCode`, `SVGTemplateResult`, `SDKVersion`, `IConsole`, `WorkflowMapper`, `UpdateRecorder`, `FormGroupDirective`, `NewPackagePolicyInputStream`, `DeviceTracker`, `FuseResult`, `ViewOptions`, `SkillGaussian`, `ClientBase`, `ILoaderIncludePipe`, `colorModule.Color`, `TestUser`, `EllipsoidPatch`, `CourseComponent`, `StoreApi`, `TileCacheId`, `LineString3d`, `TFileOrSketchPartChange`, `ResourcesModel`, `ProgramAccount`, `RenderCompleteListener`, `EditRepositoryCommand`, `DisassociateServiceRoleFromAccountCommandInput`, `THREE.SkinnedMesh`, `DailyRate`, `NAVObject`, `PackageManagers`, `Tx.Info`, `GraphReceipt`, `ContainerState`, `CoreIndexFile`, `ComponentResolverService`, `MemberDefinition`, `InstanceTarget`, `HitDatabaseMap`, `AudioService`, `PropertyChangedEvent`, `BitSource`, `HeapObject`, `ToolGroup`, `ConfigValue`, `Generation`, `TestBackendTimer`, `UniqueIdGenerator`, `CameraConfig`, `ThyNotifyService`, `InvalidParameterValueException`, `AllureRuntime`, `MapLayer`, `EventHandlers`, `Extended`, `VisTypeListEntry`, `TInjectableOptions`, `OpenDialogOptions`, `MDCFloatingLabelAdapter`, `ImageBitmap`, `LocationCalculatorForHtml`, `FrontCardAppearanceShort`, `IntersectionState`, `FileSystemHost`, `PragmaDirectiveContext`, `requests.GetDomainRecordsRequest`, `IHistoryItem`, `OnRefreshProps`, `ConversationService`, `VersionMismatchFinder`, `StyleSheet`, `Path5`, `CanvasPattern`, `EncodeApiReturnOutput`, `GPGPUProgram`, `StatisticsSetType`, `IFluidDependencySynthesizer`, `TalkSession`, `PutAccountSendingAttributesCommandInput`, `GfxPlatformWebGL2Config`, `V1Deployment`, `IBreakpoint`, `LimitedTypedData`, `ReactPortal`, `ListState`, `PackageFailures`, `ITagMatchInfo`, `JsonaAnnotation`, `BlobClient`, `AdapterConstructor`, `NVMDescriptor`, `FrescoDrawee`, `GraphQLNamedType`, `PlayerInfo`, `NodeKeyType`, `ComponentPath`, `SchemaService`, `DateBodyRow`, `GetBucketTaggingCommandInput`, `RivenProperty`, `ParsedLineType`, `AuthResponse`, `FirebaseObjectObservable`, `AnimationNodeContent`, `RobotCard`, `NVM3Objects`, `... 23 more ...`, `ServiceBuilder`, `RuleAction`, `ReaderOptions`, `IColumn`, `MockedFunction`, `StampinoRender`, `QueryOption`, `NodeSourceOption`, `Swap`, `AuthenticateResultModel`, `IProjectConf`, `PolygonGeometry`, `PickItem`, `HostElement`, `ModuleDeclaration`, `SeriesDomainsAndData`, `DispatcherPayloadMetaImpl`, `UsedHashOnion`, `CoinbasePro`, `HookOptions`, `TimePickerModel`, `TheDestinedLambdaStack`, `IReactionPublic`, `CompileOptions`, `SimpleAllocationOutcome`, `IConcatFile`, `SearchIndex`, `TypeConverter`, `SymbolScope`, `SmsProvider`, `PoolTaskDataService`, `FieldHook`, `DataSource`, `FetchedIndexPattern`, `IntPretty`, `IntegratedSpiral3d`, `AsyncFnReturn`, `ValidatorModel`, `Molecule`, `BundleOptions`, `AlyvixApiService`, `AutocompleteFieldState`, `StackOperationStep`, `StellarBalanceMonitor`, `bool`, `dom5.Node`, `FilterLabelProps`, `CameraCullInfo`, `requests.ListVirtualCircuitBandwidthShapesRequest`, `SqrlParseErrorOptions`, `matter.GrayMatterFile`, `StyleExpression`, `IFileUnit`, `HeroById`, `core.JSCodeshift`, `BrewView`, `TType`, `MessageArg`, `Masking`, `UpdateProjectResponse`, `SuperTest`, `NonFungibleAssetProvider`, `IReactionDisposer`, `IMinemeldPrototypeService`, `ExecutionContainer`, `WorldComponent`, `RenderTreeFrameReader`, `Spacing`, `CFMLEngine`, `TranspileOutput`, `LayerConfigJson`, `CreateAndTransferTransition`, `ResourceNode`, `PvsVersionDescriptor`, `HubServer`, `RootContainer`, `Structures`, `FilterService`, `TagSpecification`, `ForkOptions`, `MsgToWorker`, `NodeSorter`, `TestRunnerAdapter`, `MinifyOutput`, `CharacteristicGetCallback`, `CustomPropertyGetUsage`, `ValueStream`, `ReadAndParseBlob`, `FunctionConfiguration`, `requests.ListTransferJobsRequest`, `IAllAppDefinitions`, `ResolverMap`, `TensorTracker`, `FirebaseUserModel`, `AccountSettings`, `FetchPolicy`, `InvalidStateException`, `GroupingService`, `DebugProtocol.StepInResponse`, `PoolFactory`, `Ctor`, `Nibbles`, `ExportContext`, `SystemIconStyles`, `FirestoreError`, `AppDeepLink`, `ContractNode`, `LedgerRequest`, `SubqueryRepo`, `BasisCompressionTypeEnum`, `URLBuilder`, `MdcRadio`, `CommsRecord`, `IPCMessages.TMessage`, `ListCardConfig`, `React.ComponentClass`, `ColumnObjectType`, `SerializedSavedQueryAttributes`, `IUserNote`, `BinaryBuffer`, `TemplateDocument`, `DatasetTree`, `IDocumentContext`, `MVideoFile`, `Magic`, `StencilOp`, `StatsModule`, `NbDialogService`, `Notations`, `DataView`, `GQtyClient`, `ElementState`, `LayoutMaterial`, `NzI18nInterface`, `CreateArg`, `FacetsGroup`, `ErrorCodes`, `SearchSourceDependencies`, `SetupDependencies`, `AccountingTemplate`, `Counter`, `TypeIR`, `LoginUri`, `ReadModelInterface`, `ItemStorageType`, `TEChild`, `TableBatchOperation`, `CompiledRuleDefinition`, `BanesAndBoonsInfo`, `SpyInstance`, `GitJSONDSL`, `QueryTimestampsCommandInput`, `API.storage.api.ChangeDict`, `FileAccessor`, `FolderComponent`, `DependencyMapEntry`, `RunResult`, `ApiResourceReference`, `SupportCodeExecutor`, `JsonRpcClient`, `IFormSectionGroup`, `DeviceLog`, `EzModel`, `SimulatorDevice`, `GoEngineConfig`, `ManagementSection`, `Hello`, `ISPHttpClientOptions`, `http.IncomingMessage`, `IXYOperator`, `DataPublicPluginStart`, `AuthHandler`, `InteractionProps`, `AssertNode`, `MessageResponse`, `LicenseInfo`, `RX.Types.ReactNode`, `LogDomain`, `OwnerService`, `IEntityKeyType`, `GlobalAveragePooling2D`, `QueryShortChannelIdsMessage`, `SampleProduct`, `Ripemd160PolyfillDigest`, `ISqlEditorTabState`, `PreloadedQuery`, `SummaryCollection`, `ApiValue`, `DescribeScalingActivitiesCommandInput`, `ReadonlyObjectDeep`, `UserProvided`, `TestSuiteNode`, `ButtonData`, `CompareFn`, `TypistOptions`, `DiscordBridgeConfigAuth`, `ModalInitialState`, `TSAssign`, `DynamodbMetricChange`, `Mask`, `IConnectionOptions`, `CreateClusterCommandInput`, `SearchBarProps`, `express.Request`, `IInstanceDefinition`, `TableHeader`, `RenderHookResult`, `TensorList`, `AppThunk`, `CreateApplicationCommandOutput`, `Cls`, `CallClientState`, `MenuModelRegistry`, `EventArguments`, `MutableQuaternion`, `DebugProtocol.ScopesResponse`, `PeerId`, `GeneratedFont`, `Download`, `AddressVersion`, `JSMs.XPCOMUtils`, `PropertyInfo`, `VNodeQueue`, `Survey.SurveyModel`, `IterableDiffers`, `LernaPackage`, `BumpType`, `InjectFlags`, `StaticConfigParsed`, `ListActionsCommandInput`, `ICompilerResult`, `RouteType`, `MiTextConfig`, `OutputLink`, `ShareParams`, `BuilderReturnValue`, `ExtensionReference`, `IIterationSummary`, `DecoratorOptions`, `ValueSuggestionsGetFn`, `ValidationMessage`, `RulesClient`, `NestedValueArray`, `Immutable`, `TapeNode`, `TestState`, `LegacySprite`, `PersistenceHelpers`, `GPUBindGroup`, `TextureLoader`, `FilterOption`, `ValueXY`, `DatabaseFactory`, `CrudService`, `EntityComparisonField`, `IngredientReducerState`, `ContextOptions`, `SlideData`, `CheckboxGroupState`, `FetchGroup`, `SortedMapStructure`, `DyfiService`, `StatePropsOfControl`, `ImmutableSet`, `BinaryOperationNode`, `InsightOptions`, `CursorState`, `HashCode`, `CalendarOptions`, `EightChar`, `QueryProviderRequest`, `BuildFile`, `ErrorController`, `FaunaData`, `Pier`, `CloudFrontRequest`, `sinon.SinonFakeTimers`, `EffectReference`, `PatchListener`, `SettingsStore`, `LoginUriData`, `TokenRequest`, `GetTemplateCommandInput`, `SRoutableElement`, `GlobalVariables`, `PlayerModel`, `ICreateOrgNotificationOptions`, `DeleteDataSetCommandInput`, `Supplier`, `RecordRawData`, `GameEngine`, `Filesystem.FileExistsSync`, `ActJestMoveTimeTo`, `CustomReporterResult`, `ISubscribe`, `LineModel`, `ActionheroLogLevel`, `NoneAction`, `BoxFunction`, `StateChangeListener`, `OclExecutionContext`, `TemplatePortal`, `SizeType`, `ThyUploadFile`, `TParam`, `FunctionN`, `AnalysisMode`, `CouncilProposal`, `SendRequest`, `PostSummary`, `AnimationKeyframeLinear`, `RedisOptions`, `SolanaKeys`, `PathToRegExpOptions`, `EndpointDetails`, `sentry.SentryEvent`, `SliceRequest`, `requests.GetConnectionRequest`, `QueryResult`, `TemplateAst`, `DynamicFormArrayModel`, `RobotApiRequestMeta`, `TransactionStatus`, `TypePredicateNode`, `AndOptions`, `T16`, `NavigationParams`, `PersistStorage`, `IssueProps`, `ResponsiveSpace`, `IChild`, `AStore`, `Reconciler`, `OpticType`, `Intl.NumberFormatOptions`, `Prefab`, `NodeCheckFunc`, `ParamDefinition`, `GeoBounds`, `CosmosdbSqlDatabase`, `Fig.Arg`, `MetadataType`, `SidebarService`, `IAdvancedBoxPlotData`, `Jb2Adapter`, `WebGLMemoryInfo`, `TocLink`, `PSIBoolean`, `IRecord`, `EmitHost`, `BackendErrorLabel`, `IMovie`, `InterfaceEvent`, `UnitAnalyser`, `ChannelId`, `PacketMember`, `NormalizedConfig`, `Directions`, `MnemonicSecret`, `AudioVideoObserver`, `requests.ListAutonomousExadataInfrastructureShapesRequest`, `ContentTypeSchema`, `ScopeOptions`, `AppRouteRecordRaw`, `EChartGraphNode`, `Fixture`, `ILaunchOptions`, `Window.ShellWindow`, `ForStatement`, `CmafEncryption`, `httpProxy`, `ConvaiCheckerComponent`, `IStaticFile`, `ReplicaSet`, `BSplineWrapMode`, `CreateBotCommandInput`, `GetEnvironmentTemplateVersionCommandInput`, `ChatUser`, `PublicParams.Swap`, `ServerConfigResource`, `OperationModel`, `TransformedStringTypeTargets`, `Phaser.Game`, `TinyHooks`, `LogStream`, `NormalizedParams`, `UseTransactionQueryState`, `TokenScanner`, `UniqueKey`, `LanguageIdentifier`, `CategoryLookupTables`, `QueryOrderRequest`, `TextMetrics`, `AESJsonWebKey`, `GfxBlendFactor`, `TestFabricRegistryEntry`, `PresenceHandler`, `BodyElement`, `InvokeMethod`, `SteamTree`, `... 7 more ...`, `Attitude`, `TextMatchPattern`, `CombatAttack`, `SectionList`, `IRootElasticQuery`, `IExplorer`, `LinuxJavaContainerSettings`, `PQLS.Library.TLibraryDefinition`, `WorkspaceOptions`, `RoosterCommandBar`, `UpdateDataSetCommandInput`, `TypeNameContext`, `DescribeExportCommandInput`, `ParsedQueryWithVariables`, `MongoClient`, `NgrxJsonApiStoreResources`, `ContextProps`, `UrlFilter`, `TypeArgumentResult`, `ShapeTreeNode`, `MessengerTypes.BatchItem`, `SpansRepository`, `CheckMode`, `GetRecommendationsCommandInput`, `FetchInit`, `DeployStatus`, `CommandEntry`, `ReadableBYOBStreamOptions`, `ts.TextRange`, `TutorialRuleStatus`, `ProviderStore`, `ExplicitFoldingConfig`, `RequireId`, `Average`, `IDescribeRunner`, `Pt2`, `SymBool`, `UniformState`, `ScriptProcessorNode`, `RgbaColor`, `SlpTokenGraph`, `FluentLogger`, `Providers`, `ValidationFunc`, `ExtrinsicDetails`, `WalletState`, `EclipticCoordinates`, `Emotion`, `BuildArtifact`, `IShareButton`, `UserDataCombined`, `MinimalTransaction`, `BaseLanguageClient`, `DayElement`, `SubscribeMessage`, `MyCombatLogParser`, `PropertyCollection`, `ClassConstructor`, `UpdateFindingsCommandInput`, `DimensionMapping`, `DaffAuthLoginReducerState`, `TextInputType`, `ChromeHelpExtension`, `ChartTooltipItem`, `LaunchTemplate`, `ExternalMaster`, `MutableRefObject`, `ShapePair`, `Row`, `LoginParams`, `IAggregationStrategy`, `ITableDefine`, `CertificateAuthorityTreeItem`, `DomExplorerNode`, `NativeInsertUpdateOptions`, `ObservableLightBox`, `EncryptionConfig`, `v2.WebDAVServer`, `PosAndDir`, `MeasurementKind`, `Autopanner`, `PositionAnimation`, `MnemonicX86`, `StateObject`, `Datasource`, `ListPortfoliosForProductCommandInput`, `THREE.Box3`, `IQueryBuilder`, `QualifiedIdentifierContext`, `CloudWatchMetricChange`, `LabelType`, `DescribeOrganizationCommandInput`, `UserPoolService`, `TravisCi`, `WesterosGameState`, `SubjectDetails`, `IntelRealtimeResponse`, `SidebarButtonProps`, `PropertyDecorator`, `IWebAppWizardContext`, `AST`, `IndyPool`, `CreateRouteCommandInput`, `OperatorFinishEncodeInfo`, `S3Destination`, `LayoutActor`, `restm.RestClient`, `DirectiveProfile`, `OidcState`, `CheckResultBuilder`, `NamedTypeNode`, `SQLite3Types`, `TestThrottler`, `AirSchema`, `DataType`, `ApiErrorParams`, `PDFImage`, `BsModalService`, `FormikProps`, `FnParam`, `NonEmptyList`, `NotifyFunc`, `IDeploymentCenterContext`, `InputBox`, `CB`, `mm.IFormat`, `ISearchOptions`, `ExchangeInstance`, `IGridAddress`, `AstroConfig`, `FlowsenseUpdateTracker`, `ComponentCompilerProperty`, `IProps`, `ModelStore`, `WebGL2DisjointQueryTimerExtension`, `BlobGetPropertiesResponse`, `ElementStyles`, `BreadcrumbOptions`, `VocabularyModel`, `PPTDataType`, `CampaignTimelineBoardViewerChanelsModel`, `RectilinearEdgeRouter`, `RxnPlus`, `Bag`, `Topics`, `Slides`, `AssetsOptions`, `AwsCredentials`, `ISmsProvider`, `Thing`, `Characteristic`, `cormo.Connection`, `DeployBuilderOptions`, `PointsGeometry`, `BLOCK`, `HTMLInputElement`, `ThemeVersion`, `InterpolationCurve3dOptions`, `ChatTab`, `dagre.graphlib.Graph`, `IPreset`, `TAtrulePrelude`, `Highcharts.VennRelationObject`, `SandboxContext`, `ParticipantListItemStyles`, `ICols`, `TypeDescription`, `ResponseErrorAttributes`, `PlaylistEntry`, `DeleteSubnetGroupCommandInput`, `requests.ListAutonomousDbPreviewVersionsRequest`, `XChaCha20Poly1305`, `TodoService`, `mongoose.FilterQuery`, `Events.visible`, `EthereumListener`, `ScopedClusterClient`, `CacheManagerGetOptions`, `DeleteApp`, `FoodModel`, `SingleLayerStringMap`, `FlagInfo`, `DaffSeoNameMetaDefinition`, `DaffCartAddressFactory`, `Elem`, `IModelHostConfiguration`, `SymFloat`, `CommandInteraction`, `IFormikStageConfigInjectedProps`, `IExtendedCommit`, `Normalized`, `NgEnvironment`, `StorageKeys`, `GLsizei`, `ThumbnailProps`, `RootNode`, `Console`, `EqualityFunc`, `Ratio`, `NineZoneStagePanelPaneManagerProps`, `UrlMatchResult`, `ElasticsearchClientConfig`, `EVENT_TYPE`, `MessagingServiceInterface`, `FilterConfig`, `Enzyme.ReactWrapper`, `ToastService`, `IAstItem`, `TypeNode`, `Etcd3`, `SavedObjectsTypeMappingDefinitions`, `RType`, `VisualizeAppStateContainer`, `FactorGradient`, `CoreStart`, `requests.ListMultipartUploadPartsRequest`, `ILinkedNodeWithValue`, `SemanticMeaning`, `EventSubscriptionQuotaExceededFault`, `PreviousSpeakersState`, `TableRowData`, `ChangeStateMap`, `BrandState`, `KDF`, `PerspectiveDetails`, `Http3HeaderFrame`, `IDiscordMessageParserResult`, `HasTagName`, `RequestSpec`, `OrganizationProjectsService`, `AccountEmail`, `ATNConfig`, `Pubnub`, `ILocalConfig`, `TimeOffPolicy`, `IRouterliciousDriverPolicies`, `IExecSyncResult`, `ApplyPath`, `PeerInfo`, `JSDocTypeTag`, `events.Handler`, `FieldFormatsStart`, `ConnectionArgs`, `ChunkIndex`, `LogAnalyticsParameter`, `TableDimension`, `ResolvedEphemeralListType`, `ResolvedCSSBlocksEmberOptions`, `Players`, `NumericValuesResult`, `SlotDoc`, `EventStatus`, `ATTRIBUTE`, `TestFormat`, `ApiRun`, `StackingState`, `DrivelistDrive`, `PinMap`, `NzMessageDataOptions`, `Runnable`, `ListUsersRequest`, `SettingsConfig`, `PreprocIncInfo`, `ViewResources`, `InstanceRejectOnNotFound`, `ILanguageObject`, `React.RefObject`, `SingleYAMLDocument`, `SynthIdentifier`, `LanguageClientOptions`, `AssetType`, `RuleConfigTuple`, `ServiceClient`, `ReactEventHandlers`, `IterableChangeRecord_`, `RTCRtpSender`, `Datatypes`, `SiteConfig`, `TimeWidget`, `IProductOptionGroupTranslatable`, `MockConnection`, `HeadersFunction`, `RegisterConfig`, `ExpectedCompletionEntryObject`, `DerivedGauge`, `CommandClasses`, `IWatchOptions`, `PoiBatch`, `NodeProperties`, `SettingOptions`, `ImGui.DrawVert`, `AbstractProvider`, `Balances`, `DetailsState`, `Door`, `SurveyLogicAction`, `SystemStyleObject`, `InterpolationCurve3d`, `PageButtonProps`, `MessageId`, `ArrayEntry`, `IMagickImage`, `JsonStringifierTransformerContext`, `MessageEnvelope`, `TaskFile`, `ActionsObservable`, `LayoutConfig`, `TypeExpression`, `HMACParams`, `RetryKeycloakAdmin`, `AddApplicationInputCommandInput`, `QueryBidRequest`, `AddressHashMode`, `Mentor`, `ListRunsRequest`, `ReadFileResult`, `ChangePasswordRequest`, `CloudFront`, `i8`, `ProjectionResult`, `ClientModel`, `CreateResult`, `SettingLanguage`, `SortedMap`, `ISelectionData`, `BspSet`, `MetricsConfiguration`, `WebGLRenderTarget`, `StageStore`, `X12QueryResult`, `DijkstraNode`, `TaskData`, `IRealtimeSelect`, `MaterialConfig`, `RebaseEditorContext`, `Pool2DProgram`, `PickFunction`, `JsonDocsPart`, `BaseEdge`, `AllStyleOption`, `ApplicationParameter`, `CfnCondition`, `CaretCoordinates`, `RecycleAccumulator`, `APIVersion`, `GX.IndTexAlphaSel`, `Combine`, `WorkNode`, `Howl`, `FileAnalysisResult`, `HttpManagementPayload`, `IRef`, `IPluginTimes`, `INohmPrefixes`, `PointerInfoPre`, `UserOperation`, `WebAudioInstance`, `MetaDefinition`, `LmdbEnv`, `Weather`, `OperationInfo`, `PlayingCard`, `Group1524199022084`, `TimeGridWrapper`, `CombinedJob`, `MemoryManager`, `SessionEntity`, `NetworkSourcesVirtualSourceList`, `LinkInfo`, `ReadonlySymbolSet`, `TimerEvent`, `BRepGeometryInfo`, `ICommonTagsResult`, `SfdxFalconResultType`, `InterfaceWithExtends`, `TodoFilter`, `esbuild.OnResolveArgs`, `PropertiesService`, `StoreMetaInfo`, `TransformStreamDefaultController`, `CompilerOutput`, `ReadableStreamDefaultReader`, `DidDocumentService`, `UnhashedOrder`, `TransactionVersion`, `Tarefa`, `PadplusRoomInvitationPayload`, `React.SetStateAction`, `Flow`, `IBook`, `TaskDefinitionRegistry`, `IModelReference`, `SemanticNode`, `IResourceRow`, `SpacerProps`, `WorkRoot`, `QueryClient`, `PropsHandler`, `PreProcessor`, `vscode.Disposable`, `SideBarTabModel`, `IncomingHttpHeaders`, `HierarchyCompareInfoJSON`, `StoredEventBatchPointer`, `LoadedVertexDraw`, `messages.DataTable`, `LinariaClassName`, `AnimationController`, `GeoJsonObject`, `unreal.Message`, `ElasticsearchResponse`, `GLTFLoaderExtension`, `Scale`, `Rx.TestScheduler`, `RetryDataReplicationCommandInput`, `MockMessageRequester`, `MaterialAnimationTrack`, `requests.ListAppCatalogListingResourceVersionsRequest`, `Datum`, `RxFormArray`, `ITemplatedBundle`, `FragmentManager`, `tf.NamedTensorMap`, `INativeMetadataCollector`, `ActionTypeBase`, `DAL.DEVICE_HEAP_ERROR`, `Datafeed`, `SearchService`, `StepResult`, `AccountJSON`, `AttrAst`, `CallClientProviderProps`, `TKey2`, `FormattingRequestKind`, `FutureNumber`, `MappedNameValue`, `SearchView`, `KeyFrameLink`, `Transporter`, `TooltipInfo`, `Buffer`, `CreeperPoint`, `EventFnSuccess`, `Split`, `FieldFilterState`, `StunProtocol`, `BrowserTranslateLoader`, `DebugId`, `Objective`, `SyncResultModel`, `RollupOutput`, `OutputData`, `UpSampling2D`, `ThermostatFanModeCCSet`, `IdentifierNode`, `Assign`, `DataMap`, `tflite.TFLiteModel`, `ListBundlesCommandInput`, `MDCFloatingLabelFoundation`, `BuildLog`, `INumbersColumn`, `YAMLWorker`, `requests.ListMultipartUploadsRequest`, `SiemResponseFactory`, `APIGatewayProxyEvent`, `Village`, `IIArticlesState`, `DateHistogramBucketAggDependencies`, `ChannelConstants`, `DialogActions`, `PolyfaceBuilder`, `MinAttrs`, `SimEnt`, `Ord`, `RuleModule`, `ISymbol`, `PlotBandOptions`, `Closure`, `KeywordToken`, `requests.ListServiceGatewaysRequest`, `SiblingGroup`, `SubscriptionNotFoundFault`, `JsonAstKeyValue`, `messages.PickleDocString`, `AppSettings`, `DeleteSchemaCommandInput`, `FakeExecution`, `ImageryCommunicatorService`, `CollapseProps`, `CleanupCallback`, `ArgParser`, `Toppy`, `XAndY`, `CustomBond`, `DiagnosticAndArguments`, `IIntegerRange`, `ImportKind`, `HlsPackage`, `NumberFilterFunction`, `DialogContext`, `BSPSphereActor`, `argsT`, `ElasticsearchConfig`, `CommitTransactionCommandInput`, `CompoundPath`, `HookNextFunction`, `IAzureMapFeature`, `VFile`, `EventAttendance`, `types.MouseData`, `HapiRequest`, `IEmailTemplateSaveInput`, `MetaheroToken`, `EditFn`, `SingleBar`, `CipherObject`, `Joiner`, `MigrateEngineOptions`, `CategoryResult`, `ReaderIO`, `EventUI`, `ZoneDef`, `AgencyApiRequest`, `RectInfo`, `XRPose`, `ComplexPluginOutput`, `MatrixReader`, `FlightDataModel`, `FileTypeResult`, `CKBConfig`, `BTCMarkets.instruments`, `JessParser`, `EmailPayload`, `DeleteInvitationsCommandInput`, `OasVersion`, `serialization.Serializable`, `AdministrationScreenService`, `BillCurrencyUnit`, `CreateRegistryCommandInput`, `OptionsObject`, `EditRepositoryPayload`, `SimpleBinaryKernelImpl`, `AutofillMonitor`, `RxJsonSchema`, `Equality`, `CallIdChangedListener`, `StyleDoc`, `RecurringActivity`, `AsyncTestBedConfig`, `PolicyFromES`, `Fig.ExecuteShellCommandFunction`, `IsInstanceProps`, `OSD_FIELD_TYPES`, `PlaceIndex`, `UpSetJSSkeletonPropsImpl`, `CheckType`, `PuzzleID`, `RegionConfig`, `CompressOptions`, `ClientSideSocket`, `FloatAnimationKeyframeHermite`, `KxxRecord`, `PrimitiveProps`, `FloatBuffer`, `ApolloRequest`, `SignatureEntry`, `GetDeviceRequest`, `Listing`, `Tensor`, `StyleFunction`, `DeleteBuilder`, `JsonDocsDependencyGraph`, `WorkflowContext`, `Filterable`, `PropertyInjectInfoType`, `IJsonResourceInfo`, `BinData`, `VideoChatSession`, `SeriesData`, `AckRange`, `ApolloReactHooks.QueryHookOptions`, `RestApplication`, `RestRequest`, `NumberOptions`, `SGSymbolItem`, `AccountGameCenter`, `OAuth`, `NohmClass`, `DistinctQuestion`, `ExposedThing`, `TooltipItem`, `MemoryEngine`, `f32`, `ResolvedTypeReferenceDirectiveWithFailedLookupLocations`, `SassNumber`, `DataResult`, `HyperScriptHelperFn`, `InputSize`, `List`, `SharePluginSetup`, `ApiRevisionContract`, `Legend`, `m.Recipe`, `DataResolverInputHook`, `api.State`, `VueRouter`, `Memento`, `AnimationNode`, `GuildEmoji`, `THREE.TextureDataType`, `KeySequence`, `DragBehavior`, `SQLParserListener`, `FunctionDataStub`, `AlainConfigService`, `ConsoleFake`, `ProofTest`, `ITuple2`, `After`, `Algebra.GroupNode`, `Apply`, `LoggerTransport`, `ICredentialsState`, `GetByIdOptions`, `DaffOrderItem`, `DonwloadSuccessData`, `AnnotationDimensions`, `IActorDef`, `NexusEnumTypeDef`, `B5`, `Decorators`, `MdcTextField`, `IPropertyPaneField`, `TestInputHandler`, `TestDialogConfig`, `AtomArrowBlockElement`, `IProperties`, `RLANAnimationTrackType`, `EditorProps`, `CryptoKeyPair`, `MCU`, `DescribeEventCategoriesCommandInput`, `IHelper`, `RoundingFn`, `AgChartOptions`, `SCNSceneRenderer`, `PiProperty`, `Protocol.Runtime.RemoteObject`, `DataCardsI18nType`, `MoveEvent`, `MatchList`, `IAssetItem`, `FeedbackDelay`, `CPUTensor`, `ProductV2`, `QueryResolvers`, `UIProposal`, `IntegrationMapService`, `ChainableConnectors`, `BotAnchorPoint`, `L2Data`, `TOutput`, `PackageLock`, `CustomScript`, `GridsterComponentInterface`, `ChangeBuffer`, `ThemeContextValue`, `XjointInfo`, `HashAlgorithm`, `IRegionConfig`, `IProductTypeTranslatable`, `MainSettings`, `ChainGetter`, `WizardComponent`, `ModelJsonSchema`, `PipeFlags`, `UICarouselItemComponent`, `ReflectType`, `RepoState`, `EngineDetails`, `StatementAst`, `IOffset`, `WebSocket`, `EntityCollectionService`, `RawTree`, `ClientAuthCode`, `MortalityService`, `StatementedNode`, `RematchRootState`, `IExpressionLoader`, `RenameFn`, `MaybeAsyncHelpers`, `PasswordPolicy`, `MailboxEvent`, `PostgresTestEntity`, `TagConfiguration`, `IParseProps`, `IndexThresholdAlertParams`, `EIP712Types`, `FilterItem`, `CeramicConfig`, `UpdateManyResponse`, `lsp.Range`, `TableValidator`, `PluginOptionsSchemaArgs`, `CallEndedListener`, `SecureClientQuery`, `DescribeReplicationTaskAssessmentRunsCommandInput`, `DateTimeFormatPart`, `Button`, `ModuleInfo`, `FilterManager`, `NetworkSet`, `CloudFormationResource`, `LoadmoreNode`, `VtxLoader`, `CodeProps`, `FilterCreator`, `IErrorObject`, `ts.IScriptSnapshot`, `btSoftBodyWorldInfo`, `JsxOpeningLikeElement`, `InternalBema`, `float32`, `ProgramArgs`, `AddressBookInstance`, `Point4d`, `PostRepository`, `t.TypeOf`, `CreateTagDto`, `BLE`, `SelectOption`, `RootReducerState`, `QueryInfo`, `WhereExpression`, `Bounds`, `EmailDoc`, `ModalConfig`, `ClassPrototype`, `FunctionBody`, `CashScriptListener`, `ChordNode`, `AzureAccessOpts`, `BleService`, `AttachmentView`, `OrderByClauseArgument`, `StringPart`, `HSL`, `PublicationView`, `Keyring`, `QCProject`, `DescribeChannelBanCommandInput`, `SidebarMenu`, `Scraper`, `PolicyBuilderElement`, `FlexConfigurationPlugin`, `GetProductSearchParams`, `IDocEntryWeight`, `XI18nService`, `SVGTitleElement`, `LocalFraudProof`, `CandyDateType`, `StackSeriesData`, `EventHandlerInfo`, `DataViewMetadataColumn`, `CompType`, `LRU`, `StackNavigationOptions`, `apid.EditManualReserveOption`, `PlaybackStatus`, `TransformFlags`, `ENSService`, `WordCloudDataPoint`, `ECPairInterface`, `StepModel`, `SimpleOrder`, `ScriptAst`, `StableSwap`, `GeometryQuery`, `ChartsPlugin`, `TimerProps`, `DistanceM`, `IconifyAPIQueryParams`, `CLM.UserInput`, `DynamicCstr`, `IAuthZConfig`, `requests.ListCompartmentsRequest`, `ProviderProxy`, `Action`, `InputValidationService`, `FlipperServerImpl`, `CommentService`, `SimpleFrameStatistics`, `ImageOptions`, `MagentoCartFactory`, `PropertiesSource`, `EnvTestContext`, `FolderWithId`, `ModelStoreManagerRegistry`, `AppInstanceProposal`, `SequenceContract`, `DeepPath`, `Todos`, `Accessory`, `d.OutputTargetWww`, `PlayCase`, `BillPayer`, `IAmazonImage`, `Project`, `loaderCallback`, `FadingFeature`, `SFCDescriptor`, `Docker.Container`, `ListOfRanges`, `S2GeometryProvider`, `match`, `GraphAnimateConfig`, `VimState`, `sdk.SpeechTranslationConfig`, `SerializerTypes`, `ServerRequestHandler`, `RenderAtomic`, `ScreenProps`, `NavigationBindings`, `AuthorizationDataService`, `K2`, `PlantMember`, `MyUser`, `OtherArticulation`, `WeaponObj`, `iconType`, `DokiTheme`, `NzTabNavItemDirective`, `WaiterConfiguration`, `CounterFacade`, `TableInsertEntityHeaders`, `objPool.IPool`, `TTransport`, `JsonaObject`, `ForceSourceDeployErrorResponse`, `ClientTools`, `ForOfStatement`, `types.DocumentedType`, `SWRConfigInterface`, `UserIDStatus`, `AlertProps`, `LoadMany`, `AudioWorkletNode`, `RpcKernelBaseConnection`, `IFullProps`, `RequestChunk`, `IFileStat`, `CreditedImage`, `UnidirectionalLinkedTransferAppState`, `CueAndLoop`, `ScenarioEvent`, `SpreadElement`, `DaffCompositeProduct`, `TweetMediaState`, `InternalNode`, `CreateDashboardCommandInput`, `FileTypeEnum`, `HostInstructionsQueue`, `IntegerType`, `OAuthEvent`, `OptionsStackingValue`, `ValidationType`, `RepoSyncState`, `StateInterface`, `Ctx`, `AcrylicConfig`, `PaginationService`, `PreparsedSeq`, `JsonDocsEvent`, `$p_Predicate`, `DynamicStyleSheet`, `Saga`, `GitExtension`, `EncodeInfoDisplayItem`, `RangesCache`, `ClientScopeRepresentation`, `ClusterInfo`, `BaseUI5Node`, `EnvironmentType`, `IAmExportedWithEqual`, `PWAContext`, `VirtualHub`, `IWorkflowData`, `WorkNodePath`, `knex.Transaction`, `SecureChannel`, `oai3.Schema`, `WebSocketChannel`, `turfHelpers.FeatureCollection`, `AccordionStore`, `RequestWithSession`, `SurveyQuestionEditorTabDefinition`, `TextShadowItem`, `EnumProperty`, `ROM`, `HashMapState`, `HTMLAnchorElement`, `IHandler`, `JJunction`, `RnM2TextureInfo`, `BrowserDriver`, `ResolvedInfo`, `HemisphereLight`, `IntegrationInfo`, `GridColumnExtension`, `vscode.WebviewPanel`, `SelfDescribing`, `fhir.Composition`, `DebtTokenContract`, `GuildResolvable`, `IntegrationSettingService`, `JPABaseShapeBlock`, `InjectedProps`, `ImportReplacements`, `FetchResponse`, `RaiseNode`, `TransactionSignature`, `TinyDate`, `MDCCornerTreatment`, `SmartPlayer`, `N4`, `AssociationCCRemove`, `Pool3DProgram`, `SQLRow`, `ImageRequestInfo`, `AstBlock`, `CatExpr`, `LocalEnv`, `ResourcePrincipalAuthenticationDetailsProvider`, `HTMLCanvasElement`, `RangeBasedDocumentSymbol`, `OnPushList`, `BriefcaseDb`, `IRolesMap`, `TraverseContext`, `ChannelResolvable`, `code.Position`, `MultiLanguageBatchInput`, `IQueryOptions`, `GetCanonicalFileName`, `DialogRow`, `BorrowingMutex`, `PluginComponents`, `GetServiceCommandInput`, `MockEntityMapperService`, `SchemaElement`, `GridItem`, `TextureSourceOptions`, `LossOrMetricFn`, `AppStateModel`, `ErrorArea`, `reqType`, `IGetTimeSlotInput`, `SidebarState`, `AnalyticsFromRequests`, `CustomResourceRequest`, `ITenantService`, `IFormState`, `Drawing`, `RootStore`, `SelectItem`, `VoiceOptions`, `Birds`, `SubgraphDeploymentIDIsh`, `AssetUtils`, `ParentGroup`, `BarData`, `PrismService`, `CollisionTree`, `dayjs.Dayjs`, `ChimeSdkWrapper`, `HttpProbe`, `makerjs.IModel`, `RegisterOptions`, `TrieNode`, `StreamDeck`, `VehicleEvent`, `ICitable`, `PieSectorDataItem`, `DateFnsHelper`, `DeleteDatasetCommand`, `SqlTuningTaskSqlExecutionPlanStep`, `ts.FormatCodeOptions`, `ItemStyle`, `StartExportTaskCommandInput`, `NativeEventSubscription`, `EmptyStatement`, `Extent`, `ModelResponse`, `NodeVersion`, `ModifyClusterCommandInput`, `GithubRepo`, `LoansService`, `KanbanBoardState`, `ParseResults`, `GridColumnConfig`, `ResolverContext`, `FrameRequestCallback`, `BoundedGrid3D`, `DePacketizerBase`, `ScopedHandler`, `ExecutionWorker`, `IconButtonGridProps`, `DeleteTransformsRequestSchema`, `IStrapiModelExtended`, `Masset`, `freedom.FreedomInModuleEnv`, `Tunnel`, `GeoJsonProperties`, `Optic`, `textChanges.ChangeTracker`, `RenderTarget`, `SortEvent`, `parser.PddlSyntaxNode`, `CallReturnContext`, `NodeWrap`, `Ellipsoid`, `RecordManager`, `express.RequestHandler`, `PartialCell`, `UnaryOpProgram`, `ScriptingDefinition`, `VehicleCountRow`, `PaymentProvider`, `AZSymbolKind`, `JwtUserData`, `S3Config`, `AuthorReadModel`, `MatChipInputEvent`, `ValueMetadataBoolean`, `RemoveEvent`, `PointerCoordinates`, `CrossMentor`, `SimpleOption`, `AnySpec`, `IPicture`, `MessageHeader`, `EntityDictionary`, `IPromise`, `HttpServerType`, `FP`, `TypeVarType`, `IAnyType`, `AUTWindow`, `A2`, `Node.MinimalTransaction`, `PartitionStyle`, `GetQueryStatus`, `LocIdentifier`, `RouterMenuItem`, `FacetValue`, `AsyncSchema`, `IParticleValueAnimation`, `ShortChannelId`, `CoinbaseKey`, `EngineArgs.ApplyMigrationsInput`, `AnyElt`, `StorableComponent`, `CheckAndApproveResult`, `IRequireMotionAction`, `SectionVM`, `DispatcherPayloadMeta`, `ILinePoint`, `ContainerRef`, `DocTableCell`, `EnvFile`, `CanvasLayer`, `Focus`, `FunctionShape`, `MetaBlock`, `ViewerOut`, `DQAgent`, `PickingInfo`, `SkeletalComponent`, `CheckRunPayload`, `SpotLight`, `Vector2Arrow`, `AnchoredChange`, `IBifrostInstance`, `SendInfo`, `ContextSetImpl`, `BooleanLiteral`, `u8`, `JSONSchema3or4`, `HandlebarsTemplateDelegate`, `DeleteBucketTaggingCommandInput`, `DefineDatas`, `NavBarProps`, `TaskManagerConfig`, `Z64Online_ModelAllocation`, `OS`, `NettuAppRequest`, `ProjectRole`, `PluginObject`, `FSJetpack`, `ExtractModConfig`, `KeycloakService`, `Posts`, `IDevice`, `filterInterface`, `Thread`, `GfxRenderPassP_WebGPU`, `PureSelectorsToSelectors`, `vscode.OnEnterRule`, `IParams`, `LoggerConfig`, `CSSResolve`, `AllureGroup`, `CommonAlertState`, `SearchSourceFields`, `ThyDialogRef`, `HTMLStyleElement`, `ServiceWorkerConfig`, `IServiceIdentifier`, `TableFilterDescriptor`, `DocLinksStart`, `SurveyElementEditorContentModel`, `SaveFileReader`, `WritableStream`, `AttributeMask`, `ISPList`, `ExecutionInfo`, `EnumOptions`, `ETHOption`, `SceneControllerConfigurationCCSet`, `RoleType`, `WhenCause`, `AssetInfo`, `G6Edge`, `Micromerge`, `QueryMwRet`, `StartFrame`, `GridIndex`, `ListRepositoriesCommandInput`, `TIndex`, `AuthSigner`, `UpdateBotCommandInput`, `FabricPointerEvent`, `TemplateType`, `EqualityFn`, `Phase`, `RegisteredServiceSingleSignOnParticipationPolicy`, `BrowsingData.DataTypeSet`, `formValues`, `SavedObjectsDeleteOptions`, `JPiece`, `MDCTopAppBarAdapter`, `ECSqlInsertResult`, `MiddlewareResult`, `RemoteDatabase`, `EncString`, `NotebookCellOutput`, `PostcssStrictThemeConfig`, `EventParams`, `StepConditional`, `WebGLRenderer`, `ConnectOptions`, `ethers.providers.TransactionRequest`, `PUPPET.payloads.Message`, `ListFilesStatResult`, `IBasicSessionWithSubscription`, `Customizable`, `NamedModel`, `AttachPolicyCommandInput`, `CssNode`, `LogAttributes`, `ListView`, `EventListenerRegister`, `ImageGallerySource`, `HeaderObject`, `SerializedTreeViewItem`, `UpdateData`, `ShortValidationErrors`, `pxt.auth.Badge`, `TemplateSource`, `GfxProgramDescriptor`, `SfdxWorkspaceChecker`, `ts.WatchOfConfigFile`, `CBPeripheralWithDelegate`, `FieldAppearanceOptions`, `PropertyLike`, `ReConfigChunk`, `SimpleDate`, `AndroidBinding`, `JSONSourceData`, `NzSliderValue`, `UrlGeneratorContract`, `DisjointSetNode`, `RouteConfig`, `DaffOrderTotal`, `TypeDefinitionNode`, `AggregateMeta`, `Process`, `Sinks`, `MembersInfo`, `ResolvedNative`, `FontName`, `PanelComponent`, `IUserWithGroups`, `EmitFlags`, `StateVariables`, `LanguageConfiguration`, `createAction.Action`, `TBEvent`, `SubEntityProps`, `Revalidator`, `JoinTable`, `WS.MessageEvent`, `CheckerBaseParams`, `timePickerModule.TimePicker`, `IndexFormat`, `CameraUpdateResult`, `DragSourceMonitor`, `CreateSelectorFunction`, `ContractInfo`, `ICXCreateOrder`, `RpcRequestFulfillment`, `IPropertiesAppender`, `CommandLineAction`, `RenderMode`, `ParameterNameValue`, `NetworkScope`, `TimeChangeSource`, `ReplyShortChannelIdsEndMessage`, `GetNetworkProfileCommandInput`, `DependencyName`, `LineIndexSnapshot`, `APIHandler`, `GenerateAsyncIterable`, `TableSuggestion`, `HistoryType`, `ExpectResponseBody`, `AlterTableModifyColumnBuilder`, `RootStoreType`, `BuildOptionsInternal`, `CalculateNodePositionOptions`, `WatcherHelper`, `SessionExpired`, `LocalSession`, `AngularScope`, `NzCarouselContentDirective`, `OnResolveArgs`, `MatchArgsToParamsResult`, `IntrinsicTypeDescriptor`, `TimelineDateProfile`, `EnvSimple`, `LoadedConfigSelectors`, `ReferencePosition`, `LayersTreeItem`, `StateDB`, `RenderTask`, `DBAccessQueryResult`, `Vec2`, `CustomCompletionItem`, `ParserResult`, `AnimationEvent`, `InputButtonCombo`, `SyncOptions`, `Retro`, `OOMemberLookupInfo`, `ClampedMonth`, `ISpace`, `EditorConfig`, `HintFile`, `DeleteSnapshotScheduleCommandInput`, `TConstructor`, `PointerStates`, `SCHEMA`, `EnhancedSelector`, `SignalID`, `RuleTarget`, `CircuitState`, `QueryTuple`, `ListMultipartUploadsRequest`, `AnyCardInGame`, `FetchType`, `ProviderConstructor`, `ConstantExpr`, `RenderItem`, `HsMapService`, `EqualityConstraint`, `DependencyManager`, `AppConfigService`, `Electron.WebContents`, `IHooksGetter`, `MarkdownItNode`, `FormatParams`, `TestRenderTag`, `Flanger`, `AppAndCount`, `DialogState`, `Arc3d`, `DarwinMenuItemConstructorOptions`, `IpfsApi`, `Mismatch`, `ISeries`, `Poller`, `faunadb.Client`, `SlippageTolerance`, `EventDispatcher`, `d.HotModuleReplacement`, `PutAccountDedicatedIpWarmupAttributesCommandInput`, `TranslateResult`, `INodeData`, `IMatch`, `ConnectionCloseFrame`, `NSArray`, `IndexField`, `SelectQueryNode`, `GaugeRangeProperty`, `CreateEventSubscriptionMessage`, `TypeRegistry`, `ts.LineAndCharacter`, `CommandInputParameterModel`, `VisToExpressionAst`, `FractalisService`, `DirectiveMetadata`, `PathFinderPath`, `FileBuild`, `ProductSet`, `PostsService`, `GameName`, `PhrasingContent`, `HtmlContextTypeOptions`, `CompilerFileWatcher`, `SelectorInfo`, `InlineDatasources`, `ActionGroup`, `AdminDatabase`, `ScreenSpaceProjection`, `Electron.BrowserWindow`, `TYPE_AMOUNT`, `Timing`, `ChildrenService`, `MarkdownIt`, `ICreateUserDTO`, `EdaBlankPanelComponent`, `IParseOptions`, `EncounterState`, `CustomQueryState`, `CommitterMap`, `MatchEvent`, `IFilterContext`, `ShaderPass`, `FailedShard`, `ActiveSession`, `UploadProps`, `TranslateOptions`, `IndividualTestInfo`, `Elt`, `CalendarViewType`, `jest.CustomMatcher`, `DidExecutedPayload`, `ComposedPublicDevice`, `ParticleEmitter`, `vscode.InputBoxOptions`, `MaybeCurrency`, `UnboundType`, `T.Refs`, `PlugyPage`, `ITagInputItemProps`, `Animated.CompositeAnimation`, `TimelineItemProps`, `Star`, `CommitChangeService`, `TreeSelectionState`, `GeometryKindSet`, `MenuContext`, `StructPrimitiveType`, `LimitExceededException`, `SuggestionsRequest`, `UpdateFilter`, `StatePropsOfCombinator`, `HsButton`, `JsonRpcRecord`, `BuilderEntry`, `MarkExtensionSpec`, `OperationStatus`, `Dryad`, `BoxKeyPair`, `DemoConfig`, `T.Effect`, `Secrets`, `CompareResult`, `BehaviorMode`, `IPermissionState`, `DynamicClasses`, `CollectorEntity`, `bAsset`, `GrayMatterFile`, `CourseId`, `Tabs.Tab`, `IQueryParam`, `ChunkGroup`, `PaletteType`, `SecretRule`, `Redex`, `STColumnButton`, `OmvFeatureFilterDescription`, `UserStore`, `PolygonEditOptions`, `UncachedNpmInfoClient`, `HybridConnection`, `FragmentSpread`, `SolStateMerkleProof`, `VNodeChildren`, `Downloader`, `IpcEvent`, `DeployFunction`, `ProjectState`, `Factory.Type`, `ListrBaseClassOptions`, `IAssetComponentItem`, `SocketStream`, `bsiChecker.Checker`, `NetMDInterface`, `MigrateDev`, `UseComponent`, `IResponseAction`, `StreamSpecification`, `NetworkConfiguration`, `PageModel`, `LoadingController`, `CalloutContextOptions`, `ethers.utils.Deferrable`, `IClientRegistrarOptions`, `KeymapItem`, `Mocha.MochaOptions`, `CombatService`, `React.TouchEvent`, `FieldConfig`, `evt_exec`, `WebrtcConn`, `NormalBold`, `hubCommon.IModel`, `ResponderConfiguration`, `FoldingRangeParams`, `EditorSuggestionPlugin`, `ImageUse`, `todo`, `ScriptBuilder`, `IFluidResolvedUrl`, `SolverT`, `IonRouter`, `CkElementProps`, `ActionSheetController`, `MockState`, `PartialTheme`, `CompositeDisposable`, `FragmentType`, `RecoilTaskInterface`, `VM`, `ConnectionsManagerService`, `RectDelta`, `P2`, `V1WorkflowInputParameterModel`, `AccountEmail_VarsEntry`, `ModelMesh`, `d.Encapsulation`, `MetadataRecord`, `Contour`, `PointCloudOctreeNode`, `Vec3Term`, `A7`, `CompilerBuildStart`, `ReadWriteStream`, `Seeder`, `ArgStmtDecl`, `FlatList`, `DependencySpecifier`, `SiteTreeItem`, `GfxBufferFrequencyHint`, `QueueObject`, `PrimaryKeyType`, `Conv2DProgram`, `ValueAccessor`, `AccountAttribute`, `EndPointService`, `IpAddressWithSubnetMask`, `Effector`, `Bot`, `IFeed`, `TreeViewNode`, `GitBlame`, `DialogService`, `WorkRequestResourceMetadataKey`, `TableData`, `CollectionContext`, `IndexState`, `RootValue`, `NuxtAxiosInstance`, `LogRequest`, `Aes256Key`, `DeleteListenerCommandInput`, `ProviderToken`, `ContractFactory`, `ChainService`, `SelectedScriptStub`, `LogContext`, `DropdownMenuInitialState`, `ImmutablePeriod`, `ListParticipantsResponse`, `VMLElement`, `Nav`, `TreeNodeType`, `t_63513dcd`, `RemoteUser`, `CodeRange`, `BerryOrm`, `DescribeImagesCommandInput`, `IOtherExpectation`, `AutofillField`, `Todo`, `location.CloudLocationOption`, `ServiceInfo`, `PadplusContactPayload`, `UI`, `CRDTObject`, `LengthParams`, `IMessageMetadata`, `WaitImageOptions`, `UnsupportedOperationException`, `ResponseFactory`, `MaterialCache`, `UICollectionViewLayout`, `JsonFile`, `browser.tabs.Tab`, `MetricDimension`, `OpDescription`, `ListingModel`, `unified.Processor`, `TransformPivotConfig`, `Pubkey`, `WsChartService`, `ActiveMigrations`, `RtmpResult`, `ColorPickerEventListener`, `d.JsonDocsMethod`, `VpnGateway`, `FunctionProps`, `DataFormat`, `Teams`, `CodeActionKind`, `FileExtensionMap`, `Vertices`, `ListrEvent`, `LoadingOptions`, `BVEmitter`, `DigitalNode`, `SortService`, `SemanticTree`, `ShapeDef`, `PersistedState`, `RawPackages`, `Insets`, `TransformBaseline`, `ModelHandle`, `ZoneSpec`, `TestHandler`, `MaybeArray`, `Key`, `DataSourceParameters`, `CodeFlowAnalyzer`, `Dropout`, `Contents`, `ApiMethodScheme`, `SymInt`, `ConfigurationCCGet`, `ts.DocumentRegistry`, `PathParser`, `Myth`, `SingularReaderSelector`, `Step`, `ClockOptions`, `WorldLight`, `Redux.Reducer`, `TimingInfo`, `TabOption`, `IpcResponse`, `ListJobsCommandOutput`, `ComputationCache`, `CertificateAndPrivateKeyPair`, `ScaleObject`, `FullUser`, `PreferenceStateModel`, `MessageValue`, `OpenAPIV3.SchemaObject`, `NestedPageMetadata`, `BadgeStyleProps`, `ColumnSeriesDataItem`, `IHttpRes`, `MaterialColor`, `RebaseEntry`, `ILine`, `Sblendid`, `DateUtilsAdapter`, `SwalOptions`, `CalculationId`, `Radius`, `Footnote`, `ISurveyStatus`, `FIRDatabaseReference`, `WordOptions`, `WithCondition`, `SectionsType`, `ISolutionService`, `CreepSetup`, `GraphicMode`, `CoordinatesObject`, `ILinkInfo`, `XPCOM.nsIHttpChannel`, `RecognitionException`, `StringOrNumber`, `Defs.CompactdState`, `AxesTicksDimensions`, `MapFunction`, `gameObject.Fish`, `SignedBy`, `EchPalette`, `DMMF.Mappings`, `SpawnSyncReturns`, `DeeplinkParts`, `internal`, `DriveItemData`, `JID`, `MediaListOptions`, `IDataProvider`, `ComponentMap`, `ProductType`, `IDirectoryModel`, `InputValueDefinitionNode`, `BabelFileResult`, `QAction`, `SendAction`, `TasksStoreService`, `Roles`, `DiffHunk`, `IFileStore`, `ArrowFunction`, `LinkRecordType`, `DescribeTagsCommandInput`, `MatMenuPanel`, `SearchModeDescription`, `TelemetrySender`, `IPublisher`, `VanessaEditor`, `CkbTxGenerator`, `vscode.TextDocumentContentChangeEvent`, `OptionsWithUrl`, `MultiFn1O`, `PutPermissionCommandInput`, `AwsClientProps`, `WEBGL_debug_renderer_info`, `GeneralActionType`, `RootProps`, `CommandLineArgs`, `Observer`, `Performance`, `RowOfAny`, `IAPIRepository`, `DDL2.Schema`, `WithGenericsSubInterface`, `MonthOrYearComponents`, `IDesignLike`, `DemoAppAction`, `ARGS`, `IPC.IFilePickerFileInfo`, `HapService`, `InputObject`, `GetTableRowsResult`, `DOMOutputSpec`, `FrameBase`, `ConvertedType`, `MetricCollection`, `GravityInfo`, `Uint16Array`, `AppearanceProviderFor`, `LightData`, `AuthoringWorkspaceService`, `AnalyticsProvider`, `ValidationContext`, `RequestCredentials`, `OnPreResponseHandler`, `DisclosureStateReturn`, `IdentifyOperation`, `GetProjectCommandInput`, `GridLayout`, `WorkerInterface`, `PathPredicate`, `PositionedTickValue`, `ProviderIndex`, `UseQuery`, `JKRArchive`, `ZeroXOrders`, `ILabShell`, `next.Sketch`, `ClientChangeList`, `IGif`, `BotAdapter`, `BitbucketPrEntity`, `TextElementGroup`, `requests.ListCaptchasRequest`, `Scheme`, `TheEventbridgeEtlStack`, `IBatteryEntityConfig`, `ISourceLocation`, `IFeatureCommand`, `CallbackDataParams`, `PrismaService`, `ZoneManagerProps`, `FileObject`, `HttpAuthenticatedConnection`, `FunctionAppService`, `SceneControllerConfigurationCCGet`, `ElementMetadata`, `SpatialDropout1DLayerConfig`, `DaffStatefulCartItem`, `CompiledHierarchyEntry`, `TestDispatcher`, `page`, `ParameterExpression`, `PIXI.interaction.InteractionEvent`, `LeafletEvent`, `Driver`, `ExtraContext`, `BoomTheme`, `CachedVoiceState`, `FactoryOptions`, `SavedObjectsExportablePredicate`, `RemoteCallParticipants`, `ItemPredicate`, `PopupType`, `GfxBindings`, `RulesModel`, `KsDiagnostic`, `IndexedNode`, `ExpressionAttributeValueMap`, `SortOption`, `GetState`, `AngularFirestore`, `ShapeView`, `RepositoryStatisticsReadModel`, `SoftwareTransaction`, `IPlayable`, `DAL.DEVICE_ID_SYSTEM_DAC`, `EmbeddableStateTransfer`, `Elements`, `Invalidator`, `VariableStatementStructure`, `SearchSessionsConfig`, `EventManagerConfig`, `RTCTrackEvent`, `ArenaCursor`, `PgClass`, `UpdateParameters`, `ItemData`, `PersonalAccessTokenCredentialHandler`, `Prefix`, `DescribeUsersCommandInput`, `Recognizer`, `TrackerConfig`, `TokenSharedQueueResult`, `StreamingClient`, `Letter`, `ByteReader`, `UmlNotation`, `RecommendationType`, `Screenview`, `CanvasEvent`, `MimeType`, `OcticonSymbol`, `ObjectPool`, `StoreManager`, `In`, `ParsedSelector`, `StatedBeanContextValue`, `Placeholder`, `EventActionHandlerMutationActionCallable`, `AccordionItemComponent`, `AnyExpressionRenderDefinition`, `SignalingClient`, `IListItem`, `ScalarMap`, `CalcScaleAnmType`, `BigComplex`, `Uniform`, `NestedResource`, `TestFailure`, `MatTab`, `EIP712Domain`, `DisassociateMemberCommandInput`, `UpdateDatasetEntriesCommandInput`, `StaticBlog`, `IIconProps`, `EventAsReturnType`, `DataAnalyzeStore`, `d.PrerenderResults`, `cxapi.Environment`, `DoClass`, `MapStateProps`, `DragCheckProps`, `TruncatedNormalArgs`, `ReactDivMouseEvent`, `RegularNode`, `T.Matcher`, `AbstractUIClass`, `lex.Token`, `RestServer`, `BuildingEntity`, `DescribeWorkspaceDirectoriesCommandInput`, `EnumLiteralType`, `CreateDBInstanceCommandInput`, `ITaskConfig`, `SourceCode`, `StyledIconProps`, `JwtPair`, `OaiToOai3FileInput`, `StoreValue`, `ExtendedKeyInfo`, `IAmazonFunctionUpsertCommand`, `TMeta`, `TableEntityResultPage`, `ShapeInfo`, `FC`, `IEsSearchResponse`, `HitCircleVerdict`, `DescribeDBClustersCommandInput`, `STATE`, `Defines`, `TileSetAssetPub`, `PhotosaicImage`, `INetEventHandler`, `core.DescribePath`, `DeleteRoomCommandInput`, `DkrTextureCache`, `Initializer`, `ReplicaOnPartition`, `JSONChunk`, `ModelViewer`, `OrbitControl`, `GraphImmut`, `CanvasRenderingContext2D`, `CoinSelectOptions`, `ErrorReason`, `PluginsConfig`, `WebGLProgram`, `IChunkHeader64`, `MatCheckbox`, `SaveEntitiesSuccess`, `EntityComparator`, `CsmPublishingCredentialsPoliciesEntity`, `DownloadItem`, `requests.DeleteJobRequest`, `ArrowProps`, `ParsedPacket`, `GenericGFPoly`, `TimeFormat`, `GAMEOBJECT_SIGN`, `InteractionType`, `OutputError`, `ReferenceRecord`, `PaginationState`, `MysqlError`, `ZRRawEvent`, `NumberLiteralContext`, `SFATextureArray`, `ECDSASignature`, `RustError`, `EncArrayBuffer`, `CreditCardEscrow`, `core.IProducer`, `TEntry`, `CodelistRow`, `AcceptChannelMessage`, `Realm.ObjectSchemaProperty`, `FeeLevel`, `DataFrameAnalyticsConfig`, `DaffCategoryIdRequest`, `SpatialViewState`, `NdQtNode`, `EventTarget`, `IEventContext`, `SearchByIdRequest`, `NaotuConfig`, `ExactPackage`, `ResponsiveColumnSizes`, `UpdateQueue`, `DeleteChannelMembershipCommandInput`, `CardFooterProps`, `WindowRefService`, `CheckpointProps`, `ElementHandleForTag`, `CollectionState`, `FastTag`, `AndroidProjectConfig`, `CallAdapter`, `d.CompilerBuildStart`, `NotificationHandler`, `requests.ListHealthChecksVantagePointsRequest`, `Type_Struct`, `GraphQLSchema`, `DialogBase`, `RouteContext`, `GestureEvent`, `ObjectBindingPattern`, `QualifiedName`, `Semigroupoid2`, `HandlerExecutionContext`, `StylesProps`, `ElementCore`, `LuaComment`, `ErrorItem`, `AccountDevice`, `IBudgieNode`, `BooruCredentials`, `IGameMessage`, `EstreeNode`, `AuctionView`, `GetAccountInfoRequest`, `EncryptedWalletHandler`, `CannonPhysicsComponent`, `ListApplicationsResponse`, `ESLMediaRule`, `GraphRbacManagementClient`, `ThermostatMode`, `WindowInfo`, `OpenSearchDashboardsRequest`, `DocString`, `TextureDataType`, `UserCredential`, `FIRDataSnapshot`, `GoEngineState`, `InstanceProps`, `restify.Response`, `CloudSchedulerClient`, `EntityDbMetadata`, `Parslet`, `ClaimDTO`, `GanttViewDate`, `IDotEnv`, `ConfigStructShape`, `React.ReactPortal`, `GraphQLNamedOutputType`, `FlattenInterpolation`, `MicrosoftComputeExtensionsVirtualMachinesExtensionsProperties`, `LLVMContext`, `IL10nsStrings`, `MapGroup`, `JQuery.Event`, `CatsService`, `KeyValueChangeRecord_`, `ServerItem`, `DSpaceObject`, `IDatabaseDataSource`, `CustomRule`, `StepsProps`, `AxiosInstance`, `ParticleArgs`, `DeleteDomainCommandInput`, `GetColumnWidthFn`, `TruncatableService`, `GtkElement`, `NumberOperands`, `PackageUrlResolver`, `requests.ListUsersRequest`, `GfxSamplerP_WebGPU`, `JSONProtocol`, `OrderPair`, `ISeedPhraseStore`, `PIXI.Text`, `PatternMappingNode`, `StepDetailsExposedState`, `TinyDateType`, `EntityType`, `ShallowRenderer`, `TypeSet`, `UpdateApplicationCommandOutput`, `EntityTypeDecl`, `BusInstance`, `FetchFunction`, `NetworkManagementClient`, `BrowserFeatureKey`, `IpcRenderer`, `WsProvider`, `ITestBillingGroup`, `Shared.SubscriberFactory`, `TSTypeLiteral`, `RneFunctionComponent`, `BlockFriendsRequest`, `POISearchParams`, `SelectionArea`, `QueryListProps`, `L2Creature`, `DiagnosticInfo`, `CreateClusterCommand`, `PrinterType`, `MockTextChannel`, `MessageStatusService`, `ApplicationTheme`, `TitleCollection`, `Persist`, `RenderStatistics`, `Attempt`, `VersionComponent`, `EndpointConfig`, `MerchantGameWinningEntity`, `Shared.TokenRange`, `UnitsImpl`, `MerchantMenuOrderEntity`, `ScatterProgram`, `OutputChannelLogger`, `DetectorCallback`, `PickPoint`, `DemandDTO`, `HTMLImageSource`, `IConnectionFormSubmitData`, `SModelIndex`, `Acc`, `PredicateType`, `DataPacket`, `TermAggregationOptions`, `NotifierService`, `AlertTableItem`, `ElementCreationOptions`, `GetDedicatedIpCommandInput`, `requests.ListPackagesRequest`, `ArgumentTypes`, `IController.IFunction`, `FileWithPath`, `ILoadbalancer`, `TransactionDetail`, `PluginConfig`, `ScrollToService`, `LoginUriApi`, `InternalLabConfiguration`, `ENDAttributeValue`, `NavigatorDelegate`, `AgencyApiResponse`, `IUi`, `ISegSpan`, `CompareAtom`, `PolygonFadingParameters`, `protos.common.SignaturePolicy`, `LogState`, `MarketCreatedInfo`, `InputEventKey`, `FeeAmount`, `BitmapDrawable`, `CommitInfo`, `MetadataCache`, `DataDefinition`, `PlacementConstraint`, `ProtocolFile`, `IEventInfo`, `ISnapshotContents`, `BaseDocumentView`, `TokenValue`, `CSSToken`, `UnionOf`, `ReactInstance`, `ChainStore`, `DebugConfiguration`, `PaneOptions`, `RRTypeWindow`, `UntypedProduct`, `RunnableTask`, `IsLocalScreenSharingActiveChangedListener`, `HyperModelingDecorator`, `SpacedRepetitionSettingsDelegate`, `IDData`, `Path4`, `ChildrenType`, `OpenEditorNode`, `Android`, `Count`, `HttpClientConfig`, `SubType`, `InstanceData`, `ScriptParsedEvent`, `TileGrid`, `PluginDependency`, `SessionStorageService`, `DeleteUtterancesCommandInput`, `XFilter`, `DeauthenticationResult`, `DiagnosticSeverityOverridesMap`, `TextStyleDefinition`, `VNodeStyle`, `MarketsAccount`, `TrackType`, `CreateAddLinkOptions`, `AsyncAction`, `IHand`, `KeyRingSelectablesStore`, `GX.Attr`, `FunctionAppRuntimeSettings`, `GetResultType`, `ts.ScriptKind`, `BlockContext`, `Disk`, `TETemplate`, `NetworkStatusEvent`, `SystemManager`, `Subscribers`, `tEthereumAddress`, `StackReference`, `SchemeObjectsByLayers`, `ParsedIniData`, `Padawan`, `TiledProperty`, `BindingOrAssignmentPattern`, `InstanceOptions`, `ClientRegistry`, `MachineContext`, `ListenerEntry`, `Typed`, `PurchaseOfferingCommandInput`, `StoredChannel`, `MosString128`, `SBDraft2CommandInputParameterModel`, `RoleTuple`, `InstantiatedContractTreeItem`, `AutocompleteRenderInputParams`, `LineTypes.MessageOptions`, `GoogleAppsScript.Spreadsheet.Sheet`, `ILoadbalance`, `GraphQLClient`, `OutPacketBase`, `TransformOutput`, `DataRepository`, `React.FocusEventHandler`, `LineStyle`, `FaunaNumber`, `JSystemFileReaderHelper`, `ApplicationStatus`, `CreateInputCommandInput`, `RecordedDisplayData`, `MROpts`, `IPointCloudTreeNode`, `TocService`, `ZonesManagerProps`, `StateStorageEngine`, `SackChunk`, `ResourceLocation`, `RouteEntry`, `Resizable`, `Stacks`, `SagaGeneratorWithReturn`, `Expand`, `UpdateOneOptions`, `_this`, `ScreenConfigWithParent`, `NodeWithPosition`, `ToJsonOutput`, `ICalendarEvent`, `FooId`, `IPos`, `TcpPacket`, `KeyAction`, `React.PointerEvent`, `TheiaURI`, `SelectorSpec`, `requests.ListRecommendationsRequest`, `LessOptions`, `ScreenDto`, `MetaState`, `NoteType`, `Transfer`, `ModelSchema`, `ClassInterpreter`, `UnaryExpression`, `XYZAnyValues`, `GenericRetryStrategyOptions`, `STPSetupIntent`, `FakeImporter`, `Monorepo`, `DragDropData`, `Protocol.Network.ResponseReceivedExtraInfoEvent`, `ChapterRow`, `SendRequestConfig`, `Types.RawMessage`, `_N`, `MemDown`, `RegistryRuleType`, `Comma`, `VersionCheckTTL`, `LitCallback`, `IamStatement`, `HtmlElementNode`, `IAuthHeader`, `SubEntityType`, `S3DestinationConfiguration`, `DisplayPartsSymbolWriter`, `VariableDeclaration`, `ServiceConfiguration`, `RenderSprite`, `CheckPrivileges`, `BeaconProxy`, `SyntheticEvent`, `NotificationConfiguration`, `TinyPgParams`, `Key4`, `QuerySort`, `SyncedBackupModel`, `IRGBColor`, `Spectator`, `RangeImpl`, `Cobranca`, `Fiddle`, `Effects`, `Config.ProjectConfig`, `ApproxResult`, `DescribeDatasetResponse`, `W`, `PointCloudOctreeGeometry`, `XmlTimestampsCommandInput`, `_ChildType`, `EditCategoryDto`, `NetworkModel`, `KibanaFeature`, `HasuraModuleConfig`, `IndexPatternsService`, `TestVisitor`, `Controlled`, `TagState`, `IOperation`, `Kind`, `PingProbeProtocol`, `SentryCli`, `ProjectConfigChangedEvent`, `AbstractSyntaxTree`, `Prisma`, `RoutingState`, `AutocompleteContext`, `BlockDoc`, `ISimpleConfigFile`, `SqlBuilder`, `album`, `IDashboard`, `KeyValuePair`, `ChildAppFinalConfig`, `SearchCommandInput`, `SearchSessionsMgmtAPI`, `IChangelog`, `Codeblock`, `DBTProjectContainer`, `TimeSheetService`, `PropertyPair`, `ISpawnOptions`, `Calculator`, `FormatTimeInWordsPipe`, `ConditionalExpression`, `AxesProps`, `IMatcher`, `QueryBinder`, `GameContent`, `CollateralizerContract`, `M.Middleware`, `Images.Dimensions`, `OpenGraph`, `LiveList`, `RealtimeController`, `EventAdapter`, `YAMLDocument`, `TemplateLiteral`, `ControlService`, `Firebase`, `CustomFormGroup`, `IEdgeAD`, `ContextErrorMessageProps`, `EventContext`, `ScriptingDefinitionStub`, `DMMF.Document`, `References`, `GestureDelegate`, `DebugProtocol.ContinueArguments`, `NDframe`, `Evaluated`, `IWarehouse`, `SafetyNetConfig`, `IMeasurementEvent`, `SystemUserApi`, `DAL.KEY_W`, `ParamType`, `DAL.DEVICE_ID_TOUCH_SENSOR`, `EntityData`, `AudioParam`, `IEncoderModel`, `IHSL`, `ParseIconsOpts`, `StorageTier`, `TypeScriptEmbeddedSource`, `OutputSchemaField`, `DebugProtocol.SetBreakpointsResponse`, `JumpyWidget`, `JSONRPC`, `Self`, `WebSocketLink`, `AlternateSymbolNameMap`, `Route53`, `GherkinType`, `NetworkLoadBalancer`, `GenericCompressor`, `JsonDocsUsage`, `ArenaNodeInline`, `estypes.MgetResponseItem`, `RunSpec`, `PortfolioOverviewView`, `DriveItem`, `VirtualNetworkPeering`, `IRequestHandler`, `ColumnSeries`, `StopPipelineExecutionCommandInput`, `SimNode`, `HalfBond`, `StartServicesAccessor`, `TReferences`, `ParsedPath`, `PickerColumn`, `UploadRequest`, `SimpleChoiceGameState`, `ConfigurationParams`, `Address4`, `Swagger2Schema`, `DomainsListOptionalParams`, `DokiSticker`, `ReducerHandler`, `SyncValue`, `CallEndReason`, `TokenFetcher`, `DescribeClustersCommandInput`, `MetaService`, `core.LifecycleSettings`, `UICommand`, `PedersenParams`, `CreateThemeCommandInput`, `TypeCache`, `ValidateFilterKueryNode`, `TransactionsResponse`, `QueryContext`, `SidebarTitleProps`, `RippleGlobalOptions`, `HasUniqueIdentifier`, `IEcsServerGroupCommandResult`, `AppFileStatus`, `IImport`, `ts.TryStatement`, `PrimedCase`, `DejaTreeListComponent`, `Selected`, `Geom`, `MemoryStore`, `ComponentCompilerMethod`, `OasSchema`, `SnakePlayer`, `AsyncOptions`, `AreaState`, `EnforceNonEmptyRecord`, `ResumeData`, `MOscPulse`, `VillainService`, `InstallOptions`, `UserInfoStore`, `LineColPos`, `PointSeries`, `Framebuffer2D`, `SearchEmbeddableFactory`, `SetupObjects`, `View.Mail`, `SVGImageElement`, `IconifyIconName`, `TVector`, `FunctionDef`, `JsonSourceFile`, `RemoteParticipantState`, `IResolveWebpackConfigOptions`, `WebRtcTransport`, `FeatureCollection`, `GeneratedReport`, `TypeTarget`, `UIPageViewController`, `DataTypesInput`, `Electron.Menu`, `SpaceMembershipProps`, `TDDraw`, `TotemFile`, `NodeTypeMetricCapacity`, `MThumbnail`, `PlanetComponentRef`, `HttpResponseOptions`, `VariableDeclarationContext`, `android.webkit.WebView`, `NoShrinkArray`, `ContainerClient`, `InitialValues`, `Iterator`, `RouteLocationNormalizedLoaded`, `MapBrowserEvent`, `ICredentials`, `IStaticWebAppWizardContext`, `CrochetActivation`, `d.CompilerEventName`, `TestDataObject`, `Handles`, `RotationManager`, `IndexKey`, `AclEntry`, `SpecDefinitionsService`, `AuthPluginPackage`, `DockerOptions`, `Keybinding`, `P10`, `QueryBodyType`, `PoolClientState`, `Fr`, `ToolsService`, `TsAutocompleteComponent`, `ContinuousDomainFocus`, `UploadTaskSnapshot`, `GitError`, `BuildParams`, `StringWriter`, `ISafeFont`, `AMap.Map`, `ColorMap`, `DfsResult`, `ParsedLock`, `AccountPagination`, `angu.Value`, `DragulaService`, `IKEffector`, `ClusterExplorerNode`, `SchemaFactory`, `TerraformVars`, `ProgramState`, `CollaboratorService`, `ICredentialDataDecryptedObject`, `PanelConfigProps`, `OrgDataSource`, `Matrix33`, `ImplicationProofItem`, `Edge`, `FieldsTree`, `TextDecoder`, `UrlSerializer`, `IDinoRequestEndProps`, `TextAreaProps`, `OpenSearchDashboardsDatatableColumnMeta`, `HdBitcoinCashPayments`, `ICanvasRenderingContext`, `knex`, `DataProvider`, `StringScannerOutput`, `CallbackResult`, `vscode.TextDocumentChangeEvent`, `ScriptVM`, `ValueScopeName`, `NamedBinding`, `IOdspTokens`, `Template`, `EVENT`, `ResolvedConceptAtomTypeEntry`, `IExtensionPlugin`, `FileUploader`, `LoopBackAuth`, `SharedModel`, `NamedVariableMap`, `XTermColorTheme`, `HumidityControlSetpointType`, `ApiAdapter`, `ConfigManager`, `TLinkCallback`, `RenderOption`, `PagedAsyncIterableIterator`, `PaginatedTiles`, `PublicVocabulary`, `Projection`, `DayPlannerSettings`, `StacksMessageType`, `DefaultChangeAnalyzer`, `GroupsService`, `NamedFragments`, `Divider`, `SocialTokenV0`, `requests.ListResourceTypesRequest`, `Models.AccessTier`, `ExtensionContext`, `ObjectSchema`, `SonarQubeApiScm`, `BUNDLE_TYPE`, `commandInterface`, `GridEntry`, `Datetime`, `QListWidgetItem`, `EncryptedWalletsStore`, `DirectiveDef`, `TMenuOption`, `AutoScalingPolicy`, `Witness`, `DebugStateLegend`, `WalkContext`, `AuthenticationState`, `VariableType`, `IQuestionToolboxItem`, `GraphRequest`, `PopupPositionConfig`, `ExtendedOptions`, `Interpret`, `EnqueuedTask`, `ChatAdapter`, `ts.NamedDeclaration`, `Percussion`, `SortEnd`, `MetadataKey`, `IEntityOptions`, `SyncModule`, `SortOrderType`, `FakeSurveyDialog`, `CreateApplicationVersionCommandInput`, `ConnectionGroup`, `DeleteBucketCommandInput`, `CspConfigType`, `EvolvingArrayType`, `ApiResultCallback`, `backend_util.Conv3DInfo`, `ThySlideContainerComponent`, `PublishCommandInput`, `IssueType`, `requests.ListVmClusterNetworksRequest`, `yubo.MessageService`, `FilePathKey`, `ServiceState`, `P2PRequest`, `DescribeClustersResponse`, `TCountData`, `LiteralNode`, `FileOpItem`, `V1Scale`, `DataOptions`, `ChangeTracker`, `ChartOptions`, `PlaylistWithLoadingState`, `EnumValue`, `ModalRef`, `AppNode`, `SuiTabHeader`, `OnceTask`, `NEOONEDataProvider`, `OrderStatusState`, `SelectItemValue`, `SafeString`, `TestChangesetSequence`, `ServerObject`, `OPaths`, `Ganache`, `estypes.QueryDslQueryContainer`, `BBOX`, `AndExpression`, `SiteConfigResource`, `UICollectionView`, `ExceptionListClient`, `AllDestinations`, `App.ui.INotifications`, `EvaluateMid`, `SendData`, `Discord.Client`, `CryptoProvider`, `CodeSpec`, `GossipError`, `GeneralCallbackResult`, `TickPositionsArray`, `SettingsV11`, `AstRoot`, `LonLatArray`, `GetConfigFn`, `RecipientElement`, `ThingsPage`, `RenderParams`, `IgnoreDiagnosticResult`, `Package.Package`, `requests.ListInstanceAgentCommandsRequest`, `EmojiParseOptions`, `ControllerOptions`, `DomainInfo`, `ParameterReflection`, `ClientIdentity`, `LURLGroup`, `ProjectType`, `FormattedEntry`, `IProductTranslatable`, `WaveShaper`, `UserEntity`, `Specifier`, `BBoxObject`, `MeshBasicMaterial`, `PluginOption`, `SummaryObject`, `ILoginState`, `ISubscriptionContext`, `TConfig`, `ICellMarker`, `MiLayerData`, `nodes.RuleSet`, `GeneralSettings`, `androidx.fragment.app.Fragment`, `PrettierConfig`, `ServiceName`, `RootType`, `ArmSaveConfigs`, `ts.FunctionDeclaration`, `OnTabSelectedlistener`, `AnyChildren`, `MatchFilter`, `V1Job`, `planner.Planner`, `MessageReadListener`, `TimestampInMillis`, `IExportMapMetadata`, `ComponentEvent`, `IMergeBlock`, `BookData`, `ListingData`, `AppwriteProjectConfiguration`, `ExpressConnection`, `InputLayerArgs`, `ProductVariantPriceService`, `MessageListener`, `HardRedirectService`, `AfterGenesisBlockApplyContext`, `LuaParse`, `ArrayBuilderSegment`, `BlitzPage`, `PathConfigMap`, `Concourse`, `NitroState`, `WaveProperties`, `ListHealthChecksVantagePointsRequest`, `ShapeStyle`, `InjectContext`, `tfl.SymbolicTensor`, `MappingObject`, `RouteName`, `Restriction`, `DescribeEngineDefaultClusterParametersCommandInput`, `SagaReturnType`, `DoubleLinkedListNode`, `TypedArray`, `commonmark.Node`, `HttpConnection`, `SpineAnimation`, `TraverseCallbackType`, `Shape2DSW`, `VConsoleNetworkRequestItem`, `TypeDictionaryInfo`, `ReferencingColumnBuilder`, `DAVAccount`, `AnnotationOptions`, `SummaryData`, `GroupByPipe`, `GetWebhookParams`, `Contactable`, `KdNode`, `SubmissionCcLicence`, `OnboardingPage`, `ISignalMessage`, `AnnotationLevel`, `Recipient`, `SpyData`, `Buffers`, `CanvasGraphic`, `TensorInfo`, `ToneOscillatorNode`, `LinkData`, `paper.Path`, `PLSQLCompletionDefinition`, `ModuleOptionsWithValidateFalse`, `DeregisterInstanceCommandInput`, `MdcSnackbarRef`, `NetworkDiagnosticChangedEventArgs`, `TRequestWithUser`, `PullFromStorageInfo`, `Cumulative`, `ItemRenderer`, `SyntheticPerformanceBudget`, `LuxonDateTime`, `IMatchWarriorResult`, `Bone`, `ComponentConfig`, `AxisEdge`, `MigrationData`, `Real`, `TokenCategory`, `TmdbTvResult`, `ReactQueryMethodMap`, `RootToken`, `ComponentController`, `EAdvancedSortMethod`, `DeviceManifest`, `apid.ReserveSaveOption`, `UpdateProjectRequest`, `DeviceProps`, `OcsHttpError`, `SecurityQuestionStore`, `DescriptorValue`, `JoinPoint`, `NzUploadFile`, `ScanPaginator`, `ScriptStub`, `MacroTask`, `Token.Token`, `React.VFC`, `BotResponseService`, `ThemeData`, `ILoggerColorParams`, `NoArgListener`, `EnvPaths`, `BundleResult`, `DMMF.Model`, `CastNode`, `RequestBodyParser`, `SwimLane`, `RTCPFB`, `CoinMap`, `TypescriptMember`, `FullConfiguration`, `RuleWithFlags`, `UIEvent`, `Exec`, `DailyRotateFile`, `ForeignKeyModelInterface`, `SenseEditor`, `IndexProperty`, `IExecOptions`, `IndividualChange`, `SagaConfig`, `DomainEntry`, `Transcoder`, `RarityLevel`, `PermissionData`, `ConstructorOrField`, `PlaceholderContent`, `TEmitted`, `KeyLike`, `JSXNode`, `SimpleRange`, `StringDict`, `ExternalAuthenticateModel`, `Fence`, `SortDirectionNumeric`, `RegisteredServiceAttributeReleasePolicy`, `ConfirmDialog`, `PlanningResult`, `ContentLocation`, `ImmutableSelectorNode`, `FeatherProps`, `DocInfo`, `GXMaterialBuilder`, `eventWithTime`, `TableNode`, `FbFormPermission`, `ChartType`, `CacheQueryOptions`, `EvaluationStats`, `DiffError`, `ClippingPlane`, `OrderByItemNode`, `id`, `DeleteTagsCommandInput`, `ClassTypeFlags`, `AsyncGenerator`, `PersianDate`, `ClientId`, `Proto.FileLocationRequestArgs`, `Config.IConfig`, `SearchCallback`, `Draft.EditorState`, `RejectOnNotFound`, `RemoteEngine`, `BinarySensorCCReport`, `SharedStreetsReference`, `UrlGeneratorInternal`, `HTTPRequest`, `FullType`, `StatsCollector`, `TimeRange`, `TouchEventHandler`, `_.Iso`, `EnvsRaw`, `TaskInput`, `SupportedExchange`, `AttentionLevel`, `PointSet`, `ParseField`, `ResourceHash`, `TransmartNegationConstraint`, `Player`, `LocalGatewayTreeItem`, `GamepadEvent`, `UsersEntity`, `RowRenderTreeType`, `EndpointOperationCommandInput`, `SetTree`, `Labels`, `ITriggerEvent`, `SystemMessageProps`, `ListParams`, `Localization`, `TreemapPoint`, `SendEmailJsonDto`, `ReadonlySet`, `NodeDetails`, `FileAvailability`, `ParsingState`, `esbuild.BuildOptions`, `StyledLabelProps`, `Model1`, `ImageMatrix`, `xyTYpe`, `StyleScope`, `JSDocTypedefTag`, `TranslationBundle`, `UpdateDatabaseResponse`, `STPCardBrand`, `StudentFeedback`, `d.CompilerRequestResponse`, `TrackModel`, `CountableExpectation`, `PlayerProps`, `PathVal`, `BuffData`, `Lab`, `ListPartsCommandInput`, `IJetURL`, `TransactionReceiptsEventInfo`, `HSD_Archive`, `PickingCollisionVO`, `SignatureResult`, `Fn0`, `OpenYoloWithTimeoutApi`, `HttpTestingController`, `ServerEngine`, `IValidationResult`, `roleMenuInterface`, `DebugSessionCustomEvent`, `WrapperArray`, `MDCTextFieldInputAdapter`, `Hull`, `EmbedOptions`, `requests.ListExternalContainerDatabasesRequest`, `TransactionOpts`, `MimeParserNode`, `SiteData`, `DocumentUnderstandingServiceClient`, `Filename`, `AbiRange`, `ReduxActionWithPayload`, `MDCListAdapter`, `IWizard`, `FormHook`, `Event_PropertiesEntry`, `DiagramState`, `SegmentedBarItem`, `DashboardSavedObject`, `GLclampf`, `ITextProps`, `ITx`, `AuthenticationVirtualMachine`, `LogicalWhereExpr`, `guildDoc`, `StyleSetEvaluator`, `NSError`, `SpritesStateRecord`, `DefaultGuiState`, `ChangedElementsDb`, `YamlNode`, `MetamaskPolkadotSnap`, `PositionConfig`, `Tester`, `FileSystemProvider`, `UnitsProvider`, `IContextualMenuItemStyles`, `AVRPortConfig`, `DescribeDomainCommandInput`, `ResultList`, `OpenAPI.PathItem`, `AutomationHelper`, `TypeChecker`, `AuthFacade`, `IPageChangeEvent`, `ReadableStreamReader`, `InputSearchExpressionGroup`, `HandlerInfo`, `CeloTxObject`, `RelationshipService`, `IAutocompleteSelectCellEditorParameters`, `ActionQueue`, `MigrateDeploy`, `cc.Event.EventTouch`, `ConstructorParameters`, `NodeContentTree`, `HelpObj`, `ElementWrapper`, `TxOut`, `DubboTcpTransport`, `SpriteComponent`, `TestExecutionContext`, `MutationContext`, `DeployArgs`, `TabularData`, `CspDirectives`, `ExpressionValueError`, `LabelProps`, `UserMetadatumModel`, `MeasureUnitType`, `SegNode`, `EntityStateRecord`, `DatamodelEnum`, `ContentWidget`, `ResourceData`, `WhereClauseContext`, `Optimizer2`, `BatchCertificateTransfer`, `NgPackagrBuilderOptions`, `EncodedManagedModel`, `SQLStatement`, `LiveAtlasPlayer`, `BasicAction`, `XmlSchema`, `Spec`, `Translation`, `GPUProgram`, `SafeBlock`, `InternalStore`, `SimulationInfo`, `PrefixUnaryOperator`, `BrushScope`, `JavaRecord`, `SelectedCriteriaType`, `ResolveSubscriptionFn`, `SpawnFlags`, `ClassWeight`, `AudioVideoFacade`, `PSTDescriptorItem`, `RelayerRequest`, `TileLoader`, `ListClustersRequest`, `InitialStylingValues`, `ResourceLoader`, `CmsStorageEntry`, `GleeMessage`, `Slate`, `sdk.PushAudioInputStream`, `ProcessingContext`, `ESLintProgram`, `SlideLayout`, `GridView`, `LogRecord`, `RTCDataChannelParameters`, `ICSSInJSStyle`, `d.FsWriteResults`, `Ports`, `RemoteConsole`, `LineAndCharacter`, `DiagnosticRelatedInformation`, `StepperContext`, `AlertDescriptionProps`, `OrganizationalUnitPath`, `ThemeResolver`, `CSSBlocksJSXAnalyzer`, `IOperator`, `ElementEntity`, `Refresher`, `CurrentState`, `DependOnFileCondition`, `GetSuccess`, `CopyAuthOptions`, `IMessageListenerWrapper`, `WebdriverIOConfig`, `ExpressionAstNode`, `GeneralOptions`, `RectGraphicsOptions`, `UpdateProfileParams`, `TimeValues`, `HeaderData`, `IPackageInfo`, `PathAndExtension`, `UseMediaState`, `FieldDescription`, `MalNode`, `BroadcastChannel`, `Word`, `DeploymentHandler`, `TreemapSeriesType`, `IUtilityStoreState`, `TsInputComponent`, `PortModel`, `AnnotationVisitor`, `IFilterListRow`, `github.GitHub`, `SimpleTextSymbol`, `android.os.Parcelable`, `Attribute`, `FileShare`, `WalletLinkRelayAbstract`, `IHillResult`, `SchedulerLike`, `OnPreRoutingToolkit`, `DocumentationContext`, `TransferMode`, `MonitoringData`, `AuthClientRepository`, `RequestOpts`, `RemoveTagsFromResourceCommand`, `SetCombinationType`, `PaletteOutput`, `TypePoint`, `FormSubmissionErrors`, `ICellx`, `Events.activate`, `CSharpClass`, `UpdateBillingParams`, `freedom.RTCPeerConnection.RTCConfiguration`, `AuthCode`, `IConvertContext`, `SVGTextElement`, `PipeConnection`, `PaymentParams`, `AstNodeContent`, `PhotoSize`, `BindingFilter`, `L.LatLng`, `EnhancedReducerResult`, `FeederDetails`, `ISourceFileReference`, `ExportSpecifier`, `BlogPost`, `CountStatisticSummary`, `SeasonRequest`, `IBinding`, `TagTree`, `ParameterValueList`, `LanguageState`, `ActionReturn`, `ExtendedPostFrontMatter`, `ResetPasswordInput`, `CmsModelPlugin`, `Publication`, `ApolloLink`, `MockAttr`, `GPUBufferUsageFlags`, `NotificationIOS`, `files.Location`, `RequestUploadService`, `RoleMapping`, `AcceptableType`, `ResolutionKindSpecificLoader`, `DokiThemeConfig`, `PerModuleNameCache`, `SnapshotListParams`, `IListInfo`, `BackblazeB2Bucket`, `PackageManifest`, `types.Output`, `ThreadConnection`, `WindowsManager`, `theia.WorkspaceFolder`, `InlinableCode`, `IMOSStoryAction`, `Framework`, `ThyOverlayTrigger`, `PlanItem` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ner_graphpolygot_MT4TS_en_5.5.0_3.0_1725311999309.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_graphpolygot_MT4TS_en_5.5.0_3.0_1725311999309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\ + .setInputCols(["document"])\ + .setOutputCol("sentence") + +tokenizer = Tokenizer() \ + .setInputCols("sentence") \ + .setOutputCol("token") + +tokenClassifier = BertForTokenClassification.pretrained("roberta_ner_graphpolygot_MT4TS","en") \ + .setInputCols(["sentence", "token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val tokenizer = new Tokenizer() + .setInputCols(Array("sentence")) + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("roberta_ner_graphpolygot_MT4TS","en") + .setInputCols(Array("sentence", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_ner_graphpolygot_MT4TS| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|607.7 MB| + +## References + +References + +- https://huggingface.co/kevinjesse/graphpolygot-MT4TS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_pipeline_xx.md new file mode 100644 index 00000000000000..f59b447c4b2684 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_pipeline pipeline RoBertaForTokenClassification from StivenLancheros +author: John Snow Labs +name: roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_pipeline +date: 2024-09-02 +tags: [xx, open_source, pipeline, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_pipeline` is a Multilingual model originally trained by StivenLancheros. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_pipeline_xx_5.5.0_3.0_1725311077665.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_pipeline_xx_5.5.0_3.0_1725311077665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|438.8 MB| + +## References + +https://huggingface.co/StivenLancheros/roberta-base-biomedical-clinical-es-finetuned-ner-CRAFT_AugmentedTransfer_EN + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_roberta_base_tweetner_2020_2021_continuous_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_roberta_base_tweetner_2020_2021_continuous_pipeline_en.md new file mode 100644 index 00000000000000..91acb14603ec69 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_roberta_base_tweetner_2020_2021_continuous_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_ner_roberta_base_tweetner_2020_2021_continuous_pipeline pipeline RoBertaForTokenClassification from tner +author: John Snow Labs +name: roberta_ner_roberta_base_tweetner_2020_2021_continuous_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ner_roberta_base_tweetner_2020_2021_continuous_pipeline` is a English model originally trained by tner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_base_tweetner_2020_2021_continuous_pipeline_en_5.5.0_3.0_1725311594974.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_base_tweetner_2020_2021_continuous_pipeline_en_5.5.0_3.0_1725311594974.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_ner_roberta_base_tweetner_2020_2021_continuous_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_ner_roberta_base_tweetner_2020_2021_continuous_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_ner_roberta_base_tweetner_2020_2021_continuous_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|443.6 MB| + +## References + +https://huggingface.co/tner/roberta-base-tweetner-2020-2021-continuous + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_spanish_squades_becasincentivos4_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_spanish_squades_becasincentivos4_es.md new file mode 100644 index 00000000000000..1eb35b7f87e057 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_spanish_squades_becasincentivos4_es.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Spanish RobertaForQuestionAnswering Base Cased model (from Evelyn18) +author: John Snow Labs +name: roberta_qa_base_spanish_squades_becasincentivos4 +date: 2024-09-02 +tags: [es, open_source, roberta, question_answering, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-spanish-squades-becasIncentivos4` is a Spanish model originally trained by `Evelyn18`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_becasincentivos4_es_5.5.0_3.0_1725252081843.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_becasincentivos4_es_5.5.0_3.0_1725252081843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_spanish_squades_becasincentivos4","es")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_spanish_squades_becasincentivos4","es") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_base_spanish_squades_becasincentivos4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|es| +|Size:|459.1 MB| + +## References + +References + +- https://huggingface.co/Evelyn18/roberta-base-spanish-squades-becasIncentivos4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_squad2_finetuned_squad2_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_squad2_finetuned_squad2_en.md new file mode 100644 index 00000000000000..c4bf2f3b026526 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_squad2_finetuned_squad2_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English RobertaForQuestionAnswering Base Cased model (from Marscen) +author: John Snow Labs +name: roberta_qa_base_squad2_finetuned_squad2 +date: 2024-09-02 +tags: [en, open_source, roberta, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-squad2-finetuned-squad2` is a English model originally trained by `Marscen`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad2_finetuned_squad2_en_5.5.0_3.0_1725252777799.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad2_finetuned_squad2_en_5.5.0_3.0_1725252777799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_squad2_finetuned_squad2","en")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_squad2_finetuned_squad2","en") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_base_squad2_finetuned_squad2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.6 MB| + +## References + +References + +- https://huggingface.co/Marscen/roberta-base-squad2-finetuned-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_squad2_finetuned_squad2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_squad2_finetuned_squad2_pipeline_en.md new file mode 100644 index 00000000000000..1c0fe338b93380 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_squad2_finetuned_squad2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_base_squad2_finetuned_squad2_pipeline pipeline RoBertaForQuestionAnswering from Marscen +author: John Snow Labs +name: roberta_qa_base_squad2_finetuned_squad2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_base_squad2_finetuned_squad2_pipeline` is a English model originally trained by Marscen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad2_finetuned_squad2_pipeline_en_5.5.0_3.0_1725252801960.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad2_finetuned_squad2_pipeline_en_5.5.0_3.0_1725252801960.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_base_squad2_finetuned_squad2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_base_squad2_finetuned_squad2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_base_squad2_finetuned_squad2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/Marscen/roberta-base-squad2-finetuned-squad2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_squad2_finetuned_visquad_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_squad2_finetuned_visquad_en.md new file mode 100644 index 00000000000000..2402b8c1d4f7dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_squad2_finetuned_visquad_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English RobertaForQuestionAnswering Base Cased model (from khoanvm) +author: John Snow Labs +name: roberta_qa_base_squad2_finetuned_visquad +date: 2024-09-02 +tags: [en, open_source, roberta, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-squad2-finetuned-visquad` is a English model originally trained by `khoanvm`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad2_finetuned_visquad_en_5.5.0_3.0_1725251932157.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad2_finetuned_visquad_en_5.5.0_3.0_1725251932157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_squad2_finetuned_visquad","en")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_squad2_finetuned_visquad","en") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_base_squad2_finetuned_visquad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.6 MB| + +## References + +References + +- https://huggingface.co/khoanvm/roberta-base-squad2-finetuned-visquad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_becasv4.1_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_becasv4.1_es.md new file mode 100644 index 00000000000000..d9a4207deb2b3b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_becasv4.1_es.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Spanish RobertaForQuestionAnswering Cased model (from Evelyn18) +author: John Snow Labs +name: roberta_qa_becasv4.1 +date: 2024-09-02 +tags: [es, open_source, roberta, question_answering, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `BECASV4.1` is a Spanish model originally trained by `Evelyn18`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_becasv4.1_es_5.5.0_3.0_1725252069364.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_becasv4.1_es_5.5.0_3.0_1725252069364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_becasv4.1","es")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_becasv4.1","es") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_becasv4.1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|es| +|Size:|459.1 MB| + +## References + +References + +- https://huggingface.co/Evelyn18/BECASV4.1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_becasv4.1_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_becasv4.1_pipeline_es.md new file mode 100644 index 00000000000000..f1c902e36f8eae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_becasv4.1_pipeline_es.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Castilian, Spanish roberta_qa_becasv4.1_pipeline pipeline RoBertaForQuestionAnswering from Evelyn18 +author: John Snow Labs +name: roberta_qa_becasv4.1_pipeline +date: 2024-09-02 +tags: [es, open_source, pipeline, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_becasv4.1_pipeline` is a Castilian, Spanish model originally trained by Evelyn18. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_becasv4.1_pipeline_es_5.5.0_3.0_1725252094448.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_becasv4.1_pipeline_es_5.5.0_3.0_1725252094448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_becasv4.1_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_becasv4.1_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_becasv4.1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|459.1 MB| + +## References + +https://huggingface.co/Evelyn18/BECASV4.1 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_dpr_nq_reader_roberta_base_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_dpr_nq_reader_roberta_base_v2_en.md new file mode 100644 index 00000000000000..0cf527fcc8a279 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_dpr_nq_reader_roberta_base_v2_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English RobertaForQuestionAnswering (from nlpconnect) +author: John Snow Labs +name: roberta_qa_dpr_nq_reader_roberta_base_v2 +date: 2024-09-02 +tags: [en, open_source, question_answering, roberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `dpr-nq-reader-roberta-base-v2` is a English model originally trained by `nlpconnect`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_dpr_nq_reader_roberta_base_v2_en_5.5.0_3.0_1725251674364.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_dpr_nq_reader_roberta_base_v2_en_5.5.0_3.0_1725251674364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_dpr_nq_reader_roberta_base_v2","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = RoBertaForQuestionAnswering +.pretrained("roberta_qa_dpr_nq_reader_roberta_base_v2","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.roberta.base_v2").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_dpr_nq_reader_roberta_base_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|465.6 MB| + +## References + +References + +- https://huggingface.co/nlpconnect/dpr-nq-reader-roberta-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_dpr_nq_reader_roberta_base_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_dpr_nq_reader_roberta_base_v2_pipeline_en.md new file mode 100644 index 00000000000000..ebc563ed87ab39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_dpr_nq_reader_roberta_base_v2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_dpr_nq_reader_roberta_base_v2_pipeline pipeline RoBertaForQuestionAnswering from nlpconnect +author: John Snow Labs +name: roberta_qa_dpr_nq_reader_roberta_base_v2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_dpr_nq_reader_roberta_base_v2_pipeline` is a English model originally trained by nlpconnect. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_dpr_nq_reader_roberta_base_v2_pipeline_en_5.5.0_3.0_1725251704416.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_dpr_nq_reader_roberta_base_v2_pipeline_en_5.5.0_3.0_1725251704416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_dpr_nq_reader_roberta_base_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_dpr_nq_reader_roberta_base_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_dpr_nq_reader_roberta_base_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.6 MB| + +## References + +https://huggingface.co/nlpconnect/dpr-nq-reader-roberta-base-v2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_finetuned_country_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_finetuned_country_en.md new file mode 100644 index 00000000000000..e6968c631b843d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_finetuned_country_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English RobertaForQuestionAnswering Cased model (from nsridhar) +author: John Snow Labs +name: roberta_qa_finetuned_country +date: 2024-09-02 +tags: [en, open_source, roberta, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-finetuned-country` is a English model originally trained by `nsridhar`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_country_en_5.5.0_3.0_1725251998694.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_country_en_5.5.0_3.0_1725251998694.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_finetuned_country","en")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_finetuned_country","en") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_finetuned_country| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.7 MB| + +## References + +References + +- https://huggingface.co/nsridhar/roberta-finetuned-country \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_finetuned_country_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_finetuned_country_pipeline_en.md new file mode 100644 index 00000000000000..5411ee51b46c46 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_finetuned_country_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_finetuned_country_pipeline pipeline RoBertaForQuestionAnswering from nsridhar +author: John Snow Labs +name: roberta_qa_finetuned_country_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_finetuned_country_pipeline` is a English model originally trained by nsridhar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_country_pipeline_en_5.5.0_3.0_1725252025265.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_country_pipeline_en_5.5.0_3.0_1725252025265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_finetuned_country_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_finetuned_country_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_finetuned_country_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.7 MB| + +## References + +https://huggingface.co/nsridhar/roberta-finetuned-country + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_en.md new file mode 100644 index 00000000000000..4f643ddcd9f5a4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English RobertaForQuestionAnswering Large Cased model (from anas-awadalla) +author: John Snow Labs +name: roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0 +date: 2024-09-02 +tags: [en, open_source, roberta, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-large-few-shot-k-32-finetuned-squad-seed-0` is a English model originally trained by `anas-awadalla`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_en_5.5.0_3.0_1725252817737.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_en_5.5.0_3.0_1725252817737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0","en")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0","en") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +References + +- https://huggingface.co/anas-awadalla/roberta-large-few-shot-k-32-finetuned-squad-seed-0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_pipeline_en.md new file mode 100644 index 00000000000000..93cce0941bcf20 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla +author: John Snow Labs +name: roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_pipeline` is a English model originally trained by anas-awadalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_pipeline_en_5.5.0_3.0_1725252907697.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_pipeline_en_5.5.0_3.0_1725252907697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_large_few_shot_k_32_finetuned_squad_seed_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/anas-awadalla/roberta-large-few-shot-k-32-finetuned-squad-seed-0 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_large_fine_tuned_squad_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_large_fine_tuned_squad_es.md new file mode 100644 index 00000000000000..93e60e6350abfe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_large_fine_tuned_squad_es.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Spanish RobertaForQuestionAnswering Large Cased model (from stevemobs) +author: John Snow Labs +name: roberta_qa_large_fine_tuned_squad +date: 2024-09-02 +tags: [es, open_source, roberta, question_answering, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-large-fine-tuned-squad-es` is a Spanish model originally trained by `stevemobs`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_large_fine_tuned_squad_es_5.5.0_3.0_1725251886608.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_large_fine_tuned_squad_es_5.5.0_3.0_1725251886608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_large_fine_tuned_squad","es")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_large_fine_tuned_squad","es") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_large_fine_tuned_squad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|es| +|Size:|1.3 GB| + +## References + +References + +- https://huggingface.co/stevemobs/roberta-large-fine-tuned-squad-es \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_large_fine_tuned_squad_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_large_fine_tuned_squad_pipeline_es.md new file mode 100644 index 00000000000000..8a1c59f1596bff --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_large_fine_tuned_squad_pipeline_es.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Castilian, Spanish roberta_qa_large_fine_tuned_squad_pipeline pipeline RoBertaForQuestionAnswering from stevemobs +author: John Snow Labs +name: roberta_qa_large_fine_tuned_squad_pipeline +date: 2024-09-02 +tags: [es, open_source, pipeline, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_large_fine_tuned_squad_pipeline` is a Castilian, Spanish model originally trained by stevemobs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_large_fine_tuned_squad_pipeline_es_5.5.0_3.0_1725251955365.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_large_fine_tuned_squad_pipeline_es_5.5.0_3.0_1725251955365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_large_fine_tuned_squad_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_large_fine_tuned_squad_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_large_fine_tuned_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|1.3 GB| + +## References + +https://huggingface.co/stevemobs/roberta-large-fine-tuned-squad-es + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_miamiya_base_squad2_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_miamiya_base_squad2_finetuned_squad_en.md new file mode 100644 index 00000000000000..670617201c07ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_miamiya_base_squad2_finetuned_squad_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English RobertaForQuestionAnswering Base Cased model (from miamiya) +author: John Snow Labs +name: roberta_qa_miamiya_base_squad2_finetuned_squad +date: 2024-09-02 +tags: [en, open_source, roberta, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-squad2-finetuned-squad` is a English model originally trained by `miamiya`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_miamiya_base_squad2_finetuned_squad_en_5.5.0_3.0_1725251701673.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_miamiya_base_squad2_finetuned_squad_en_5.5.0_3.0_1725251701673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_miamiya_base_squad2_finetuned_squad","en")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_miamiya_base_squad2_finetuned_squad","en") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_miamiya_base_squad2_finetuned_squad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.5 MB| + +## References + +References + +- https://huggingface.co/miamiya/roberta-base-squad2-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_movie_roberta_squad_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_movie_roberta_squad_en.md new file mode 100644 index 00000000000000..b1de821bf21a1b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_movie_roberta_squad_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English RobertaForQuestionAnswering (from thatdramebaazguy) +author: John Snow Labs +name: roberta_qa_movie_roberta_squad +date: 2024-09-02 +tags: [en, open_source, question_answering, roberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `movie-roberta-squad` is a English model originally trained by `thatdramebaazguy`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_movie_roberta_squad_en_5.5.0_3.0_1725251674572.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_movie_roberta_squad_en_5.5.0_3.0_1725251674572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_movie_roberta_squad","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = RoBertaForQuestionAnswering +.pretrained("roberta_qa_movie_roberta_squad","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.movie_squad.roberta.by_thatdramebaazguy").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_movie_roberta_squad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|466.0 MB| + +## References + +References + +- https://huggingface.co/thatdramebaazguy/movie-roberta-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_en.md new file mode 100644 index 00000000000000..5cf976c8e40227 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English RobertaForQuestionAnswering Base Cased model (from AnonymousSub) +author: John Snow Labs +name: roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3 +date: 2024-09-02 +tags: [en, open_source, roberta, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `recipe_triplet_recipes-roberta-base_squadv2_epochs_3` is a English model originally trained by `AnonymousSub`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_en_5.5.0_3.0_1725252034680.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_en_5.5.0_3.0_1725252034680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3","en")\ + .setInputCols(["document_question", "document_context"])\ + .setOutputCol("answer")\ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[Document_Assembler, Question_Answering]) + +data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val Document_Assembler = new MultiDocumentAssembler() + .setInputCols(Array("question", "context")) + .setOutputCols(Array("document_question", "document_context")) + +val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3","en") + .setInputCols(Array("document_question", "document_context")) + .setOutputCol("answer") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering)) + +val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|466.3 MB| + +## References + +References + +- https://huggingface.co/AnonymousSub/recipe_triplet_recipes-roberta-base_squadv2_epochs_3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_pipeline_en.md new file mode 100644 index 00000000000000..ace2bc8ee9337e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub +author: John Snow Labs +name: roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_pipeline` is a English model originally trained by AnonymousSub. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_pipeline_en_5.5.0_3.0_1725252062298.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_pipeline_en_5.5.0_3.0_1725252062298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_recipe_triplet_recipes_base_squadv2_epochs_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|466.3 MB| + +## References + +https://huggingface.co/AnonymousSub/recipe_triplet_recipes-roberta-base_squadv2_epochs_3 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_FT_newsqa_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_FT_newsqa_en.md new file mode 100644 index 00000000000000..8c5acaeead8474 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_FT_newsqa_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English RobertaForQuestionAnswering (from AnonymousSub) +author: John Snow Labs +name: roberta_qa_roberta_FT_newsqa +date: 2024-09-02 +tags: [en, open_source, question_answering, roberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta_FT_newsqa` is a English model originally trained by `AnonymousSub`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_FT_newsqa_en_5.5.0_3.0_1725252512022.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_FT_newsqa_en_5.5.0_3.0_1725252512022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_FT_newsqa","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = RoBertaForQuestionAnswering +.pretrained("roberta_qa_roberta_FT_newsqa","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.news.roberta.qa_roberta_ft_newsqa.by_AnonymousSub").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_roberta_FT_newsqa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|457.8 MB| + +## References + +References + +- https://huggingface.co/AnonymousSub/roberta_FT_newsqa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_es.md new file mode 100644 index 00000000000000..9c29f00f9d6db6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_es.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Castilian, Spanish roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln RoBertaForQuestionAnswering from hackathon-pln-es +author: John Snow Labs +name: roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln +date: 2024-09-02 +tags: [es, open_source, onnx, question_answering, roberta] +task: Question Answering +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln` is a Castilian, Spanish model originally trained by hackathon-pln-es. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_es_5.5.0_3.0_1725252437530.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_es_5.5.0_3.0_1725252437530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln","es") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln", "es") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|es| +|Size:|464.7 MB| + +## References + +https://huggingface.co/hackathon-pln-es/roberta-base-biomedical-es-squad2-es \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_pipeline_es.md new file mode 100644 index 00000000000000..44628dab649067 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_pipeline_es.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Castilian, Spanish roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_pipeline pipeline RoBertaForQuestionAnswering from hackathon-pln-es +author: John Snow Labs +name: roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_pipeline +date: 2024-09-02 +tags: [es, open_source, pipeline, onnx] +task: Question Answering +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_pipeline` is a Castilian, Spanish model originally trained by hackathon-pln-es. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_pipeline_es_5.5.0_3.0_1725252463252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_pipeline_es_5.5.0_3.0_1725252463252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_roberta_base_biomedical_spanish_squad2_hackathon_pln_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|464.7 MB| + +## References + +https://huggingface.co/hackathon-pln-es/roberta-base-biomedical-es-squad2-es + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_en.md new file mode 100644 index 00000000000000..6fa8e1a83adc65 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English RobertaForQuestionAnswering (from anas-awadalla) +author: John Snow Labs +name: roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42 +date: 2024-09-02 +tags: [en, open_source, question_answering, roberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-few-shot-k-1024-finetuned-squad-seed-42` is a English model originally trained by `anas-awadalla`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_en_5.5.0_3.0_1725252476462.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_en_5.5.0_3.0_1725252476462.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = RoBertaForQuestionAnswering +.pretrained("roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squad.roberta.base_1024d_seed_42").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|446.4 MB| + +## References + +References + +- https://huggingface.co/anas-awadalla/roberta-base-few-shot-k-1024-finetuned-squad-seed-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_pipeline_en.md new file mode 100644 index 00000000000000..85d2c3fce75fa4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla +author: John Snow Labs +name: roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_pipeline` is a English model originally trained by anas-awadalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_pipeline_en_5.5.0_3.0_1725252503757.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_pipeline_en_5.5.0_3.0_1725252503757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_42_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|446.4 MB| + +## References + +https://huggingface.co/anas-awadalla/roberta-base-few-shot-k-1024-finetuned-squad-seed-42 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_en.md new file mode 100644 index 00000000000000..ce9fa1bd06f44a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English RobertaForQuestionAnswering (from anas-awadalla) +author: John Snow Labs +name: roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6 +date: 2024-09-02 +tags: [en, open_source, question_answering, roberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-few-shot-k-128-finetuned-squad-seed-6` is a English model originally trained by `anas-awadalla`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_en_5.5.0_3.0_1725252619373.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_en_5.5.0_3.0_1725252619373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = RoBertaForQuestionAnswering +.pretrained("roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squad.roberta.base_128d_seed_6").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|422.0 MB| + +## References + +References + +- https://huggingface.co/anas-awadalla/roberta-base-few-shot-k-128-finetuned-squad-seed-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_pipeline_en.md new file mode 100644 index 00000000000000..8f9eb3fdd29e69 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla +author: John Snow Labs +name: roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_pipeline` is a English model originally trained by anas-awadalla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_pipeline_en_5.5.0_3.0_1725252660643.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_pipeline_en_5.5.0_3.0_1725252660643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|422.0 MB| + +## References + +https://huggingface.co/anas-awadalla/roberta-base-few-shot-k-128-finetuned-squad-seed-6 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_en.md new file mode 100644 index 00000000000000..76733cd1d5282c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English RobertaForQuestionAnswering (from anas-awadalla) +author: John Snow Labs +name: roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42 +date: 2024-09-02 +tags: [en, open_source, question_answering, roberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-few-shot-k-16-finetuned-squad-seed-42` is a English model originally trained by `anas-awadalla`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_en_5.5.0_3.0_1725252277917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_en_5.5.0_3.0_1725252277917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = RoBertaForQuestionAnswering +.pretrained("roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squad.roberta.base_seed_42").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|424.3 MB| + +## References + +References + +- https://huggingface.co/anas-awadalla/roberta-base-few-shot-k-16-finetuned-squad-seed-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_unqover_roberta_base_squad_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_unqover_roberta_base_squad_en.md new file mode 100644 index 00000000000000..71d33579c25b37 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_unqover_roberta_base_squad_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English RobertaForQuestionAnswering (from tli8hf) +author: John Snow Labs +name: roberta_qa_unqover_roberta_base_squad +date: 2024-09-02 +tags: [en, open_source, question_answering, roberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `unqover-roberta-base-squad` is a English model originally trained by `tli8hf`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_unqover_roberta_base_squad_en_5.5.0_3.0_1725252001537.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_unqover_roberta_base_squad_en_5.5.0_3.0_1725252001537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_unqover_roberta_base_squad","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols("question", "context") +.setOutputCols("document_question", "document_context") + +val spanClassifier = RoBertaForQuestionAnswering +.pretrained("roberta_qa_unqover_roberta_base_squad","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squad.roberta.base.by_tli8hf").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_unqover_roberta_base_squad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.1 MB| + +## References + +References + +- https://huggingface.co/tli8hf/unqover-roberta-base-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_unqover_roberta_base_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_unqover_roberta_base_squad_pipeline_en.md new file mode 100644 index 00000000000000..0538a3fa11b7f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_unqover_roberta_base_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_unqover_roberta_base_squad_pipeline pipeline RoBertaForQuestionAnswering from tli8hf +author: John Snow Labs +name: roberta_qa_unqover_roberta_base_squad_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_unqover_roberta_base_squad_pipeline` is a English model originally trained by tli8hf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_unqover_roberta_base_squad_pipeline_en_5.5.0_3.0_1725252027902.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_unqover_roberta_base_squad_pipeline_en_5.5.0_3.0_1725252027902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_unqover_roberta_base_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_unqover_roberta_base_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_unqover_roberta_base_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.1 MB| + +## References + +https://huggingface.co/tli8hf/unqover-roberta-base-squad + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_en.md new file mode 100644 index 00000000000000..bc00ccdd541e5a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_en.md @@ -0,0 +1,104 @@ +--- +layout: model +title: English RobertaForSequenceClassification Cased model (from mrm8488) +author: John Snow Labs +name: roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech +date: 2024-09-02 +tags: [en, open_source, roberta, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `distilroberta-finetuned-tweets-hate-speech` is a English model originally trained by `mrm8488`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_en_5.5.0_3.0_1725277199543.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_en_5.5.0_3.0_1725277199543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +classifier = RoBertaForSequenceClassification.pretrained("roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val classifer = RoBertaForSequenceClassification.pretrained("roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.distil_roberta.tweet_hate.distilled_finetuned").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|308.9 MB| + +## References + +References + +- https://huggingface.co/mrm8488/distilroberta-finetuned-tweets-hate-speech \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_pipeline_en.md new file mode 100644 index 00000000000000..5d6ea828cb2203 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_pipeline pipeline RoBertaForSequenceClassification from mrm8488 +author: John Snow Labs +name: roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_pipeline` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_pipeline_en_5.5.0_3.0_1725277216335.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_pipeline_en_5.5.0_3.0_1725277216335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_sequence_classifier_distilroberta_finetuned_tweets_hate_speech_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|309.0 MB| + +## References + +https://huggingface.co/mrm8488/distilroberta-finetuned-tweets-hate-speech + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_small_greek_el.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_small_greek_el.md new file mode 100644 index 00000000000000..3f6a48c9c883ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_small_greek_el.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Modern Greek (1453-) roberta_small_greek RoBertaEmbeddings from ClassCat +author: John Snow Labs +name: roberta_small_greek +date: 2024-09-02 +tags: [el, open_source, onnx, embeddings, roberta] +task: Embeddings +language: el +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_small_greek` is a Modern Greek (1453-) model originally trained by ClassCat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_small_greek_el_5.5.0_3.0_1725264500771.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_small_greek_el_5.5.0_3.0_1725264500771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("roberta_small_greek","el") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("roberta_small_greek","el") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_small_greek| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|el| +|Size:|192.1 MB| + +## References + +https://huggingface.co/ClassCat/roberta-small-greek \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_small_greek_pipeline_el.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_small_greek_pipeline_el.md new file mode 100644 index 00000000000000..ce4b4504f32bc8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_small_greek_pipeline_el.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Modern Greek (1453-) roberta_small_greek_pipeline pipeline RoBertaEmbeddings from ClassCat +author: John Snow Labs +name: roberta_small_greek_pipeline +date: 2024-09-02 +tags: [el, open_source, pipeline, onnx] +task: Embeddings +language: el +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_small_greek_pipeline` is a Modern Greek (1453-) model originally trained by ClassCat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_small_greek_pipeline_el_5.5.0_3.0_1725264511729.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_small_greek_pipeline_el_5.5.0_3.0_1725264511729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_small_greek_pipeline", lang = "el") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_small_greek_pipeline", lang = "el") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_small_greek_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|el| +|Size:|192.1 MB| + +## References + +https://huggingface.co/ClassCat/roberta-small-greek + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_tiny_10m_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_tiny_10m_en.md new file mode 100644 index 00000000000000..b701dcd7314875 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_tiny_10m_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_tiny_10m RoBertaEmbeddings from g8a9 +author: John Snow Labs +name: roberta_tiny_10m +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_tiny_10m` is a English model originally trained by g8a9. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_tiny_10m_en_5.5.0_3.0_1725264611728.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_tiny_10m_en_5.5.0_3.0_1725264611728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("roberta_tiny_10m","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("roberta_tiny_10m","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_tiny_10m| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|353.3 MB| + +## References + +https://huggingface.co/g8a9/roberta-tiny-10M \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_tiny_10m_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_tiny_10m_pipeline_en.md new file mode 100644 index 00000000000000..ce5a26c7d5827b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_tiny_10m_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_tiny_10m_pipeline pipeline RoBertaEmbeddings from g8a9 +author: John Snow Labs +name: roberta_tiny_10m_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_tiny_10m_pipeline` is a English model originally trained by g8a9. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_tiny_10m_pipeline_en_5.5.0_3.0_1725264630682.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_tiny_10m_pipeline_en_5.5.0_3.0_1725264630682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_tiny_10m_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_tiny_10m_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_tiny_10m_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|353.3 MB| + +## References + +https://huggingface.co/g8a9/roberta-tiny-10M + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-robertalex_plantl_gob_es_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-02-robertalex_plantl_gob_es_pipeline_es.md new file mode 100644 index 00000000000000..fc30deb3172f8c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-robertalex_plantl_gob_es_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish robertalex_plantl_gob_es_pipeline pipeline RoBertaEmbeddings from PlanTL-GOB-ES +author: John Snow Labs +name: robertalex_plantl_gob_es_pipeline +date: 2024-09-02 +tags: [es, open_source, pipeline, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robertalex_plantl_gob_es_pipeline` is a Castilian, Spanish model originally trained by PlanTL-GOB-ES. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robertalex_plantl_gob_es_pipeline_es_5.5.0_3.0_1725264155577.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robertalex_plantl_gob_es_pipeline_es_5.5.0_3.0_1725264155577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("robertalex_plantl_gob_es_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("robertalex_plantl_gob_es_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|robertalex_plantl_gob_es_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|298.1 MB| + +## References + +https://huggingface.co/PlanTL-GOB-ES/RoBERTalex + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-rubioroberta_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-02-rubioroberta_pipeline_ru.md new file mode 100644 index 00000000000000..ab9d0d14456529 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-rubioroberta_pipeline_ru.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Russian rubioroberta_pipeline pipeline RoBertaEmbeddings from alexyalunin +author: John Snow Labs +name: rubioroberta_pipeline +date: 2024-09-02 +tags: [ru, open_source, pipeline, onnx] +task: Embeddings +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubioroberta_pipeline` is a Russian model originally trained by alexyalunin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubioroberta_pipeline_ru_5.5.0_3.0_1725265017235.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubioroberta_pipeline_ru_5.5.0_3.0_1725265017235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("rubioroberta_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("rubioroberta_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubioroberta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|1.3 GB| + +## References + +https://huggingface.co/alexyalunin/RuBioRoBERTa + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-rubioroberta_ru.md b/docs/_posts/ahmedlone127/2024-09-02-rubioroberta_ru.md new file mode 100644 index 00000000000000..ac4c6ccaf2444b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-rubioroberta_ru.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Russian rubioroberta RoBertaEmbeddings from alexyalunin +author: John Snow Labs +name: rubioroberta +date: 2024-09-02 +tags: [ru, open_source, onnx, embeddings, roberta] +task: Embeddings +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubioroberta` is a Russian model originally trained by alexyalunin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubioroberta_ru_5.5.0_3.0_1725264947622.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubioroberta_ru_5.5.0_3.0_1725264947622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("rubioroberta","ru") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("rubioroberta","ru") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubioroberta| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|ru| +|Size:|1.3 GB| + +## References + +https://huggingface.co/alexyalunin/RuBioRoBERTa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-russian_english_hw_iad_en.md b/docs/_posts/ahmedlone127/2024-09-02-russian_english_hw_iad_en.md new file mode 100644 index 00000000000000..f3c3076e077d71 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-russian_english_hw_iad_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English russian_english_hw_iad MarianTransformer from MegaSerega +author: John Snow Labs +name: russian_english_hw_iad +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`russian_english_hw_iad` is a English model originally trained by MegaSerega. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/russian_english_hw_iad_en_5.5.0_3.0_1725304497203.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/russian_english_hw_iad_en_5.5.0_3.0_1725304497203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("russian_english_hw_iad","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("russian_english_hw_iad","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|russian_english_hw_iad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|526.3 MB| + +## References + +https://huggingface.co/MegaSerega/ru-en-HW-IAD \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-russian_english_hw_iad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-russian_english_hw_iad_pipeline_en.md new file mode 100644 index 00000000000000..eb2b9f38183136 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-russian_english_hw_iad_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English russian_english_hw_iad_pipeline pipeline MarianTransformer from MegaSerega +author: John Snow Labs +name: russian_english_hw_iad_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`russian_english_hw_iad_pipeline` is a English model originally trained by MegaSerega. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/russian_english_hw_iad_pipeline_en_5.5.0_3.0_1725304525591.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/russian_english_hw_iad_pipeline_en_5.5.0_3.0_1725304525591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("russian_english_hw_iad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("russian_english_hw_iad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|russian_english_hw_iad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|526.9 MB| + +## References + +https://huggingface.co/MegaSerega/ru-en-HW-IAD + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_ha.md b/docs/_posts/ahmedlone127/2024-09-02-saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_ha.md new file mode 100644 index 00000000000000..3baf6cd17b20b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_ha.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Hausa saad_speech_recognition_hausa_audio_tonga_tonga_islands_text WhisperForCTC from Baghdad99 +author: John Snow Labs +name: saad_speech_recognition_hausa_audio_tonga_tonga_islands_text +date: 2024-09-02 +tags: [ha, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: ha +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`saad_speech_recognition_hausa_audio_tonga_tonga_islands_text` is a Hausa model originally trained by Baghdad99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_ha_5.5.0_3.0_1725287451878.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_ha_5.5.0_3.0_1725287451878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("saad_speech_recognition_hausa_audio_tonga_tonga_islands_text","ha") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("saad_speech_recognition_hausa_audio_tonga_tonga_islands_text", "ha") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|saad_speech_recognition_hausa_audio_tonga_tonga_islands_text| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ha| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Baghdad99/saad-speech-recognition-hausa-audio-to-text \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_pipeline_ha.md b/docs/_posts/ahmedlone127/2024-09-02-saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_pipeline_ha.md new file mode 100644 index 00000000000000..921918b7dbf111 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_pipeline_ha.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Hausa saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_pipeline pipeline WhisperForCTC from Baghdad99 +author: John Snow Labs +name: saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_pipeline +date: 2024-09-02 +tags: [ha, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ha +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_pipeline` is a Hausa model originally trained by Baghdad99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_pipeline_ha_5.5.0_3.0_1725287548733.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_pipeline_ha_5.5.0_3.0_1725287548733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_pipeline", lang = "ha") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_pipeline", lang = "ha") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|saad_speech_recognition_hausa_audio_tonga_tonga_islands_text_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ha| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Baghdad99/saad-speech-recognition-hausa-audio-to-text + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-safeedit_safety_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-02-safeedit_safety_classifier_en.md new file mode 100644 index 00000000000000..cc5b033069c095 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-safeedit_safety_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English safeedit_safety_classifier RoBertaForSequenceClassification from zjunlp +author: John Snow Labs +name: safeedit_safety_classifier +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`safeedit_safety_classifier` is a English model originally trained by zjunlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/safeedit_safety_classifier_en_5.5.0_3.0_1725238468092.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/safeedit_safety_classifier_en_5.5.0_3.0_1725238468092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("safeedit_safety_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("safeedit_safety_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|safeedit_safety_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/zjunlp/SafeEdit-Safety-Classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-safeedit_safety_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-safeedit_safety_classifier_pipeline_en.md new file mode 100644 index 00000000000000..1090e6a48e15be --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-safeedit_safety_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English safeedit_safety_classifier_pipeline pipeline RoBertaForSequenceClassification from zjunlp +author: John Snow Labs +name: safeedit_safety_classifier_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`safeedit_safety_classifier_pipeline` is a English model originally trained by zjunlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/safeedit_safety_classifier_pipeline_en_5.5.0_3.0_1725238550839.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/safeedit_safety_classifier_pipeline_en_5.5.0_3.0_1725238550839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("safeedit_safety_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("safeedit_safety_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|safeedit_safety_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/zjunlp/SafeEdit-Safety-Classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sci_finnish_bert_en.md b/docs/_posts/ahmedlone127/2024-09-02-sci_finnish_bert_en.md new file mode 100644 index 00000000000000..b3ba16827e50c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sci_finnish_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sci_finnish_bert CamemBertEmbeddings from Sci-fi-vy +author: John Snow Labs +name: sci_finnish_bert +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sci_finnish_bert` is a English model originally trained by Sci-fi-vy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sci_finnish_bert_en_5.5.0_3.0_1725299547137.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sci_finnish_bert_en_5.5.0_3.0_1725299547137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("sci_finnish_bert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("sci_finnish_bert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sci_finnish_bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Sci-fi-vy/Sci-fi-Bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sci_finnish_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sci_finnish_bert_pipeline_en.md new file mode 100644 index 00000000000000..4a2cabe5cbde49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sci_finnish_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sci_finnish_bert_pipeline pipeline CamemBertEmbeddings from Sci-fi-vy +author: John Snow Labs +name: sci_finnish_bert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sci_finnish_bert_pipeline` is a English model originally trained by Sci-fi-vy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sci_finnish_bert_pipeline_en_5.5.0_3.0_1725299626143.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sci_finnish_bert_pipeline_en_5.5.0_3.0_1725299626143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sci_finnish_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sci_finnish_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sci_finnish_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Sci-fi-vy/Sci-fi-Bert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sciencebrief_translation_en.md b/docs/_posts/ahmedlone127/2024-09-02-sciencebrief_translation_en.md new file mode 100644 index 00000000000000..bafcc092901eac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sciencebrief_translation_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sciencebrief_translation MarianTransformer from ieuniversity +author: John Snow Labs +name: sciencebrief_translation +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sciencebrief_translation` is a English model originally trained by ieuniversity. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sciencebrief_translation_en_5.5.0_3.0_1725243659189.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sciencebrief_translation_en_5.5.0_3.0_1725243659189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("sciencebrief_translation","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("sciencebrief_translation","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sciencebrief_translation| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|539.2 MB| + +## References + +https://huggingface.co/ieuniversity/sciencebrief_translation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sciencebrief_translation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sciencebrief_translation_pipeline_en.md new file mode 100644 index 00000000000000..1a4f8000a21eb4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sciencebrief_translation_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sciencebrief_translation_pipeline pipeline MarianTransformer from ieuniversity +author: John Snow Labs +name: sciencebrief_translation_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sciencebrief_translation_pipeline` is a English model originally trained by ieuniversity. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sciencebrief_translation_pipeline_en_5.5.0_3.0_1725243689501.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sciencebrief_translation_pipeline_en_5.5.0_3.0_1725243689501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sciencebrief_translation_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sciencebrief_translation_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sciencebrief_translation_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|539.7 MB| + +## References + +https://huggingface.co/ieuniversity/sciencebrief_translation + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_adaptive_lm_molecules_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_adaptive_lm_molecules_en.md new file mode 100644 index 00000000000000..9f063b35333d36 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_adaptive_lm_molecules_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_adaptive_lm_molecules BertSentenceEmbeddings from mossaic-candle +author: John Snow Labs +name: sent_adaptive_lm_molecules +date: 2024-09-02 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_adaptive_lm_molecules` is a English model originally trained by mossaic-candle. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_adaptive_lm_molecules_en_5.5.0_3.0_1725273612434.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_adaptive_lm_molecules_en_5.5.0_3.0_1725273612434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_adaptive_lm_molecules","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_adaptive_lm_molecules","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_adaptive_lm_molecules| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|263.8 MB| + +## References + +https://huggingface.co/mossaic-candle/adaptive-lm-molecules \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_adaptive_lm_molecules_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_adaptive_lm_molecules_pipeline_en.md new file mode 100644 index 00000000000000..6357671b554273 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_adaptive_lm_molecules_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_adaptive_lm_molecules_pipeline pipeline BertSentenceEmbeddings from mossaic-candle +author: John Snow Labs +name: sent_adaptive_lm_molecules_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_adaptive_lm_molecules_pipeline` is a English model originally trained by mossaic-candle. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_adaptive_lm_molecules_pipeline_en_5.5.0_3.0_1725273691275.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_adaptive_lm_molecules_pipeline_en_5.5.0_3.0_1725273691275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_adaptive_lm_molecules_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_adaptive_lm_molecules_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_adaptive_lm_molecules_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.4 MB| + +## References + +https://huggingface.co/mossaic-candle/adaptive-lm-molecules + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_arbert_ar.md b/docs/_posts/ahmedlone127/2024-09-02-sent_arbert_ar.md new file mode 100644 index 00000000000000..098c3fc65b85ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_arbert_ar.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Arabic sent_arbert BertSentenceEmbeddings from UBC-NLP +author: John Snow Labs +name: sent_arbert +date: 2024-09-02 +tags: [ar, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_arbert` is a Arabic model originally trained by UBC-NLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_arbert_ar_5.5.0_3.0_1725274130789.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_arbert_ar_5.5.0_3.0_1725274130789.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_arbert","ar") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_arbert","ar") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_arbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|ar| +|Size:|605.3 MB| + +## References + +https://huggingface.co/UBC-NLP/ARBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_arbert_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-02-sent_arbert_pipeline_ar.md new file mode 100644 index 00000000000000..cb1e24d5d3b840 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_arbert_pipeline_ar.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Arabic sent_arbert_pipeline pipeline BertSentenceEmbeddings from UBC-NLP +author: John Snow Labs +name: sent_arbert_pipeline +date: 2024-09-02 +tags: [ar, open_source, pipeline, onnx] +task: Embeddings +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_arbert_pipeline` is a Arabic model originally trained by UBC-NLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_arbert_pipeline_ar_5.5.0_3.0_1725274162936.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_arbert_pipeline_ar_5.5.0_3.0_1725274162936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_arbert_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_arbert_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_arbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|605.9 MB| + +## References + +https://huggingface.co/UBC-NLP/ARBERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_arabertv02_twitter_ar.md b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_arabertv02_twitter_ar.md new file mode 100644 index 00000000000000..9d8ac0d585be70 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_arabertv02_twitter_ar.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Arabic sent_bert_base_arabertv02_twitter BertSentenceEmbeddings from aubmindlab +author: John Snow Labs +name: sent_bert_base_arabertv02_twitter +date: 2024-09-02 +tags: [ar, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_arabertv02_twitter` is a Arabic model originally trained by aubmindlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabertv02_twitter_ar_5.5.0_3.0_1725273895910.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabertv02_twitter_ar_5.5.0_3.0_1725273895910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_arabertv02_twitter","ar") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_arabertv02_twitter","ar") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_arabertv02_twitter| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|ar| +|Size:|505.0 MB| + +## References + +https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_arabertv02_twitter_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_arabertv02_twitter_pipeline_ar.md new file mode 100644 index 00000000000000..808170da31921e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_arabertv02_twitter_pipeline_ar.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Arabic sent_bert_base_arabertv02_twitter_pipeline pipeline BertSentenceEmbeddings from aubmindlab +author: John Snow Labs +name: sent_bert_base_arabertv02_twitter_pipeline +date: 2024-09-02 +tags: [ar, open_source, pipeline, onnx] +task: Embeddings +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_arabertv02_twitter_pipeline` is a Arabic model originally trained by aubmindlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabertv02_twitter_pipeline_ar_5.5.0_3.0_1725273922680.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabertv02_twitter_pipeline_ar_5.5.0_3.0_1725273922680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bert_base_arabertv02_twitter_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bert_base_arabertv02_twitter_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_arabertv02_twitter_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|505.6 MB| + +## References + +https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_greek_uncased_v1_pipeline_el.md b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_greek_uncased_v1_pipeline_el.md new file mode 100644 index 00000000000000..cf1891b8688cee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_greek_uncased_v1_pipeline_el.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Modern Greek (1453-) sent_bert_base_greek_uncased_v1_pipeline pipeline BertSentenceEmbeddings from nlpaueb +author: John Snow Labs +name: sent_bert_base_greek_uncased_v1_pipeline +date: 2024-09-02 +tags: [el, open_source, pipeline, onnx] +task: Embeddings +language: el +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_greek_uncased_v1_pipeline` is a Modern Greek (1453-) model originally trained by nlpaueb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_greek_uncased_v1_pipeline_el_5.5.0_3.0_1725273295526.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_greek_uncased_v1_pipeline_el_5.5.0_3.0_1725273295526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bert_base_greek_uncased_v1_pipeline", lang = "el") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bert_base_greek_uncased_v1_pipeline", lang = "el") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_greek_uncased_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|el| +|Size:|421.7 MB| + +## References + +https://huggingface.co/nlpaueb/bert-base-greek-uncased-v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_ko.md b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_ko.md new file mode 100644 index 00000000000000..057d7a61ba67a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_ko.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Korean sent_bert_base BertSentenceEmbeddings from klue +author: John Snow Labs +name: sent_bert_base +date: 2024-09-02 +tags: [ko, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: ko +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base` is a Korean model originally trained by klue. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_ko_5.5.0_3.0_1725273421921.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_ko_5.5.0_3.0_1725273421921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base","ko") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base","ko") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|ko| +|Size:|412.4 MB| + +## References + +https://huggingface.co/klue/bert-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_pipeline_ko.md b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_pipeline_ko.md new file mode 100644 index 00000000000000..9be009bdd82903 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_base_pipeline_ko.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Korean sent_bert_base_pipeline pipeline BertSentenceEmbeddings from klue +author: John Snow Labs +name: sent_bert_base_pipeline +date: 2024-09-02 +tags: [ko, open_source, pipeline, onnx] +task: Embeddings +language: ko +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_pipeline` is a Korean model originally trained by klue. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_pipeline_ko_5.5.0_3.0_1725273443859.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_pipeline_ko_5.5.0_3.0_1725273443859.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bert_base_pipeline", lang = "ko") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bert_base_pipeline", lang = "ko") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ko| +|Size:|413.0 MB| + +## References + +https://huggingface.co/klue/bert-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_bert_large_arabertv02_ar.md b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_large_arabertv02_ar.md new file mode 100644 index 00000000000000..3a2e151da13160 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_large_arabertv02_ar.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Arabic sent_bert_large_arabertv02 BertSentenceEmbeddings from aubmindlab +author: John Snow Labs +name: sent_bert_large_arabertv02 +date: 2024-09-02 +tags: [ar, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_arabertv02` is a Arabic model originally trained by aubmindlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_arabertv02_ar_5.5.0_3.0_1725274241558.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_arabertv02_ar_5.5.0_3.0_1725274241558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_arabertv02","ar") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_arabertv02","ar") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_large_arabertv02| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|ar| +|Size:|1.4 GB| + +## References + +https://huggingface.co/aubmindlab/bert-large-arabertv02 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_bert_large_portuguese_cased_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_large_portuguese_cased_pipeline_pt.md new file mode 100644 index 00000000000000..069f145c156fcf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_large_portuguese_cased_pipeline_pt.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Portuguese sent_bert_large_portuguese_cased_pipeline pipeline BertSentenceEmbeddings from neuralmind +author: John Snow Labs +name: sent_bert_large_portuguese_cased_pipeline +date: 2024-09-02 +tags: [pt, open_source, pipeline, onnx] +task: Embeddings +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_portuguese_cased_pipeline` is a Portuguese model originally trained by neuralmind. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_portuguese_cased_pipeline_pt_5.5.0_3.0_1725273384882.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_portuguese_cased_pipeline_pt_5.5.0_3.0_1725273384882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bert_large_portuguese_cased_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bert_large_portuguese_cased_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_large_portuguese_cased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|1.2 GB| + +## References + +https://huggingface.co/neuralmind/bert-large-portuguese-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_bert_review_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_review_pipeline_en.md new file mode 100644 index 00000000000000..17c606fd1d5c0a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_review_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_bert_review_pipeline pipeline BertSentenceEmbeddings from activebus +author: John Snow Labs +name: sent_bert_review_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_review_pipeline` is a English model originally trained by activebus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_review_pipeline_en_5.5.0_3.0_1725273933629.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_review_pipeline_en_5.5.0_3.0_1725273933629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bert_review_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bert_review_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_review_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|259.0 MB| + +## References + +https://huggingface.co/activebus/BERT_Review + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_bertabaporu_base_uncased_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-02-sent_bertabaporu_base_uncased_pipeline_pt.md new file mode 100644 index 00000000000000..ba2565a87bbf88 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_bertabaporu_base_uncased_pipeline_pt.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Portuguese sent_bertabaporu_base_uncased_pipeline pipeline BertSentenceEmbeddings from pablocosta +author: John Snow Labs +name: sent_bertabaporu_base_uncased_pipeline +date: 2024-09-02 +tags: [pt, open_source, pipeline, onnx] +task: Embeddings +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bertabaporu_base_uncased_pipeline` is a Portuguese model originally trained by pablocosta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bertabaporu_base_uncased_pipeline_pt_5.5.0_3.0_1725273460003.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bertabaporu_base_uncased_pipeline_pt_5.5.0_3.0_1725273460003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bertabaporu_base_uncased_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bertabaporu_base_uncased_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bertabaporu_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|505.3 MB| + +## References + +https://huggingface.co/pablocosta/bertabaporu-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_bertabaporu_base_uncased_pt.md b/docs/_posts/ahmedlone127/2024-09-02-sent_bertabaporu_base_uncased_pt.md new file mode 100644 index 00000000000000..00bc9eaba0783e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_bertabaporu_base_uncased_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese sent_bertabaporu_base_uncased BertSentenceEmbeddings from pablocosta +author: John Snow Labs +name: sent_bertabaporu_base_uncased +date: 2024-09-02 +tags: [pt, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bertabaporu_base_uncased` is a Portuguese model originally trained by pablocosta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bertabaporu_base_uncased_pt_5.5.0_3.0_1725273430123.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bertabaporu_base_uncased_pt_5.5.0_3.0_1725273430123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bertabaporu_base_uncased","pt") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bertabaporu_base_uncased","pt") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bertabaporu_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|pt| +|Size:|504.8 MB| + +## References + +https://huggingface.co/pablocosta/bertabaporu-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_biomednlp_biomedbert_base_uncased_abstract_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_biomednlp_biomedbert_base_uncased_abstract_pipeline_en.md new file mode 100644 index 00000000000000..6e42becb8e1fb2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_biomednlp_biomedbert_base_uncased_abstract_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_biomednlp_biomedbert_base_uncased_abstract_pipeline pipeline BertSentenceEmbeddings from microsoft +author: John Snow Labs +name: sent_biomednlp_biomedbert_base_uncased_abstract_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biomednlp_biomedbert_base_uncased_abstract_pipeline` is a English model originally trained by microsoft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biomednlp_biomedbert_base_uncased_abstract_pipeline_en_5.5.0_3.0_1725274502551.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biomednlp_biomedbert_base_uncased_abstract_pipeline_en_5.5.0_3.0_1725274502551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_biomednlp_biomedbert_base_uncased_abstract_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_biomednlp_biomedbert_base_uncased_abstract_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_biomednlp_biomedbert_base_uncased_abstract_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.6 MB| + +## References + +https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_conflibert_scr_uncased_snowood1_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_conflibert_scr_uncased_snowood1_en.md new file mode 100644 index 00000000000000..0b51a2dc06fce1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_conflibert_scr_uncased_snowood1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_conflibert_scr_uncased_snowood1 BertSentenceEmbeddings from snowood1 +author: John Snow Labs +name: sent_conflibert_scr_uncased_snowood1 +date: 2024-09-02 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_conflibert_scr_uncased_snowood1` is a English model originally trained by snowood1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_conflibert_scr_uncased_snowood1_en_5.5.0_3.0_1725273653466.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_conflibert_scr_uncased_snowood1_en_5.5.0_3.0_1725273653466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_conflibert_scr_uncased_snowood1","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_conflibert_scr_uncased_snowood1","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_conflibert_scr_uncased_snowood1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.0 MB| + +## References + +https://huggingface.co/snowood1/ConfliBERT-scr-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_conflibert_scr_uncased_snowood1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_conflibert_scr_uncased_snowood1_pipeline_en.md new file mode 100644 index 00000000000000..6966a9fe1a7ccb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_conflibert_scr_uncased_snowood1_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_conflibert_scr_uncased_snowood1_pipeline pipeline BertSentenceEmbeddings from snowood1 +author: John Snow Labs +name: sent_conflibert_scr_uncased_snowood1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_conflibert_scr_uncased_snowood1_pipeline` is a English model originally trained by snowood1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_conflibert_scr_uncased_snowood1_pipeline_en_5.5.0_3.0_1725273674763.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_conflibert_scr_uncased_snowood1_pipeline_en_5.5.0_3.0_1725273674763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_conflibert_scr_uncased_snowood1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_conflibert_scr_uncased_snowood1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_conflibert_scr_uncased_snowood1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.5 MB| + +## References + +https://huggingface.co/snowood1/ConfliBERT-scr-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_hatebert_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_hatebert_en.md new file mode 100644 index 00000000000000..f2233119686f3f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_hatebert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_hatebert BertSentenceEmbeddings from GroNLP +author: John Snow Labs +name: sent_hatebert +date: 2024-09-02 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hatebert` is a English model originally trained by GroNLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hatebert_en_5.5.0_3.0_1725273808922.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hatebert_en_5.5.0_3.0_1725273808922.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_hatebert","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_hatebert","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_hatebert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.1 MB| + +## References + +https://huggingface.co/GroNLP/hateBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_hatebert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_hatebert_pipeline_en.md new file mode 100644 index 00000000000000..43f6dd097fef72 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_hatebert_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_hatebert_pipeline pipeline BertSentenceEmbeddings from GroNLP +author: John Snow Labs +name: sent_hatebert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hatebert_pipeline` is a English model originally trained by GroNLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hatebert_pipeline_en_5.5.0_3.0_1725273830487.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hatebert_pipeline_en_5.5.0_3.0_1725273830487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_hatebert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_hatebert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_hatebert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/GroNLP/hateBERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_indobert_base_uncased_id.md b/docs/_posts/ahmedlone127/2024-09-02-sent_indobert_base_uncased_id.md new file mode 100644 index 00000000000000..9092b3b49c2227 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_indobert_base_uncased_id.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Indonesian sent_indobert_base_uncased BertSentenceEmbeddings from indolem +author: John Snow Labs +name: sent_indobert_base_uncased +date: 2024-09-02 +tags: [id, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: id +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_indobert_base_uncased` is a Indonesian model originally trained by indolem. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_indobert_base_uncased_id_5.5.0_3.0_1725273336060.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_indobert_base_uncased_id_5.5.0_3.0_1725273336060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_indobert_base_uncased","id") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_indobert_base_uncased","id") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_indobert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|id| +|Size:|411.7 MB| + +## References + +https://huggingface.co/indolem/indobert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_indobert_base_uncased_pipeline_id.md b/docs/_posts/ahmedlone127/2024-09-02-sent_indobert_base_uncased_pipeline_id.md new file mode 100644 index 00000000000000..2f8960b59db426 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_indobert_base_uncased_pipeline_id.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Indonesian sent_indobert_base_uncased_pipeline pipeline BertSentenceEmbeddings from indolem +author: John Snow Labs +name: sent_indobert_base_uncased_pipeline +date: 2024-09-02 +tags: [id, open_source, pipeline, onnx] +task: Embeddings +language: id +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_indobert_base_uncased_pipeline` is a Indonesian model originally trained by indolem. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_indobert_base_uncased_pipeline_id_5.5.0_3.0_1725273360097.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_indobert_base_uncased_pipeline_id_5.5.0_3.0_1725273360097.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_indobert_base_uncased_pipeline", lang = "id") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_indobert_base_uncased_pipeline", lang = "id") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_indobert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|id| +|Size:|412.3 MB| + +## References + +https://huggingface.co/indolem/indobert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_medbit_r3_plus_it.md b/docs/_posts/ahmedlone127/2024-09-02-sent_medbit_r3_plus_it.md new file mode 100644 index 00000000000000..37910fd227ef1a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_medbit_r3_plus_it.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Italian sent_medbit_r3_plus BertSentenceEmbeddings from IVN-RIN +author: John Snow Labs +name: sent_medbit_r3_plus +date: 2024-09-02 +tags: [it, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: it +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_medbit_r3_plus` is a Italian model originally trained by IVN-RIN. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_medbit_r3_plus_it_5.5.0_3.0_1725273764547.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_medbit_r3_plus_it_5.5.0_3.0_1725273764547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_medbit_r3_plus","it") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_medbit_r3_plus","it") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_medbit_r3_plus| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|it| +|Size:|409.2 MB| + +## References + +https://huggingface.co/IVN-RIN/medBIT-r3-plus \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_medbit_r3_plus_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-02-sent_medbit_r3_plus_pipeline_it.md new file mode 100644 index 00000000000000..bbe0f8d7c7804f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_medbit_r3_plus_pipeline_it.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Italian sent_medbit_r3_plus_pipeline pipeline BertSentenceEmbeddings from IVN-RIN +author: John Snow Labs +name: sent_medbit_r3_plus_pipeline +date: 2024-09-02 +tags: [it, open_source, pipeline, onnx] +task: Embeddings +language: it +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_medbit_r3_plus_pipeline` is a Italian model originally trained by IVN-RIN. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_medbit_r3_plus_pipeline_it_5.5.0_3.0_1725273786702.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_medbit_r3_plus_pipeline_it_5.5.0_3.0_1725273786702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_medbit_r3_plus_pipeline", lang = "it") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_medbit_r3_plus_pipeline", lang = "it") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_medbit_r3_plus_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|it| +|Size:|409.7 MB| + +## References + +https://huggingface.co/IVN-RIN/medBIT-r3-plus + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_muril_base_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_muril_base_cased_pipeline_en.md new file mode 100644 index 00000000000000..2b3a9acd37c22d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_muril_base_cased_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_muril_base_cased_pipeline pipeline BertSentenceEmbeddings from google +author: John Snow Labs +name: sent_muril_base_cased_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_muril_base_cased_pipeline` is a English model originally trained by google. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_muril_base_cased_pipeline_en_5.5.0_3.0_1725274440813.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_muril_base_cased_pipeline_en_5.5.0_3.0_1725274440813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_muril_base_cased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_muril_base_cased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_muril_base_cased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|891.0 MB| + +## References + +https://huggingface.co/google/muril-base-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_sec_bert_base_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_sec_bert_base_en.md new file mode 100644 index 00000000000000..599fe8dc1d2f78 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_sec_bert_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_sec_bert_base BertSentenceEmbeddings from nlpaueb +author: John Snow Labs +name: sent_sec_bert_base +date: 2024-09-02 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_sec_bert_base` is a English model originally trained by nlpaueb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_sec_bert_base_en_5.5.0_3.0_1725273922301.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_sec_bert_base_en_5.5.0_3.0_1725273922301.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_sec_bert_base","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_sec_bert_base","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_sec_bert_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.5 MB| + +## References + +https://huggingface.co/nlpaueb/sec-bert-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_sec_bert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_sec_bert_base_pipeline_en.md new file mode 100644 index 00000000000000..21471d16a4f71f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_sec_bert_base_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_sec_bert_base_pipeline pipeline BertSentenceEmbeddings from nlpaueb +author: John Snow Labs +name: sent_sec_bert_base_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_sec_bert_base_pipeline` is a English model originally trained by nlpaueb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_sec_bert_base_pipeline_en_5.5.0_3.0_1725273948440.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_sec_bert_base_pipeline_en_5.5.0_3.0_1725273948440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_sec_bert_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_sec_bert_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_sec_bert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/nlpaueb/sec-bert-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_sikuroberta_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-02-sent_sikuroberta_pipeline_zh.md new file mode 100644 index 00000000000000..be7c6d1b4587aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_sikuroberta_pipeline_zh.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Chinese sent_sikuroberta_pipeline pipeline BertSentenceEmbeddings from SIKU-BERT +author: John Snow Labs +name: sent_sikuroberta_pipeline +date: 2024-09-02 +tags: [zh, open_source, pipeline, onnx] +task: Embeddings +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_sikuroberta_pipeline` is a Chinese model originally trained by SIKU-BERT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_sikuroberta_pipeline_zh_5.5.0_3.0_1725274377607.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_sikuroberta_pipeline_zh_5.5.0_3.0_1725274377607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_sikuroberta_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_sikuroberta_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_sikuroberta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|406.5 MB| + +## References + +https://huggingface.co/SIKU-BERT/sikuroberta + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_splade_cocondenser_ensembledistil_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_splade_cocondenser_ensembledistil_pipeline_en.md new file mode 100644 index 00000000000000..1c28b6bbd54cfe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sent_splade_cocondenser_ensembledistil_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_splade_cocondenser_ensembledistil_pipeline pipeline BertSentenceEmbeddings from naver +author: John Snow Labs +name: sent_splade_cocondenser_ensembledistil_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_splade_cocondenser_ensembledistil_pipeline` is a English model originally trained by naver. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_splade_cocondenser_ensembledistil_pipeline_en_5.5.0_3.0_1725273597459.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_splade_cocondenser_ensembledistil_pipeline_en_5.5.0_3.0_1725273597459.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_splade_cocondenser_ensembledistil_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_splade_cocondenser_ensembledistil_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_splade_cocondenser_ensembledistil_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.0 MB| + +## References + +https://huggingface.co/naver/splade-cocondenser-ensembledistil + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sentence_transformers_e5_large_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-sentence_transformers_e5_large_v2_en.md new file mode 100644 index 00000000000000..c84a3e968a7d79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sentence_transformers_e5_large_v2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English sentence_transformers_e5_large_v2 E5Embeddings from embaas +author: John Snow Labs +name: sentence_transformers_e5_large_v2 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_transformers_e5_large_v2` is a English model originally trained by embaas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_transformers_e5_large_v2_en_5.5.0_3.0_1725260307358.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_transformers_e5_large_v2_en_5.5.0_3.0_1725260307358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("sentence_transformers_e5_large_v2","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("sentence_transformers_e5_large_v2","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentence_transformers_e5_large_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|796.2 MB| + +## References + +https://huggingface.co/embaas/sentence-transformers-e5-large-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-senticse_en.md b/docs/_posts/ahmedlone127/2024-09-02-senticse_en.md new file mode 100644 index 00000000000000..63cfe5be6fa464 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-senticse_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English senticse RoBertaForSequenceClassification from DILAB-HYU +author: John Snow Labs +name: senticse +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`senticse` is a English model originally trained by DILAB-HYU. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/senticse_en_5.5.0_3.0_1725237934675.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/senticse_en_5.5.0_3.0_1725237934675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("senticse","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("senticse", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|senticse| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|435.5 MB| + +## References + +https://huggingface.co/DILAB-HYU/SentiCSE \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-senticse_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-senticse_pipeline_en.md new file mode 100644 index 00000000000000..f32a6f9e1f408d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-senticse_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English senticse_pipeline pipeline RoBertaForSequenceClassification from DILAB-HYU +author: John Snow Labs +name: senticse_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`senticse_pipeline` is a English model originally trained by DILAB-HYU. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/senticse_pipeline_en_5.5.0_3.0_1725237976928.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/senticse_pipeline_en_5.5.0_3.0_1725237976928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("senticse_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("senticse_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|senticse_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|435.5 MB| + +## References + +https://huggingface.co/DILAB-HYU/SentiCSE + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-setfit_model_labelfaithful_epochs2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-setfit_model_labelfaithful_epochs2_pipeline_en.md new file mode 100644 index 00000000000000..a64f7464ffeff3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-setfit_model_labelfaithful_epochs2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English setfit_model_labelfaithful_epochs2_pipeline pipeline MPNetEmbeddings from mitra-mir +author: John Snow Labs +name: setfit_model_labelfaithful_epochs2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_labelfaithful_epochs2_pipeline` is a English model originally trained by mitra-mir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_labelfaithful_epochs2_pipeline_en_5.5.0_3.0_1725280385714.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_labelfaithful_epochs2_pipeline_en_5.5.0_3.0_1725280385714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("setfit_model_labelfaithful_epochs2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("setfit_model_labelfaithful_epochs2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_model_labelfaithful_epochs2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/mitra-mir/setfit_model_labelfaithful_epochs2 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-setfit_pc_multilabel_example_en.md b/docs/_posts/ahmedlone127/2024-09-02-setfit_pc_multilabel_example_en.md new file mode 100644 index 00000000000000..996fc169727919 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-setfit_pc_multilabel_example_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English setfit_pc_multilabel_example MPNetEmbeddings from taldarim +author: John Snow Labs +name: setfit_pc_multilabel_example +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_pc_multilabel_example` is a English model originally trained by taldarim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_pc_multilabel_example_en_5.5.0_3.0_1725313597636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_pc_multilabel_example_en_5.5.0_3.0_1725313597636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("setfit_pc_multilabel_example","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("setfit_pc_multilabel_example","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_pc_multilabel_example| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/taldarim/setfit-pc-multilabel-example \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-setfit_pc_multilabel_example_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-setfit_pc_multilabel_example_pipeline_en.md new file mode 100644 index 00000000000000..9805f4e2792ae7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-setfit_pc_multilabel_example_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English setfit_pc_multilabel_example_pipeline pipeline MPNetEmbeddings from taldarim +author: John Snow Labs +name: setfit_pc_multilabel_example_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_pc_multilabel_example_pipeline` is a English model originally trained by taldarim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_pc_multilabel_example_pipeline_en_5.5.0_3.0_1725313617385.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_pc_multilabel_example_pipeline_en_5.5.0_3.0_1725313617385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("setfit_pc_multilabel_example_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("setfit_pc_multilabel_example_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_pc_multilabel_example_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/taldarim/setfit-pc-multilabel-example + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-setfit_southern_sotho_icd10_l3_en.md b/docs/_posts/ahmedlone127/2024-09-02-setfit_southern_sotho_icd10_l3_en.md new file mode 100644 index 00000000000000..62728fefa11122 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-setfit_southern_sotho_icd10_l3_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English setfit_southern_sotho_icd10_l3 MPNetEmbeddings from rjac +author: John Snow Labs +name: setfit_southern_sotho_icd10_l3 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_southern_sotho_icd10_l3` is a English model originally trained by rjac. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_southern_sotho_icd10_l3_en_5.5.0_3.0_1725313578513.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_southern_sotho_icd10_l3_en_5.5.0_3.0_1725313578513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("setfit_southern_sotho_icd10_l3","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("setfit_southern_sotho_icd10_l3","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_southern_sotho_icd10_l3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/rjac/setfit-ST-ICD10-L3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-setfit_southern_sotho_icd10_l3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-setfit_southern_sotho_icd10_l3_pipeline_en.md new file mode 100644 index 00000000000000..d77c24ccef9b17 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-setfit_southern_sotho_icd10_l3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English setfit_southern_sotho_icd10_l3_pipeline pipeline MPNetEmbeddings from rjac +author: John Snow Labs +name: setfit_southern_sotho_icd10_l3_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_southern_sotho_icd10_l3_pipeline` is a English model originally trained by rjac. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_southern_sotho_icd10_l3_pipeline_en_5.5.0_3.0_1725313603108.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_southern_sotho_icd10_l3_pipeline_en_5.5.0_3.0_1725313603108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("setfit_southern_sotho_icd10_l3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("setfit_southern_sotho_icd10_l3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_southern_sotho_icd10_l3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/rjac/setfit-ST-ICD10-L3 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sft_sql_embedding_en.md b/docs/_posts/ahmedlone127/2024-09-02-sft_sql_embedding_en.md new file mode 100644 index 00000000000000..3c6c432ccadb0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sft_sql_embedding_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English sft_sql_embedding MPNetEmbeddings from s2593817 +author: John Snow Labs +name: sft_sql_embedding +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sft_sql_embedding` is a English model originally trained by s2593817. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sft_sql_embedding_en_5.5.0_3.0_1725280864003.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sft_sql_embedding_en_5.5.0_3.0_1725280864003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = MPNetEmbeddings.pretrained("sft_sql_embedding","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("sft_sql_embedding","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sft_sql_embedding| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/s2593817/sft-sql-embedding \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sft_sql_embedding_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sft_sql_embedding_pipeline_en.md new file mode 100644 index 00000000000000..39f4ed411d6ad4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sft_sql_embedding_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English sft_sql_embedding_pipeline pipeline MPNetEmbeddings from s2593817 +author: John Snow Labs +name: sft_sql_embedding_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sft_sql_embedding_pipeline` is a English model originally trained by s2593817. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sft_sql_embedding_pipeline_en_5.5.0_3.0_1725280886448.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sft_sql_embedding_pipeline_en_5.5.0_3.0_1725280886448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sft_sql_embedding_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sft_sql_embedding_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sft_sql_embedding_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/s2593817/sft-sql-embedding + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-shanghainese_opus_serbocroatian_chinese_3500_en.md b/docs/_posts/ahmedlone127/2024-09-02-shanghainese_opus_serbocroatian_chinese_3500_en.md new file mode 100644 index 00000000000000..0005e04ef32dad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-shanghainese_opus_serbocroatian_chinese_3500_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English shanghainese_opus_serbocroatian_chinese_3500 MarianTransformer from spycsh +author: John Snow Labs +name: shanghainese_opus_serbocroatian_chinese_3500 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`shanghainese_opus_serbocroatian_chinese_3500` is a English model originally trained by spycsh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/shanghainese_opus_serbocroatian_chinese_3500_en_5.5.0_3.0_1725294442197.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/shanghainese_opus_serbocroatian_chinese_3500_en_5.5.0_3.0_1725294442197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("shanghainese_opus_serbocroatian_chinese_3500","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("shanghainese_opus_serbocroatian_chinese_3500","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|shanghainese_opus_serbocroatian_chinese_3500| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|540.6 MB| + +## References + +https://huggingface.co/spycsh/shanghainese-opus-sh-zh-3500 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-shanghainese_opus_serbocroatian_chinese_3500_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-shanghainese_opus_serbocroatian_chinese_3500_pipeline_en.md new file mode 100644 index 00000000000000..c22759babfda23 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-shanghainese_opus_serbocroatian_chinese_3500_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English shanghainese_opus_serbocroatian_chinese_3500_pipeline pipeline MarianTransformer from spycsh +author: John Snow Labs +name: shanghainese_opus_serbocroatian_chinese_3500_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`shanghainese_opus_serbocroatian_chinese_3500_pipeline` is a English model originally trained by spycsh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/shanghainese_opus_serbocroatian_chinese_3500_pipeline_en_5.5.0_3.0_1725294474562.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/shanghainese_opus_serbocroatian_chinese_3500_pipeline_en_5.5.0_3.0_1725294474562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("shanghainese_opus_serbocroatian_chinese_3500_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("shanghainese_opus_serbocroatian_chinese_3500_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|shanghainese_opus_serbocroatian_chinese_3500_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|541.1 MB| + +## References + +https://huggingface.co/spycsh/shanghainese-opus-sh-zh-3500 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_base_ccnet_stsb100_en.md b/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_base_ccnet_stsb100_en.md new file mode 100644 index 00000000000000..7b1c8df3b02abd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_base_ccnet_stsb100_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sitexsometre_camembert_base_ccnet_stsb100 CamemBertForSequenceClassification from Kigo1974 +author: John Snow Labs +name: sitexsometre_camembert_base_ccnet_stsb100 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sitexsometre_camembert_base_ccnet_stsb100` is a English model originally trained by Kigo1974. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_base_ccnet_stsb100_en_5.5.0_3.0_1725298639061.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_base_ccnet_stsb100_en_5.5.0_3.0_1725298639061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("sitexsometre_camembert_base_ccnet_stsb100","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("sitexsometre_camembert_base_ccnet_stsb100", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sitexsometre_camembert_base_ccnet_stsb100| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|390.8 MB| + +## References + +https://huggingface.co/Kigo1974/sitexsometre-camembert-base-ccnet-stsb100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_base_ccnet_stsb100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_base_ccnet_stsb100_pipeline_en.md new file mode 100644 index 00000000000000..b9b76d10fc9938 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_base_ccnet_stsb100_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sitexsometre_camembert_base_ccnet_stsb100_pipeline pipeline CamemBertForSequenceClassification from Kigo1974 +author: John Snow Labs +name: sitexsometre_camembert_base_ccnet_stsb100_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sitexsometre_camembert_base_ccnet_stsb100_pipeline` is a English model originally trained by Kigo1974. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_base_ccnet_stsb100_pipeline_en_5.5.0_3.0_1725298669799.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_base_ccnet_stsb100_pipeline_en_5.5.0_3.0_1725298669799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sitexsometre_camembert_base_ccnet_stsb100_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sitexsometre_camembert_base_ccnet_stsb100_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sitexsometre_camembert_base_ccnet_stsb100_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|390.8 MB| + +## References + +https://huggingface.co/Kigo1974/sitexsometre-camembert-base-ccnet-stsb100 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_base_ccnet_stsb200_en.md b/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_base_ccnet_stsb200_en.md new file mode 100644 index 00000000000000..d7d7136becd8f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_base_ccnet_stsb200_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sitexsometre_camembert_base_ccnet_stsb200 CamemBertForSequenceClassification from Kigo1974 +author: John Snow Labs +name: sitexsometre_camembert_base_ccnet_stsb200 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sitexsometre_camembert_base_ccnet_stsb200` is a English model originally trained by Kigo1974. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_base_ccnet_stsb200_en_5.5.0_3.0_1725299007527.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_base_ccnet_stsb200_en_5.5.0_3.0_1725299007527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("sitexsometre_camembert_base_ccnet_stsb200","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("sitexsometre_camembert_base_ccnet_stsb200", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sitexsometre_camembert_base_ccnet_stsb200| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|390.8 MB| + +## References + +https://huggingface.co/Kigo1974/sitexsometre-camembert-base-ccnet-stsb200 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_large_stsb200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_large_stsb200_pipeline_en.md new file mode 100644 index 00000000000000..5e7fd6e1cdc22a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_large_stsb200_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sitexsometre_camembert_large_stsb200_pipeline pipeline CamemBertForSequenceClassification from Kigo1974 +author: John Snow Labs +name: sitexsometre_camembert_large_stsb200_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sitexsometre_camembert_large_stsb200_pipeline` is a English model originally trained by Kigo1974. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_large_stsb200_pipeline_en_5.5.0_3.0_1725298854675.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_large_stsb200_pipeline_en_5.5.0_3.0_1725298854675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sitexsometre_camembert_large_stsb200_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sitexsometre_camembert_large_stsb200_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sitexsometre_camembert_large_stsb200_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|805.5 MB| + +## References + +https://huggingface.co/Kigo1974/sitexsometre-camembert-large-stsb200 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sloberta_sl.md b/docs/_posts/ahmedlone127/2024-09-02-sloberta_sl.md new file mode 100644 index 00000000000000..f132d4dc14606e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sloberta_sl.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Slovenian sloberta CamemBertEmbeddings from EMBEDDIA +author: John Snow Labs +name: sloberta +date: 2024-09-02 +tags: [sl, open_source, onnx, embeddings, camembert] +task: Embeddings +language: sl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sloberta` is a Slovenian model originally trained by EMBEDDIA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sloberta_sl_5.5.0_3.0_1725296401882.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sloberta_sl_5.5.0_3.0_1725296401882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("sloberta","sl") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("sloberta","sl") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sloberta| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|sl| +|Size:|263.5 MB| + +## References + +https://huggingface.co/EMBEDDIA/sloberta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sloberta_slo_word_spelling_annotator_pipeline_sl.md b/docs/_posts/ahmedlone127/2024-09-02-sloberta_slo_word_spelling_annotator_pipeline_sl.md new file mode 100644 index 00000000000000..bfc918e3437e10 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sloberta_slo_word_spelling_annotator_pipeline_sl.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Slovenian sloberta_slo_word_spelling_annotator_pipeline pipeline CamemBertEmbeddings from cjvt +author: John Snow Labs +name: sloberta_slo_word_spelling_annotator_pipeline +date: 2024-09-02 +tags: [sl, open_source, pipeline, onnx] +task: Embeddings +language: sl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sloberta_slo_word_spelling_annotator_pipeline` is a Slovenian model originally trained by cjvt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sloberta_slo_word_spelling_annotator_pipeline_sl_5.5.0_3.0_1725297551457.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sloberta_slo_word_spelling_annotator_pipeline_sl_5.5.0_3.0_1725297551457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sloberta_slo_word_spelling_annotator_pipeline", lang = "sl") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sloberta_slo_word_spelling_annotator_pipeline", lang = "sl") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sloberta_slo_word_spelling_annotator_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|sl| +|Size:|412.1 MB| + +## References + +https://huggingface.co/cjvt/SloBERTa-slo-word-spelling-annotator + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-slovene_law_roberta_5_en.md b/docs/_posts/ahmedlone127/2024-09-02-slovene_law_roberta_5_en.md new file mode 100644 index 00000000000000..d1d4be5065f4ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-slovene_law_roberta_5_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English slovene_law_roberta_5 RoBertaForQuestionAnswering from aseljayasooriya +author: John Snow Labs +name: slovene_law_roberta_5 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slovene_law_roberta_5` is a English model originally trained by aseljayasooriya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slovene_law_roberta_5_en_5.5.0_3.0_1725252172990.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slovene_law_roberta_5_en_5.5.0_3.0_1725252172990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("slovene_law_roberta_5","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("slovene_law_roberta_5", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|slovene_law_roberta_5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.7 MB| + +## References + +https://huggingface.co/aseljayasooriya/sl-law-roberta-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-slovene_roberta_base_pipeline_sl.md b/docs/_posts/ahmedlone127/2024-09-02-slovene_roberta_base_pipeline_sl.md new file mode 100644 index 00000000000000..eac43f96219045 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-slovene_roberta_base_pipeline_sl.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Slovenian slovene_roberta_base_pipeline pipeline RoBertaEmbeddings from macedonizer +author: John Snow Labs +name: slovene_roberta_base_pipeline +date: 2024-09-02 +tags: [sl, open_source, pipeline, onnx] +task: Embeddings +language: sl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slovene_roberta_base_pipeline` is a Slovenian model originally trained by macedonizer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slovene_roberta_base_pipeline_sl_5.5.0_3.0_1725264600537.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slovene_roberta_base_pipeline_sl_5.5.0_3.0_1725264600537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("slovene_roberta_base_pipeline", lang = "sl") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("slovene_roberta_base_pipeline", lang = "sl") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|slovene_roberta_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|sl| +|Size:|311.7 MB| + +## References + +https://huggingface.co/macedonizer/sl-roberta-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-slovene_roberta_base_sl.md b/docs/_posts/ahmedlone127/2024-09-02-slovene_roberta_base_sl.md new file mode 100644 index 00000000000000..2badf07254f979 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-slovene_roberta_base_sl.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Slovenian slovene_roberta_base RoBertaEmbeddings from macedonizer +author: John Snow Labs +name: slovene_roberta_base +date: 2024-09-02 +tags: [sl, open_source, onnx, embeddings, roberta] +task: Embeddings +language: sl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slovene_roberta_base` is a Slovenian model originally trained by macedonizer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slovene_roberta_base_sl_5.5.0_3.0_1725264582760.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slovene_roberta_base_sl_5.5.0_3.0_1725264582760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("slovene_roberta_base","sl") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("slovene_roberta_base","sl") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|slovene_roberta_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|sl| +|Size:|311.7 MB| + +## References + +https://huggingface.co/macedonizer/sl-roberta-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-snm_siriraj_en.md b/docs/_posts/ahmedlone127/2024-09-02-snm_siriraj_en.md new file mode 100644 index 00000000000000..39320ea490228c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-snm_siriraj_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English snm_siriraj CamemBertForTokenClassification from Tippawan +author: John Snow Labs +name: snm_siriraj +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, camembert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`snm_siriraj` is a English model originally trained by Tippawan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/snm_siriraj_en_5.5.0_3.0_1725266530202.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/snm_siriraj_en_5.5.0_3.0_1725266530202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = CamemBertForTokenClassification.pretrained("snm_siriraj","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = CamemBertForTokenClassification.pretrained("snm_siriraj", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|snm_siriraj| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|392.1 MB| + +## References + +https://huggingface.co/Tippawan/snm-siriraj \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-snm_siriraj_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-snm_siriraj_pipeline_en.md new file mode 100644 index 00000000000000..c7a8dff0cc0a1b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-snm_siriraj_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English snm_siriraj_pipeline pipeline CamemBertForTokenClassification from Tippawan +author: John Snow Labs +name: snm_siriraj_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`snm_siriraj_pipeline` is a English model originally trained by Tippawan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/snm_siriraj_pipeline_en_5.5.0_3.0_1725266553399.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/snm_siriraj_pipeline_en_5.5.0_3.0_1725266553399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("snm_siriraj_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("snm_siriraj_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|snm_siriraj_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|392.1 MB| + +## References + +https://huggingface.co/Tippawan/snm-siriraj + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_all_mpnet_finetuned_arabic_1000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_all_mpnet_finetuned_arabic_1000_pipeline_en.md new file mode 100644 index 00000000000000..0881dce2fd0586 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_all_mpnet_finetuned_arabic_1000_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English southern_sotho_all_mpnet_finetuned_arabic_1000_pipeline pipeline MPNetEmbeddings from danfeg +author: John Snow Labs +name: southern_sotho_all_mpnet_finetuned_arabic_1000_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_all_mpnet_finetuned_arabic_1000_pipeline` is a English model originally trained by danfeg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_1000_pipeline_en_5.5.0_3.0_1725280966321.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_1000_pipeline_en_5.5.0_3.0_1725280966321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("southern_sotho_all_mpnet_finetuned_arabic_1000_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("southern_sotho_all_mpnet_finetuned_arabic_1000_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|southern_sotho_all_mpnet_finetuned_arabic_1000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-AR-1000 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_v3_test_mpnet_base_allnli_stsb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_v3_test_mpnet_base_allnli_stsb_pipeline_en.md new file mode 100644 index 00000000000000..ecaad36609a36d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_v3_test_mpnet_base_allnli_stsb_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English southern_sotho_v3_test_mpnet_base_allnli_stsb_pipeline pipeline MPNetEmbeddings from tomaarsen +author: John Snow Labs +name: southern_sotho_v3_test_mpnet_base_allnli_stsb_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_v3_test_mpnet_base_allnli_stsb_pipeline` is a English model originally trained by tomaarsen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_v3_test_mpnet_base_allnli_stsb_pipeline_en_5.5.0_3.0_1725313694109.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_v3_test_mpnet_base_allnli_stsb_pipeline_en_5.5.0_3.0_1725313694109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("southern_sotho_v3_test_mpnet_base_allnli_stsb_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("southern_sotho_v3_test_mpnet_base_allnli_stsb_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|southern_sotho_v3_test_mpnet_base_allnli_stsb_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|399.5 MB| + +## References + +https://huggingface.co/tomaarsen/st-v3-test-mpnet-base-allnli-stsb + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-spanberta_en.md b/docs/_posts/ahmedlone127/2024-09-02-spanberta_en.md new file mode 100644 index 00000000000000..fcee415503c8b0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-spanberta_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English spanberta RoBertaEmbeddings from chriskhanhtran +author: John Snow Labs +name: spanberta +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanberta` is a English model originally trained by chriskhanhtran. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanberta_en_5.5.0_3.0_1725265186626.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanberta_en_5.5.0_3.0_1725265186626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("spanberta","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("spanberta","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spanberta| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|463.8 MB| + +## References + +https://huggingface.co/chriskhanhtran/spanberta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-spanish_english_aligned_en.md b/docs/_posts/ahmedlone127/2024-09-02-spanish_english_aligned_en.md new file mode 100644 index 00000000000000..f898f35caae1f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-spanish_english_aligned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English spanish_english_aligned MarianTransformer from americasnlp-lct-ehu +author: John Snow Labs +name: spanish_english_aligned +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanish_english_aligned` is a English model originally trained by americasnlp-lct-ehu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanish_english_aligned_en_5.5.0_3.0_1725305267125.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanish_english_aligned_en_5.5.0_3.0_1725305267125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("spanish_english_aligned","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("spanish_english_aligned","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spanish_english_aligned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|539.2 MB| + +## References + +https://huggingface.co/americasnlp-lct-ehu/es_en_aligned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-spanish_english_aligned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-spanish_english_aligned_pipeline_en.md new file mode 100644 index 00000000000000..8895fe8bebb9f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-spanish_english_aligned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English spanish_english_aligned_pipeline pipeline MarianTransformer from americasnlp-lct-ehu +author: John Snow Labs +name: spanish_english_aligned_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanish_english_aligned_pipeline` is a English model originally trained by americasnlp-lct-ehu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanish_english_aligned_pipeline_en_5.5.0_3.0_1725305293980.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanish_english_aligned_pipeline_en_5.5.0_3.0_1725305293980.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("spanish_english_aligned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("spanish_english_aligned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spanish_english_aligned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|539.7 MB| + +## References + +https://huggingface.co/americasnlp-lct-ehu/es_en_aligned + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-spanish_english_extra_en.md b/docs/_posts/ahmedlone127/2024-09-02-spanish_english_extra_en.md new file mode 100644 index 00000000000000..2d29eabed343ea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-spanish_english_extra_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English spanish_english_extra MarianTransformer from americasnlp-lct-ehu +author: John Snow Labs +name: spanish_english_extra +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanish_english_extra` is a English model originally trained by americasnlp-lct-ehu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanish_english_extra_en_5.5.0_3.0_1725243034139.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanish_english_extra_en_5.5.0_3.0_1725243034139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("spanish_english_extra","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("spanish_english_extra","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spanish_english_extra| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|539.1 MB| + +## References + +https://huggingface.co/americasnlp-lct-ehu/es_en_extra \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-spanish_english_extra_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-spanish_english_extra_pipeline_en.md new file mode 100644 index 00000000000000..30ec10f741b11a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-spanish_english_extra_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English spanish_english_extra_pipeline pipeline MarianTransformer from americasnlp-lct-ehu +author: John Snow Labs +name: spanish_english_extra_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanish_english_extra_pipeline` is a English model originally trained by americasnlp-lct-ehu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanish_english_extra_pipeline_en_5.5.0_3.0_1725243067029.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanish_english_extra_pipeline_en_5.5.0_3.0_1725243067029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("spanish_english_extra_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("spanish_english_extra_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spanish_english_extra_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|539.7 MB| + +## References + +https://huggingface.co/americasnlp-lct-ehu/es_en_extra + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-spark_name_hindi_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-spark_name_hindi_tonga_tonga_islands_english_en.md new file mode 100644 index 00000000000000..1ea93f140bdaec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-spark_name_hindi_tonga_tonga_islands_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English spark_name_hindi_tonga_tonga_islands_english MarianTransformer from ihebaker10 +author: John Snow Labs +name: spark_name_hindi_tonga_tonga_islands_english +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spark_name_hindi_tonga_tonga_islands_english` is a English model originally trained by ihebaker10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spark_name_hindi_tonga_tonga_islands_english_en_5.5.0_3.0_1725295366359.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spark_name_hindi_tonga_tonga_islands_english_en_5.5.0_3.0_1725295366359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("spark_name_hindi_tonga_tonga_islands_english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("spark_name_hindi_tonga_tonga_islands_english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spark_name_hindi_tonga_tonga_islands_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|518.5 MB| + +## References + +https://huggingface.co/ihebaker10/spark-name-hi-to-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-spark_name_hindi_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-spark_name_hindi_tonga_tonga_islands_english_pipeline_en.md new file mode 100644 index 00000000000000..f547cd0050a439 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-spark_name_hindi_tonga_tonga_islands_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English spark_name_hindi_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from ihebaker10 +author: John Snow Labs +name: spark_name_hindi_tonga_tonga_islands_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spark_name_hindi_tonga_tonga_islands_english_pipeline` is a English model originally trained by ihebaker10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spark_name_hindi_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725295393308.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spark_name_hindi_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725295393308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("spark_name_hindi_tonga_tonga_islands_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("spark_name_hindi_tonga_tonga_islands_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spark_name_hindi_tonga_tonga_islands_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|519.0 MB| + +## References + +https://huggingface.co/ihebaker10/spark-name-hi-to-en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-spark_name_korean_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-spark_name_korean_tonga_tonga_islands_english_en.md new file mode 100644 index 00000000000000..e4eec9a842bfd7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-spark_name_korean_tonga_tonga_islands_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English spark_name_korean_tonga_tonga_islands_english MarianTransformer from ihebaker10 +author: John Snow Labs +name: spark_name_korean_tonga_tonga_islands_english +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spark_name_korean_tonga_tonga_islands_english` is a English model originally trained by ihebaker10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spark_name_korean_tonga_tonga_islands_english_en_5.5.0_3.0_1725303882222.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spark_name_korean_tonga_tonga_islands_english_en_5.5.0_3.0_1725303882222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("spark_name_korean_tonga_tonga_islands_english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("spark_name_korean_tonga_tonga_islands_english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spark_name_korean_tonga_tonga_islands_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|540.5 MB| + +## References + +https://huggingface.co/ihebaker10/spark-name-ko-to-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-spark_name_korean_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-spark_name_korean_tonga_tonga_islands_english_pipeline_en.md new file mode 100644 index 00000000000000..a04213659b7f31 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-spark_name_korean_tonga_tonga_islands_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English spark_name_korean_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from ihebaker10 +author: John Snow Labs +name: spark_name_korean_tonga_tonga_islands_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spark_name_korean_tonga_tonga_islands_english_pipeline` is a English model originally trained by ihebaker10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spark_name_korean_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725303913692.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spark_name_korean_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725303913692.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("spark_name_korean_tonga_tonga_islands_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("spark_name_korean_tonga_tonga_islands_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spark_name_korean_tonga_tonga_islands_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|541.1 MB| + +## References + +https://huggingface.co/ihebaker10/spark-name-ko-to-en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-squeezebert_finetuned_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-squeezebert_finetuned_squadv2_pipeline_en.md new file mode 100644 index 00000000000000..8b2c594eb0b9ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-squeezebert_finetuned_squadv2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English squeezebert_finetuned_squadv2_pipeline pipeline BertForQuestionAnswering from mrm8488 +author: John Snow Labs +name: squeezebert_finetuned_squadv2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`squeezebert_finetuned_squadv2_pipeline` is a English model originally trained by mrm8488. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/squeezebert_finetuned_squadv2_pipeline_en_5.5.0_3.0_1725312541226.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squeezebert_finetuned_squadv2_pipeline_en_5.5.0_3.0_1725312541226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("squeezebert_finetuned_squadv2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("squeezebert_finetuned_squadv2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|squeezebert_finetuned_squadv2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|186.4 MB| + +## References + +https://huggingface.co/mrm8488/squeezebert-finetuned-squadv2 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-srtk_scorer_en.md b/docs/_posts/ahmedlone127/2024-09-02-srtk_scorer_en.md new file mode 100644 index 00000000000000..b87be149589f1c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-srtk_scorer_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English srtk_scorer RoBertaEmbeddings from drt +author: John Snow Labs +name: srtk_scorer +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`srtk_scorer` is a English model originally trained by drt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/srtk_scorer_en_5.5.0_3.0_1725264887873.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/srtk_scorer_en_5.5.0_3.0_1725264887873.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("srtk_scorer","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("srtk_scorer","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|srtk_scorer| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|433.4 MB| + +## References + +https://huggingface.co/drt/srtk-scorer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-srtk_scorer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-srtk_scorer_pipeline_en.md new file mode 100644 index 00000000000000..256e5357977d98 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-srtk_scorer_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English srtk_scorer_pipeline pipeline RoBertaEmbeddings from drt +author: John Snow Labs +name: srtk_scorer_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`srtk_scorer_pipeline` is a English model originally trained by drt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/srtk_scorer_pipeline_en_5.5.0_3.0_1725264928686.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/srtk_scorer_pipeline_en_5.5.0_3.0_1725264928686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("srtk_scorer_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("srtk_scorer_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|srtk_scorer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|433.4 MB| + +## References + +https://huggingface.co/drt/srtk-scorer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-storieslm_v1_1963_en.md b/docs/_posts/ahmedlone127/2024-09-02-storieslm_v1_1963_en.md new file mode 100644 index 00000000000000..f4ef9f45696f57 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-storieslm_v1_1963_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English storieslm_v1_1963 BertEmbeddings from StoriesLM +author: John Snow Labs +name: storieslm_v1_1963 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`storieslm_v1_1963` is a English model originally trained by StoriesLM. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/storieslm_v1_1963_en_5.5.0_3.0_1725319088771.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/storieslm_v1_1963_en_5.5.0_3.0_1725319088771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = BertEmbeddings.pretrained("storieslm_v1_1963","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("storieslm_v1_1963","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|storieslm_v1_1963| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|en| +|Size:|408.1 MB| + +## References + +https://huggingface.co/StoriesLM/StoriesLM-v1-1963 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-storieslm_v1_1963_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-storieslm_v1_1963_pipeline_en.md new file mode 100644 index 00000000000000..54c4a84083910d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-storieslm_v1_1963_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English storieslm_v1_1963_pipeline pipeline BertEmbeddings from StoriesLM +author: John Snow Labs +name: storieslm_v1_1963_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`storieslm_v1_1963_pipeline` is a English model originally trained by StoriesLM. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/storieslm_v1_1963_pipeline_en_5.5.0_3.0_1725319108800.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/storieslm_v1_1963_pipeline_en_5.5.0_3.0_1725319108800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("storieslm_v1_1963_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("storieslm_v1_1963_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|storieslm_v1_1963_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.1 MB| + +## References + +https://huggingface.co/StoriesLM/StoriesLM-v1-1963 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-storyseeker_en.md b/docs/_posts/ahmedlone127/2024-09-02-storyseeker_en.md new file mode 100644 index 00000000000000..d12a248bd6e92e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-storyseeker_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English storyseeker RoBertaForSequenceClassification from mariaantoniak +author: John Snow Labs +name: storyseeker +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`storyseeker` is a English model originally trained by mariaantoniak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/storyseeker_en_5.5.0_3.0_1725277765209.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/storyseeker_en_5.5.0_3.0_1725277765209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("storyseeker","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("storyseeker", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|storyseeker| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|437.3 MB| + +## References + +https://huggingface.co/mariaantoniak/storyseeker \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-storyseeker_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-storyseeker_pipeline_en.md new file mode 100644 index 00000000000000..cb628ac2c124ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-storyseeker_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English storyseeker_pipeline pipeline RoBertaForSequenceClassification from mariaantoniak +author: John Snow Labs +name: storyseeker_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`storyseeker_pipeline` is a English model originally trained by mariaantoniak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/storyseeker_pipeline_en_5.5.0_3.0_1725277795477.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/storyseeker_pipeline_en_5.5.0_3.0_1725277795477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("storyseeker_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("storyseeker_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|storyseeker_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|437.3 MB| + +## References + +https://huggingface.co/mariaantoniak/storyseeker + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-streetclip_en.md b/docs/_posts/ahmedlone127/2024-09-02-streetclip_en.md new file mode 100644 index 00000000000000..45ac24d4d95038 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-streetclip_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English streetclip CLIPForZeroShotClassification from geolocal +author: John Snow Labs +name: streetclip +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`streetclip` is a English model originally trained by geolocal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/streetclip_en_5.5.0_3.0_1725275905431.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/streetclip_en_5.5.0_3.0_1725275905431.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("streetclip","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("streetclip","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|streetclip| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/geolocal/StreetCLIP \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-streetclip_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-streetclip_pipeline_en.md new file mode 100644 index 00000000000000..4d1de03baf39c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-streetclip_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English streetclip_pipeline pipeline CLIPForZeroShotClassification from geolocal +author: John Snow Labs +name: streetclip_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`streetclip_pipeline` is a English model originally trained by geolocal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/streetclip_pipeline_en_5.5.0_3.0_1725275986104.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/streetclip_pipeline_en_5.5.0_3.0_1725275986104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("streetclip_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("streetclip_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|streetclip_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/geolocal/StreetCLIP + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-stress_prediction_en.md b/docs/_posts/ahmedlone127/2024-09-02-stress_prediction_en.md new file mode 100644 index 00000000000000..831a39776e0a68 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-stress_prediction_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English stress_prediction DistilBertForSequenceClassification from alibidaran +author: John Snow Labs +name: stress_prediction +date: 2024-09-02 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stress_prediction` is a English model originally trained by alibidaran. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stress_prediction_en_5.5.0_3.0_1725292135247.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stress_prediction_en_5.5.0_3.0_1725292135247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("stress_prediction","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("stress_prediction","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|stress_prediction| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +References + +https://huggingface.co/alibidaran/stress_prediction \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-stsb_tinybert_l_4_finetuned_auc_151221_top3_en.md b/docs/_posts/ahmedlone127/2024-09-02-stsb_tinybert_l_4_finetuned_auc_151221_top3_en.md new file mode 100644 index 00000000000000..de1b66aca8c1e4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-stsb_tinybert_l_4_finetuned_auc_151221_top3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English stsb_tinybert_l_4_finetuned_auc_151221_top3 BertForSequenceClassification from Katsiaryna +author: John Snow Labs +name: stsb_tinybert_l_4_finetuned_auc_151221_top3 +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stsb_tinybert_l_4_finetuned_auc_151221_top3` is a English model originally trained by Katsiaryna. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stsb_tinybert_l_4_finetuned_auc_151221_top3_en_5.5.0_3.0_1725293730881.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stsb_tinybert_l_4_finetuned_auc_151221_top3_en_5.5.0_3.0_1725293730881.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = BertForSequenceClassification.pretrained("stsb_tinybert_l_4_finetuned_auc_151221_top3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("stsb_tinybert_l_4_finetuned_auc_151221_top3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|stsb_tinybert_l_4_finetuned_auc_151221_top3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Katsiaryna/stsb-TinyBERT-L-4-finetuned_auc_151221-top3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sumathi_camembert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sumathi_camembert_pipeline_en.md new file mode 100644 index 00000000000000..a572f4765a4fad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sumathi_camembert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sumathi_camembert_pipeline pipeline CamemBertEmbeddings from SumathiS +author: John Snow Labs +name: sumathi_camembert_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sumathi_camembert_pipeline` is a English model originally trained by SumathiS. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sumathi_camembert_pipeline_en_5.5.0_3.0_1725300195742.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sumathi_camembert_pipeline_en_5.5.0_3.0_1725300195742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sumathi_camembert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sumathi_camembert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sumathi_camembert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/SumathiS/sumathi_camembert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sunbird_english_multiple_languages_en.md b/docs/_posts/ahmedlone127/2024-09-02-sunbird_english_multiple_languages_en.md new file mode 100644 index 00000000000000..857f1bda392a49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sunbird_english_multiple_languages_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sunbird_english_multiple_languages MarianTransformer from Sunbird +author: John Snow Labs +name: sunbird_english_multiple_languages +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sunbird_english_multiple_languages` is a English model originally trained by Sunbird. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sunbird_english_multiple_languages_en_5.5.0_3.0_1725243894948.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sunbird_english_multiple_languages_en_5.5.0_3.0_1725243894948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("sunbird_english_multiple_languages","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("sunbird_english_multiple_languages","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sunbird_english_multiple_languages| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|529.9 MB| + +## References + +https://huggingface.co/Sunbird/sunbird-en-mul \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sunbird_english_multiple_languages_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sunbird_english_multiple_languages_pipeline_en.md new file mode 100644 index 00000000000000..afd6154f7ebb53 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sunbird_english_multiple_languages_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sunbird_english_multiple_languages_pipeline pipeline MarianTransformer from Sunbird +author: John Snow Labs +name: sunbird_english_multiple_languages_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sunbird_english_multiple_languages_pipeline` is a English model originally trained by Sunbird. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sunbird_english_multiple_languages_pipeline_en_5.5.0_3.0_1725243932632.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sunbird_english_multiple_languages_pipeline_en_5.5.0_3.0_1725243932632.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sunbird_english_multiple_languages_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sunbird_english_multiple_languages_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sunbird_english_multiple_languages_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|530.4 MB| + +## References + +https://huggingface.co/Sunbird/sunbird-en-mul + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sungbeom_whisper_small_korean_set54_ko.md b/docs/_posts/ahmedlone127/2024-09-02-sungbeom_whisper_small_korean_set54_ko.md new file mode 100644 index 00000000000000..192cca907d8690 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sungbeom_whisper_small_korean_set54_ko.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Korean sungbeom_whisper_small_korean_set54 WhisperForCTC from maxseats +author: John Snow Labs +name: sungbeom_whisper_small_korean_set54 +date: 2024-09-02 +tags: [ko, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: ko +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sungbeom_whisper_small_korean_set54` is a Korean model originally trained by maxseats. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sungbeom_whisper_small_korean_set54_ko_5.5.0_3.0_1725286212629.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sungbeom_whisper_small_korean_set54_ko_5.5.0_3.0_1725286212629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("sungbeom_whisper_small_korean_set54","ko") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("sungbeom_whisper_small_korean_set54", "ko") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sungbeom_whisper_small_korean_set54| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ko| +|Size:|1.7 GB| + +## References + +https://huggingface.co/maxseats/SungBeom-whisper-small-ko-set54 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-sungbeom_whisper_small_korean_set54_pipeline_ko.md b/docs/_posts/ahmedlone127/2024-09-02-sungbeom_whisper_small_korean_set54_pipeline_ko.md new file mode 100644 index 00000000000000..540538f8041cfb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-sungbeom_whisper_small_korean_set54_pipeline_ko.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Korean sungbeom_whisper_small_korean_set54_pipeline pipeline WhisperForCTC from maxseats +author: John Snow Labs +name: sungbeom_whisper_small_korean_set54_pipeline +date: 2024-09-02 +tags: [ko, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ko +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sungbeom_whisper_small_korean_set54_pipeline` is a Korean model originally trained by maxseats. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sungbeom_whisper_small_korean_set54_pipeline_ko_5.5.0_3.0_1725286303558.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sungbeom_whisper_small_korean_set54_pipeline_ko_5.5.0_3.0_1725286303558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sungbeom_whisper_small_korean_set54_pipeline", lang = "ko") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sungbeom_whisper_small_korean_set54_pipeline", lang = "ko") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sungbeom_whisper_small_korean_set54_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ko| +|Size:|1.7 GB| + +## References + +https://huggingface.co/maxseats/SungBeom-whisper-small-ko-set54 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-syntrans_spanish_english_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-syntrans_spanish_english_v2_pipeline_en.md new file mode 100644 index 00000000000000..e97c8803664999 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-syntrans_spanish_english_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English syntrans_spanish_english_v2_pipeline pipeline MarianTransformer from lkoppens +author: John Snow Labs +name: syntrans_spanish_english_v2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`syntrans_spanish_english_v2_pipeline` is a English model originally trained by lkoppens. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/syntrans_spanish_english_v2_pipeline_en_5.5.0_3.0_1725295674722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/syntrans_spanish_english_v2_pipeline_en_5.5.0_3.0_1725295674722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("syntrans_spanish_english_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("syntrans_spanish_english_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|syntrans_spanish_english_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|539.9 MB| + +## References + +https://huggingface.co/lkoppens/syntrans-es-en-v2 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-t5_small_finetuned_german_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-t5_small_finetuned_german_tonga_tonga_islands_english_en.md new file mode 100644 index 00000000000000..6efa3095ffa99d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-t5_small_finetuned_german_tonga_tonga_islands_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English t5_small_finetuned_german_tonga_tonga_islands_english MarianTransformer from AMNS4000 +author: John Snow Labs +name: t5_small_finetuned_german_tonga_tonga_islands_english +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_german_tonga_tonga_islands_english` is a English model originally trained by AMNS4000. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_german_tonga_tonga_islands_english_en_5.5.0_3.0_1725243867509.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_german_tonga_tonga_islands_english_en_5.5.0_3.0_1725243867509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("t5_small_finetuned_german_tonga_tonga_islands_english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("t5_small_finetuned_german_tonga_tonga_islands_english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|t5_small_finetuned_german_tonga_tonga_islands_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|498.9 MB| + +## References + +https://huggingface.co/AMNS4000/t5_small-finetuned-de-to-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-t5_small_finetuned_german_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-t5_small_finetuned_german_tonga_tonga_islands_english_pipeline_en.md new file mode 100644 index 00000000000000..52ba73f7ff4017 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-t5_small_finetuned_german_tonga_tonga_islands_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English t5_small_finetuned_german_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from AMNS4000 +author: John Snow Labs +name: t5_small_finetuned_german_tonga_tonga_islands_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_german_tonga_tonga_islands_english_pipeline` is a English model originally trained by AMNS4000. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_german_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725243898854.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_german_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725243898854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("t5_small_finetuned_german_tonga_tonga_islands_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("t5_small_finetuned_german_tonga_tonga_islands_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|t5_small_finetuned_german_tonga_tonga_islands_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|499.4 MB| + +## References + +https://huggingface.co/AMNS4000/t5_small-finetuned-de-to-en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-tabletop_v_1_0_en.md b/docs/_posts/ahmedlone127/2024-09-02-tabletop_v_1_0_en.md new file mode 100644 index 00000000000000..b6d1a6a49e41a1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-tabletop_v_1_0_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English tabletop_v_1_0 CLIPForZeroShotClassification from orionai +author: John Snow Labs +name: tabletop_v_1_0 +date: 2024-09-02 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tabletop_v_1_0` is a English model originally trained by orionai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tabletop_v_1_0_en_5.5.0_3.0_1725276326712.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tabletop_v_1_0_en_5.5.0_3.0_1725276326712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("tabletop_v_1_0","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("tabletop_v_1_0","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tabletop_v_1_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/orionai/tabletop-v.1.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-tabletop_v_1_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-tabletop_v_1_0_pipeline_en.md new file mode 100644 index 00000000000000..a80c17815bfbeb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-tabletop_v_1_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English tabletop_v_1_0_pipeline pipeline CLIPForZeroShotClassification from orionai +author: John Snow Labs +name: tabletop_v_1_0_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tabletop_v_1_0_pipeline` is a English model originally trained by orionai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tabletop_v_1_0_pipeline_en_5.5.0_3.0_1725276357870.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tabletop_v_1_0_pipeline_en_5.5.0_3.0_1725276357870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tabletop_v_1_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tabletop_v_1_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tabletop_v_1_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/orionai/tabletop-v.1.0 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-taiwanese_whisper_ericchang_en.md b/docs/_posts/ahmedlone127/2024-09-02-taiwanese_whisper_ericchang_en.md new file mode 100644 index 00000000000000..9c7b99993000d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-taiwanese_whisper_ericchang_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English taiwanese_whisper_ericchang WhisperForCTC from EricChang +author: John Snow Labs +name: taiwanese_whisper_ericchang +date: 2024-09-02 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`taiwanese_whisper_ericchang` is a English model originally trained by EricChang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/taiwanese_whisper_ericchang_en_5.5.0_3.0_1725245620326.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/taiwanese_whisper_ericchang_en_5.5.0_3.0_1725245620326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("taiwanese_whisper_ericchang","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("taiwanese_whisper_ericchang", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|taiwanese_whisper_ericchang| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/EricChang/Taiwanese-Whisper \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-taiwanese_whisper_ericchang_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-taiwanese_whisper_ericchang_pipeline_en.md new file mode 100644 index 00000000000000..72426b643baa26 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-taiwanese_whisper_ericchang_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English taiwanese_whisper_ericchang_pipeline pipeline WhisperForCTC from EricChang +author: John Snow Labs +name: taiwanese_whisper_ericchang_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`taiwanese_whisper_ericchang_pipeline` is a English model originally trained by EricChang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/taiwanese_whisper_ericchang_pipeline_en_5.5.0_3.0_1725245710285.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/taiwanese_whisper_ericchang_pipeline_en_5.5.0_3.0_1725245710285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("taiwanese_whisper_ericchang_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("taiwanese_whisper_ericchang_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|taiwanese_whisper_ericchang_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/EricChang/Taiwanese-Whisper + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-task_subtle_task__model_deberta__aug_method_austroasiatic_languages_en.md b/docs/_posts/ahmedlone127/2024-09-02-task_subtle_task__model_deberta__aug_method_austroasiatic_languages_en.md new file mode 100644 index 00000000000000..67040846ac9722 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-task_subtle_task__model_deberta__aug_method_austroasiatic_languages_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English task_subtle_task__model_deberta__aug_method_austroasiatic_languages DeBertaForSequenceClassification from BenjaminOcampo +author: John Snow Labs +name: task_subtle_task__model_deberta__aug_method_austroasiatic_languages +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, deberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_subtle_task__model_deberta__aug_method_austroasiatic_languages` is a English model originally trained by BenjaminOcampo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_deberta__aug_method_austroasiatic_languages_en_5.5.0_3.0_1725281601378.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_deberta__aug_method_austroasiatic_languages_en_5.5.0_3.0_1725281601378.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DeBertaForSequenceClassification.pretrained("task_subtle_task__model_deberta__aug_method_austroasiatic_languages","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DeBertaForSequenceClassification.pretrained("task_subtle_task__model_deberta__aug_method_austroasiatic_languages", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|task_subtle_task__model_deberta__aug_method_austroasiatic_languages| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|607.4 MB| + +## References + +https://huggingface.co/BenjaminOcampo/task-subtle_task__model-deberta__aug_method-aav \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-tatar_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-tatar_pipeline_en.md new file mode 100644 index 00000000000000..8be32e161d70cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-tatar_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tatar_pipeline pipeline MarianTransformer from baobuiquang +author: John Snow Labs +name: tatar_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tatar_pipeline` is a English model originally trained by baobuiquang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tatar_pipeline_en_5.5.0_3.0_1725294683645.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tatar_pipeline_en_5.5.0_3.0_1725294683645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tatar_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tatar_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tatar_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|476.2 MB| + +## References + +https://huggingface.co/baobuiquang/TT + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-temp_checkpoints_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-temp_checkpoints_pipeline_en.md new file mode 100644 index 00000000000000..1320a9bcabd335 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-temp_checkpoints_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English temp_checkpoints_pipeline pipeline DistilBertForSequenceClassification from FilippoLampa +author: John Snow Labs +name: temp_checkpoints_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`temp_checkpoints_pipeline` is a English model originally trained by FilippoLampa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/temp_checkpoints_pipeline_en_5.5.0_3.0_1725306310082.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/temp_checkpoints_pipeline_en_5.5.0_3.0_1725306310082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("temp_checkpoints_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("temp_checkpoints_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|temp_checkpoints_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/FilippoLampa/temp_checkpoints + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-test_1_en.md b/docs/_posts/ahmedlone127/2024-09-02-test_1_en.md new file mode 100644 index 00000000000000..a5a10fcf807229 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-test_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English test_1 CamemBertEmbeddings from Sophon +author: John Snow Labs +name: test_1 +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_1` is a English model originally trained by Sophon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_1_en_5.5.0_3.0_1725300975382.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_1_en_5.5.0_3.0_1725300975382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("test_1","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("test_1","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Sophon/test-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-test_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-test_1_pipeline_en.md new file mode 100644 index 00000000000000..ac012c78b4647c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-test_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English test_1_pipeline pipeline CamemBertEmbeddings from Sophon +author: John Snow Labs +name: test_1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_1_pipeline` is a English model originally trained by Sophon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_1_pipeline_en_5.5.0_3.0_1725301050330.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_1_pipeline_en_5.5.0_3.0_1725301050330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("test_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("test_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Sophon/test-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-test_model_hasanmurad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-test_model_hasanmurad_pipeline_en.md new file mode 100644 index 00000000000000..5d65b686119f83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-test_model_hasanmurad_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English test_model_hasanmurad_pipeline pipeline CamemBertEmbeddings from Hasanmurad +author: John Snow Labs +name: test_model_hasanmurad_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_hasanmurad_pipeline` is a English model originally trained by Hasanmurad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model_hasanmurad_pipeline_en_5.5.0_3.0_1725302298458.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_hasanmurad_pipeline_en_5.5.0_3.0_1725302298458.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("test_model_hasanmurad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("test_model_hasanmurad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_model_hasanmurad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Hasanmurad/test-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-testhelsinkimulenjpth02_en.md b/docs/_posts/ahmedlone127/2024-09-02-testhelsinkimulenjpth02_en.md new file mode 100644 index 00000000000000..a1a5ec8c86b464 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-testhelsinkimulenjpth02_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English testhelsinkimulenjpth02 MarianTransformer from Shularp +author: John Snow Labs +name: testhelsinkimulenjpth02 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testhelsinkimulenjpth02` is a English model originally trained by Shularp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testhelsinkimulenjpth02_en_5.5.0_3.0_1725295832512.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testhelsinkimulenjpth02_en_5.5.0_3.0_1725295832512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("testhelsinkimulenjpth02","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("testhelsinkimulenjpth02","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|testhelsinkimulenjpth02| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|530.1 MB| + +## References + +https://huggingface.co/Shularp/TestHelsinkimulEnJpTh02 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-text_classification_model_multilingual_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-text_classification_model_multilingual_pipeline_xx.md new file mode 100644 index 00000000000000..3bbcc5e74fc49e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-text_classification_model_multilingual_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual text_classification_model_multilingual_pipeline pipeline DistilBertForSequenceClassification from cwchang +author: John Snow Labs +name: text_classification_model_multilingual_pipeline +date: 2024-09-02 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_classification_model_multilingual_pipeline` is a Multilingual model originally trained by cwchang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_classification_model_multilingual_pipeline_xx_5.5.0_3.0_1725305778232.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_classification_model_multilingual_pipeline_xx_5.5.0_3.0_1725305778232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("text_classification_model_multilingual_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("text_classification_model_multilingual_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|text_classification_model_multilingual_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|508.1 MB| + +## References + +https://huggingface.co/cwchang/text-classification-model-multilingual + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-tiny_random_albertforquestionanswering_en.md b/docs/_posts/ahmedlone127/2024-09-02-tiny_random_albertforquestionanswering_en.md new file mode 100644 index 00000000000000..ea19a21dd9b73a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-tiny_random_albertforquestionanswering_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English tiny_random_albertforquestionanswering AlbertForQuestionAnswering from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_albertforquestionanswering +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_albertforquestionanswering` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_albertforquestionanswering_en_5.5.0_3.0_1725310010438.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_albertforquestionanswering_en_5.5.0_3.0_1725310010438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("tiny_random_albertforquestionanswering","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("tiny_random_albertforquestionanswering", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_albertforquestionanswering| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|15.2 MB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-tiny_random_albertforquestionanswering_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-tiny_random_albertforquestionanswering_pipeline_en.md new file mode 100644 index 00000000000000..59aef92bbe2dd3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-tiny_random_albertforquestionanswering_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English tiny_random_albertforquestionanswering_pipeline pipeline AlbertForQuestionAnswering from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_albertforquestionanswering_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_albertforquestionanswering_pipeline` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_albertforquestionanswering_pipeline_en_5.5.0_3.0_1725310011572.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_albertforquestionanswering_pipeline_en_5.5.0_3.0_1725310011572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tiny_random_albertforquestionanswering_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tiny_random_albertforquestionanswering_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_albertforquestionanswering_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|15.2 MB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-AlbertForQuestionAnswering + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-tiny_random_albertforsequenceclassification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-tiny_random_albertforsequenceclassification_pipeline_en.md new file mode 100644 index 00000000000000..2d85c609df6c4f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-tiny_random_albertforsequenceclassification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tiny_random_albertforsequenceclassification_pipeline pipeline AlbertForSequenceClassification from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_albertforsequenceclassification_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_albertforsequenceclassification_pipeline` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_albertforsequenceclassification_pipeline_en_5.5.0_3.0_1725301746458.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_albertforsequenceclassification_pipeline_en_5.5.0_3.0_1725301746458.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tiny_random_albertforsequenceclassification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tiny_random_albertforsequenceclassification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_albertforsequenceclassification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|15.2 MB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-AlbertForSequenceClassification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-tiny_random_clipmodel_hf_tiny_model_private_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-tiny_random_clipmodel_hf_tiny_model_private_pipeline_en.md new file mode 100644 index 00000000000000..8ca2406e412ced --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-tiny_random_clipmodel_hf_tiny_model_private_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English tiny_random_clipmodel_hf_tiny_model_private_pipeline pipeline CLIPForZeroShotClassification from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_clipmodel_hf_tiny_model_private_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_clipmodel_hf_tiny_model_private_pipeline` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_clipmodel_hf_tiny_model_private_pipeline_en_5.5.0_3.0_1725275826071.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_clipmodel_hf_tiny_model_private_pipeline_en_5.5.0_3.0_1725275826071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tiny_random_clipmodel_hf_tiny_model_private_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tiny_random_clipmodel_hf_tiny_model_private_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_clipmodel_hf_tiny_model_private_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|547.0 KB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-CLIPModel + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-traduttore_italian_english_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-traduttore_italian_english_2_pipeline_en.md new file mode 100644 index 00000000000000..46cf5c10bff6b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-traduttore_italian_english_2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English traduttore_italian_english_2_pipeline pipeline MarianTransformer from zaneas +author: John Snow Labs +name: traduttore_italian_english_2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`traduttore_italian_english_2_pipeline` is a English model originally trained by zaneas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/traduttore_italian_english_2_pipeline_en_5.5.0_3.0_1725294747537.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/traduttore_italian_english_2_pipeline_en_5.5.0_3.0_1725294747537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("traduttore_italian_english_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("traduttore_italian_english_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|traduttore_italian_english_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|625.6 MB| + +## References + +https://huggingface.co/zaneas/Traduttore_IT_EN_2 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-traffy_problem_predict_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-traffy_problem_predict_pipeline_en.md new file mode 100644 index 00000000000000..8332643f6ee5e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-traffy_problem_predict_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English traffy_problem_predict_pipeline pipeline CamemBertForSequenceClassification from nlp-chula +author: John Snow Labs +name: traffy_problem_predict_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`traffy_problem_predict_pipeline` is a English model originally trained by nlp-chula. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/traffy_problem_predict_pipeline_en_5.5.0_3.0_1725299220020.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/traffy_problem_predict_pipeline_en_5.5.0_3.0_1725299220020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("traffy_problem_predict_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("traffy_problem_predict_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|traffy_problem_predict_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/nlp-chula/traffy-problem-predict + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-trainingarg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-trainingarg_pipeline_en.md new file mode 100644 index 00000000000000..f86a620d676cb1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-trainingarg_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English trainingarg_pipeline pipeline DistilBertForSequenceClassification from PiotrNaspinski +author: John Snow Labs +name: trainingarg_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trainingarg_pipeline` is a English model originally trained by PiotrNaspinski. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trainingarg_pipeline_en_5.5.0_3.0_1725292295690.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trainingarg_pipeline_en_5.5.0_3.0_1725292295690.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("trainingarg_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("trainingarg_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|trainingarg_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/PiotrNaspinski/TrainingArg + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-transformer_english_russian_anonumous_en.md b/docs/_posts/ahmedlone127/2024-09-02-transformer_english_russian_anonumous_en.md new file mode 100644 index 00000000000000..d7e0bd65d25833 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-transformer_english_russian_anonumous_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English transformer_english_russian_anonumous MarianTransformer from Anonumous +author: John Snow Labs +name: transformer_english_russian_anonumous +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`transformer_english_russian_anonumous` is a English model originally trained by Anonumous. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/transformer_english_russian_anonumous_en_5.5.0_3.0_1725295040090.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/transformer_english_russian_anonumous_en_5.5.0_3.0_1725295040090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("transformer_english_russian_anonumous","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("transformer_english_russian_anonumous","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|transformer_english_russian_anonumous| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|525.4 MB| + +## References + +https://huggingface.co/Anonumous/transformer-en-ru \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-transformer_english_russian_anonumous_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-transformer_english_russian_anonumous_pipeline_en.md new file mode 100644 index 00000000000000..f481b8b8a593cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-transformer_english_russian_anonumous_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English transformer_english_russian_anonumous_pipeline pipeline MarianTransformer from Anonumous +author: John Snow Labs +name: transformer_english_russian_anonumous_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`transformer_english_russian_anonumous_pipeline` is a English model originally trained by Anonumous. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/transformer_english_russian_anonumous_pipeline_en_5.5.0_3.0_1725295068533.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/transformer_english_russian_anonumous_pipeline_en_5.5.0_3.0_1725295068533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("transformer_english_russian_anonumous_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("transformer_english_russian_anonumous_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|transformer_english_russian_anonumous_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|525.9 MB| + +## References + +https://huggingface.co/Anonumous/transformer-en-ru + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-translate_model_v3_1_en.md b/docs/_posts/ahmedlone127/2024-09-02-translate_model_v3_1_en.md new file mode 100644 index 00000000000000..27158eea09ba51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-translate_model_v3_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English translate_model_v3_1 MarianTransformer from gshields +author: John Snow Labs +name: translate_model_v3_1 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translate_model_v3_1` is a English model originally trained by gshields. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translate_model_v3_1_en_5.5.0_3.0_1725303678768.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translate_model_v3_1_en_5.5.0_3.0_1725303678768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("translate_model_v3_1","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("translate_model_v3_1","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|translate_model_v3_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|523.0 MB| + +## References + +https://huggingface.co/gshields/translate_model_v3.1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-translation_en2zh_en.md b/docs/_posts/ahmedlone127/2024-09-02-translation_en2zh_en.md new file mode 100644 index 00000000000000..481b527a34d597 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-translation_en2zh_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English translation_en2zh MarianTransformer from Jyshen +author: John Snow Labs +name: translation_en2zh +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_en2zh` is a English model originally trained by Jyshen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_en2zh_en_5.5.0_3.0_1725295014466.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_en2zh_en_5.5.0_3.0_1725295014466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("translation_en2zh","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("translation_en2zh","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|translation_en2zh| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|541.0 MB| + +## References + +https://huggingface.co/Jyshen/Translation_en2zh \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-translation_en2zh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-translation_en2zh_pipeline_en.md new file mode 100644 index 00000000000000..8f40faaf778f4a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-translation_en2zh_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English translation_en2zh_pipeline pipeline MarianTransformer from Jyshen +author: John Snow Labs +name: translation_en2zh_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_en2zh_pipeline` is a English model originally trained by Jyshen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_en2zh_pipeline_en_5.5.0_3.0_1725295046587.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_en2zh_pipeline_en_5.5.0_3.0_1725295046587.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("translation_en2zh_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("translation_en2zh_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|translation_en2zh_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|541.6 MB| + +## References + +https://huggingface.co/Jyshen/Translation_en2zh + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-translation_english_lug_v6_en.md b/docs/_posts/ahmedlone127/2024-09-02-translation_english_lug_v6_en.md new file mode 100644 index 00000000000000..83d8e7de32b486 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-translation_english_lug_v6_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English translation_english_lug_v6 MarianTransformer from atwine +author: John Snow Labs +name: translation_english_lug_v6 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_english_lug_v6` is a English model originally trained by atwine. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_english_lug_v6_en_5.5.0_3.0_1725303923025.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_english_lug_v6_en_5.5.0_3.0_1725303923025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("translation_english_lug_v6","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("translation_english_lug_v6","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|translation_english_lug_v6| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|514.5 MB| + +## References + +https://huggingface.co/atwine/translation-en-lug-v6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-translation_english_vietnamese_official_en.md b/docs/_posts/ahmedlone127/2024-09-02-translation_english_vietnamese_official_en.md new file mode 100644 index 00000000000000..1b87206dd0ac12 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-translation_english_vietnamese_official_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English translation_english_vietnamese_official MarianTransformer from NguyenManhAI +author: John Snow Labs +name: translation_english_vietnamese_official +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_english_vietnamese_official` is a English model originally trained by NguyenManhAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_english_vietnamese_official_en_5.5.0_3.0_1725295779635.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_english_vietnamese_official_en_5.5.0_3.0_1725295779635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("translation_english_vietnamese_official","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("translation_english_vietnamese_official","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|translation_english_vietnamese_official| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|474.9 MB| + +## References + +https://huggingface.co/NguyenManhAI/translation-en-vi-official \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-translation_english_vietnamese_official_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-translation_english_vietnamese_official_pipeline_en.md new file mode 100644 index 00000000000000..0a1ec4b74d5afe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-translation_english_vietnamese_official_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English translation_english_vietnamese_official_pipeline pipeline MarianTransformer from NguyenManhAI +author: John Snow Labs +name: translation_english_vietnamese_official_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_english_vietnamese_official_pipeline` is a English model originally trained by NguyenManhAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_english_vietnamese_official_pipeline_en_5.5.0_3.0_1725295804791.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_english_vietnamese_official_pipeline_en_5.5.0_3.0_1725295804791.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("translation_english_vietnamese_official_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("translation_english_vietnamese_official_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|translation_english_vietnamese_official_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|475.5 MB| + +## References + +https://huggingface.co/NguyenManhAI/translation-en-vi-official + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-triple_20e_1000_fit_all_mpnet_base_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-triple_20e_1000_fit_all_mpnet_base_v2_pipeline_en.md new file mode 100644 index 00000000000000..019cbdee8ac43a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-triple_20e_1000_fit_all_mpnet_base_v2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English triple_20e_1000_fit_all_mpnet_base_v2_pipeline pipeline MPNetEmbeddings from satyroffrost +author: John Snow Labs +name: triple_20e_1000_fit_all_mpnet_base_v2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`triple_20e_1000_fit_all_mpnet_base_v2_pipeline` is a English model originally trained by satyroffrost. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/triple_20e_1000_fit_all_mpnet_base_v2_pipeline_en_5.5.0_3.0_1725313564635.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/triple_20e_1000_fit_all_mpnet_base_v2_pipeline_en_5.5.0_3.0_1725313564635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("triple_20e_1000_fit_all_mpnet_base_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("triple_20e_1000_fit_all_mpnet_base_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|triple_20e_1000_fit_all_mpnet_base_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/satyroffrost/triple-20e-1000-fit-all-mpnet-base-v2 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-turkish2_en.md b/docs/_posts/ahmedlone127/2024-09-02-turkish2_en.md new file mode 100644 index 00000000000000..945f83177b4a39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-turkish2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English turkish2 MarianTransformer from PontifexMaximus +author: John Snow Labs +name: turkish2 +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish2` is a English model originally trained by PontifexMaximus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish2_en_5.5.0_3.0_1725243475533.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish2_en_5.5.0_3.0_1725243475533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("turkish2","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("turkish2","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkish2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|525.3 MB| + +## References + +https://huggingface.co/PontifexMaximus/Turkish2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-ukr_roberta_base_uk.md b/docs/_posts/ahmedlone127/2024-09-02-ukr_roberta_base_uk.md new file mode 100644 index 00000000000000..10a18e1a25754d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-ukr_roberta_base_uk.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Ukrainian ukr_roberta_base RoBertaEmbeddings from youscan +author: John Snow Labs +name: ukr_roberta_base +date: 2024-09-02 +tags: [uk, open_source, onnx, embeddings, roberta] +task: Embeddings +language: uk +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ukr_roberta_base` is a Ukrainian model originally trained by youscan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ukr_roberta_base_uk_5.5.0_3.0_1725264732723.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ukr_roberta_base_uk_5.5.0_3.0_1725264732723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = RoBertaEmbeddings.pretrained("ukr_roberta_base","uk") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("ukr_roberta_base","uk") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ukr_roberta_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|uk| +|Size:|471.3 MB| + +## References + +https://huggingface.co/youscan/ukr-roberta-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-umberto_commoncrawl_cased_v1_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-02-umberto_commoncrawl_cased_v1_pipeline_it.md new file mode 100644 index 00000000000000..d24c4b9f5b98ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-umberto_commoncrawl_cased_v1_pipeline_it.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Italian umberto_commoncrawl_cased_v1_pipeline pipeline CamemBertEmbeddings from Musixmatch +author: John Snow Labs +name: umberto_commoncrawl_cased_v1_pipeline +date: 2024-09-02 +tags: [it, open_source, pipeline, onnx] +task: Embeddings +language: it +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`umberto_commoncrawl_cased_v1_pipeline` is a Italian model originally trained by Musixmatch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/umberto_commoncrawl_cased_v1_pipeline_it_5.5.0_3.0_1725319873505.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/umberto_commoncrawl_cased_v1_pipeline_it_5.5.0_3.0_1725319873505.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("umberto_commoncrawl_cased_v1_pipeline", lang = "it") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("umberto_commoncrawl_cased_v1_pipeline", lang = "it") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|umberto_commoncrawl_cased_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|it| +|Size:|263.1 MB| + +## References + +https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-umberto_wikipedia_uncased_v1_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-02-umberto_wikipedia_uncased_v1_pipeline_it.md new file mode 100644 index 00000000000000..14577b280b8d2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-umberto_wikipedia_uncased_v1_pipeline_it.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Italian umberto_wikipedia_uncased_v1_pipeline pipeline CamemBertEmbeddings from Musixmatch +author: John Snow Labs +name: umberto_wikipedia_uncased_v1_pipeline +date: 2024-09-02 +tags: [it, open_source, pipeline, onnx] +task: Embeddings +language: it +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`umberto_wikipedia_uncased_v1_pipeline` is a Italian model originally trained by Musixmatch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/umberto_wikipedia_uncased_v1_pipeline_it_5.5.0_3.0_1725320061488.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/umberto_wikipedia_uncased_v1_pipeline_it_5.5.0_3.0_1725320061488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("umberto_wikipedia_uncased_v1_pipeline", lang = "it") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("umberto_wikipedia_uncased_v1_pipeline", lang = "it") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|umberto_wikipedia_uncased_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|it| +|Size:|262.7 MB| + +## References + +https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-upsc_classification_model_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-upsc_classification_model_v1_pipeline_en.md new file mode 100644 index 00000000000000..87912f7dddbfd3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-upsc_classification_model_v1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English upsc_classification_model_v1_pipeline pipeline MPNetEmbeddings from kowshik +author: John Snow Labs +name: upsc_classification_model_v1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`upsc_classification_model_v1_pipeline` is a English model originally trained by kowshik. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/upsc_classification_model_v1_pipeline_en_5.5.0_3.0_1725313843768.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/upsc_classification_model_v1_pipeline_en_5.5.0_3.0_1725313843768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("upsc_classification_model_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("upsc_classification_model_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|upsc_classification_model_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/kowshik/upsc-classification-model-v1 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-urdish_roberta_base_sentiment_pipeline_ur.md b/docs/_posts/ahmedlone127/2024-09-02-urdish_roberta_base_sentiment_pipeline_ur.md new file mode 100644 index 00000000000000..c63375c46a32dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-urdish_roberta_base_sentiment_pipeline_ur.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Urdu urdish_roberta_base_sentiment_pipeline pipeline RoBertaForSequenceClassification from dataranch +author: John Snow Labs +name: urdish_roberta_base_sentiment_pipeline +date: 2024-09-02 +tags: [ur, open_source, pipeline, onnx] +task: Text Classification +language: ur +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`urdish_roberta_base_sentiment_pipeline` is a Urdu model originally trained by dataranch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/urdish_roberta_base_sentiment_pipeline_ur_5.5.0_3.0_1725277898934.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/urdish_roberta_base_sentiment_pipeline_ur_5.5.0_3.0_1725277898934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("urdish_roberta_base_sentiment_pipeline", lang = "ur") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("urdish_roberta_base_sentiment_pipeline", lang = "ur") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|urdish_roberta_base_sentiment_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ur| +|Size:|468.3 MB| + +## References + +https://huggingface.co/dataranch/urdish-roberta-base-sentiment + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-vn_japanese_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-vn_japanese_tonga_tonga_islands_english_en.md new file mode 100644 index 00000000000000..904ebb918d47ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-vn_japanese_tonga_tonga_islands_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English vn_japanese_tonga_tonga_islands_english MarianTransformer from twieland +author: John Snow Labs +name: vn_japanese_tonga_tonga_islands_english +date: 2024-09-02 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vn_japanese_tonga_tonga_islands_english` is a English model originally trained by twieland. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vn_japanese_tonga_tonga_islands_english_en_5.5.0_3.0_1725243298949.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vn_japanese_tonga_tonga_islands_english_en_5.5.0_3.0_1725243298949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("vn_japanese_tonga_tonga_islands_english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("vn_japanese_tonga_tonga_islands_english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vn_japanese_tonga_tonga_islands_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|515.6 MB| + +## References + +https://huggingface.co/twieland/VN_ja_to_en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-vn_japanese_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-vn_japanese_tonga_tonga_islands_english_pipeline_en.md new file mode 100644 index 00000000000000..aef4dcb8d8e022 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-vn_japanese_tonga_tonga_islands_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English vn_japanese_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from twieland +author: John Snow Labs +name: vn_japanese_tonga_tonga_islands_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vn_japanese_tonga_tonga_islands_english_pipeline` is a English model originally trained by twieland. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vn_japanese_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725243332690.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vn_japanese_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725243332690.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("vn_japanese_tonga_tonga_islands_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("vn_japanese_tonga_tonga_islands_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vn_japanese_tonga_tonga_islands_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|516.1 MB| + +## References + +https://huggingface.co/twieland/VN_ja_to_en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-wangchanberta_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-02-wangchanberta_sentiment_analysis_en.md new file mode 100644 index 00000000000000..13f3e6c81b8235 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-wangchanberta_sentiment_analysis_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English wangchanberta_sentiment_analysis CamemBertForSequenceClassification from SuratanBoonpong +author: John Snow Labs +name: wangchanberta_sentiment_analysis +date: 2024-09-02 +tags: [en, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wangchanberta_sentiment_analysis` is a English model originally trained by SuratanBoonpong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wangchanberta_sentiment_analysis_en_5.5.0_3.0_1725299040290.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wangchanberta_sentiment_analysis_en_5.5.0_3.0_1725299040290.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("wangchanberta_sentiment_analysis","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("wangchanberta_sentiment_analysis", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wangchanberta_sentiment_analysis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|394.3 MB| + +## References + +https://huggingface.co/SuratanBoonpong/Wangchanberta_sentiment_analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-wangchanberta_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-wangchanberta_sentiment_analysis_pipeline_en.md new file mode 100644 index 00000000000000..7a27314faf2097 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-wangchanberta_sentiment_analysis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English wangchanberta_sentiment_analysis_pipeline pipeline CamemBertForSequenceClassification from SuratanBoonpong +author: John Snow Labs +name: wangchanberta_sentiment_analysis_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wangchanberta_sentiment_analysis_pipeline` is a English model originally trained by SuratanBoonpong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wangchanberta_sentiment_analysis_pipeline_en_5.5.0_3.0_1725299060970.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wangchanberta_sentiment_analysis_pipeline_en_5.5.0_3.0_1725299060970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("wangchanberta_sentiment_analysis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("wangchanberta_sentiment_analysis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wangchanberta_sentiment_analysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|394.4 MB| + +## References + +https://huggingface.co/SuratanBoonpong/Wangchanberta_sentiment_analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whipser_medium_english_pal300_step25_en.md b/docs/_posts/ahmedlone127/2024-09-02-whipser_medium_english_pal300_step25_en.md new file mode 100644 index 00000000000000..225430622cce5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whipser_medium_english_pal300_step25_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whipser_medium_english_pal300_step25 WhisperForCTC from KevinGeng +author: John Snow Labs +name: whipser_medium_english_pal300_step25 +date: 2024-09-02 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whipser_medium_english_pal300_step25` is a English model originally trained by KevinGeng. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whipser_medium_english_pal300_step25_en_5.5.0_3.0_1725251138952.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whipser_medium_english_pal300_step25_en_5.5.0_3.0_1725251138952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("whipser_medium_english_pal300_step25","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whipser_medium_english_pal300_step25", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whipser_medium_english_pal300_step25| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|4.8 GB| + +## References + +https://huggingface.co/KevinGeng/whipser_medium_en_PAL300_step25 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_arabic_ar.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_arabic_ar.md new file mode 100644 index 00000000000000..478a0ca8853bf2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_arabic_ar.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Arabic whisper_arabic WhisperForCTC from hamzamalik11 +author: John Snow Labs +name: whisper_arabic +date: 2024-09-02 +tags: [ar, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_arabic` is a Arabic model originally trained by hamzamalik11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_arabic_ar_5.5.0_3.0_1725246197916.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_arabic_ar_5.5.0_3.0_1725246197916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("whisper_arabic","ar") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_arabic", "ar") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_arabic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ar| +|Size:|1.7 GB| + +## References + +https://huggingface.co/hamzamalik11/Whisper_Arabic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_arabic_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_arabic_pipeline_ar.md new file mode 100644 index 00000000000000..0e03b87281d70e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_arabic_pipeline_ar.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Arabic whisper_arabic_pipeline pipeline WhisperForCTC from hamzamalik11 +author: John Snow Labs +name: whisper_arabic_pipeline +date: 2024-09-02 +tags: [ar, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_arabic_pipeline` is a Arabic model originally trained by hamzamalik11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_arabic_pipeline_ar_5.5.0_3.0_1725246286856.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_arabic_pipeline_ar_5.5.0_3.0_1725246286856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_arabic_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_arabic_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_arabic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|1.7 GB| + +## References + +https://huggingface.co/hamzamalik11/Whisper_Arabic + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_base_arabic_quran_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_arabic_quran_pipeline_en.md new file mode 100644 index 00000000000000..779c7290d000d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_arabic_quran_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_base_arabic_quran_pipeline pipeline WhisperForCTC from tarteel-ai +author: John Snow Labs +name: whisper_base_arabic_quran_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_arabic_quran_pipeline` is a English model originally trained by tarteel-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_arabic_quran_pipeline_en_5.5.0_3.0_1725249522947.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_arabic_quran_pipeline_en_5.5.0_3.0_1725249522947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_base_arabic_quran_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_base_arabic_quran_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_base_arabic_quran_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|643.1 MB| + +## References + +https://huggingface.co/tarteel-ai/whisper-base-ar-quran + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_base_bungoma_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_bungoma_english_en.md new file mode 100644 index 00000000000000..d68892173c4129 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_bungoma_english_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_base_bungoma_english WhisperForCTC from eai6 +author: John Snow Labs +name: whisper_base_bungoma_english +date: 2024-09-02 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_bungoma_english` is a English model originally trained by eai6. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_bungoma_english_en_5.5.0_3.0_1725250489169.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_bungoma_english_en_5.5.0_3.0_1725250489169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("whisper_base_bungoma_english","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_base_bungoma_english", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_base_bungoma_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|645.3 MB| + +## References + +https://huggingface.co/eai6/whisper-base-bungoma.en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_base_bungoma_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_bungoma_english_pipeline_en.md new file mode 100644 index 00000000000000..fe48b13f2b99da --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_bungoma_english_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_base_bungoma_english_pipeline pipeline WhisperForCTC from eai6 +author: John Snow Labs +name: whisper_base_bungoma_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_bungoma_english_pipeline` is a English model originally trained by eai6. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_bungoma_english_pipeline_en_5.5.0_3.0_1725250533630.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_bungoma_english_pipeline_en_5.5.0_3.0_1725250533630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_base_bungoma_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_base_bungoma_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_base_bungoma_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|645.3 MB| + +## References + +https://huggingface.co/eai6/whisper-base-bungoma.en + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_base_quran_ai_by_tarteel_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_quran_ai_by_tarteel_en.md new file mode 100644 index 00000000000000..14dc8d39494298 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_quran_ai_by_tarteel_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_base_quran_ai_by_tarteel WhisperForCTC from Democtic +author: John Snow Labs +name: whisper_base_quran_ai_by_tarteel +date: 2024-09-02 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_quran_ai_by_tarteel` is a English model originally trained by Democtic. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_quran_ai_by_tarteel_en_5.5.0_3.0_1725289752832.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_quran_ai_by_tarteel_en_5.5.0_3.0_1725289752832.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("whisper_base_quran_ai_by_tarteel","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_base_quran_ai_by_tarteel", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_base_quran_ai_by_tarteel| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|643.1 MB| + +## References + +https://huggingface.co/Democtic/whisper-base-quran-ai-by-tarteel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_base_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_spanish_es.md new file mode 100644 index 00000000000000..836be70d6035e8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_spanish_es.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Castilian, Spanish whisper_base_spanish WhisperForCTC from zuazo +author: John Snow Labs +name: whisper_base_spanish +date: 2024-09-02 +tags: [es, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_spanish` is a Castilian, Spanish model originally trained by zuazo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_spanish_es_5.5.0_3.0_1725288070985.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_spanish_es_5.5.0_3.0_1725288070985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("whisper_base_spanish","es") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_base_spanish", "es") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_base_spanish| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|es| +|Size:|642.7 MB| + +## References + +https://huggingface.co/zuazo/whisper-base-es \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_base_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_spanish_pipeline_es.md new file mode 100644 index 00000000000000..f59865a2df6771 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_spanish_pipeline_es.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Castilian, Spanish whisper_base_spanish_pipeline pipeline WhisperForCTC from zuazo +author: John Snow Labs +name: whisper_base_spanish_pipeline +date: 2024-09-02 +tags: [es, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_spanish_pipeline` is a Castilian, Spanish model originally trained by zuazo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_spanish_pipeline_es_5.5.0_3.0_1725288104931.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_spanish_pipeline_es_5.5.0_3.0_1725288104931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_base_spanish_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_base_spanish_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_base_spanish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|642.7 MB| + +## References + +https://huggingface.co/zuazo/whisper-base-es + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_kannada_tiny_kn.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_kannada_tiny_kn.md new file mode 100644 index 00000000000000..92e42e58444098 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_kannada_tiny_kn.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Kannada whisper_kannada_tiny WhisperForCTC from vasista22 +author: John Snow Labs +name: whisper_kannada_tiny +date: 2024-09-02 +tags: [kn, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: kn +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_kannada_tiny` is a Kannada model originally trained by vasista22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_kannada_tiny_kn_5.5.0_3.0_1725247750371.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_kannada_tiny_kn_5.5.0_3.0_1725247750371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("whisper_kannada_tiny","kn") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_kannada_tiny", "kn") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_kannada_tiny| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|kn| +|Size:|391.0 MB| + +## References + +https://huggingface.co/vasista22/whisper-kannada-tiny \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_kannada_tiny_pipeline_kn.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_kannada_tiny_pipeline_kn.md new file mode 100644 index 00000000000000..13b95ed5589d96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_kannada_tiny_pipeline_kn.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Kannada whisper_kannada_tiny_pipeline pipeline WhisperForCTC from vasista22 +author: John Snow Labs +name: whisper_kannada_tiny_pipeline +date: 2024-09-02 +tags: [kn, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: kn +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_kannada_tiny_pipeline` is a Kannada model originally trained by vasista22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_kannada_tiny_pipeline_kn_5.5.0_3.0_1725247771917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_kannada_tiny_pipeline_kn_5.5.0_3.0_1725247771917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_kannada_tiny_pipeline", lang = "kn") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_kannada_tiny_pipeline", lang = "kn") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_kannada_tiny_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|kn| +|Size:|391.0 MB| + +## References + +https://huggingface.co/vasista22/whisper-kannada-tiny + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_cantonese_alvanlii_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_cantonese_alvanlii_pipeline_zh.md new file mode 100644 index 00000000000000..f9a6ad7948174a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_cantonese_alvanlii_pipeline_zh.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Chinese whisper_small_cantonese_alvanlii_pipeline pipeline WhisperForCTC from alvanlii +author: John Snow Labs +name: whisper_small_cantonese_alvanlii_pipeline +date: 2024-09-02 +tags: [zh, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_cantonese_alvanlii_pipeline` is a Chinese model originally trained by alvanlii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_cantonese_alvanlii_pipeline_zh_5.5.0_3.0_1725285772467.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_cantonese_alvanlii_pipeline_zh_5.5.0_3.0_1725285772467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_cantonese_alvanlii_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_cantonese_alvanlii_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_cantonese_alvanlii_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|1.7 GB| + +## References + +https://huggingface.co/alvanlii/whisper-small-cantonese + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_cantonese_alvanlii_zh.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_cantonese_alvanlii_zh.md new file mode 100644 index 00000000000000..aeaa66c15fd495 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_cantonese_alvanlii_zh.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Chinese whisper_small_cantonese_alvanlii WhisperForCTC from alvanlii +author: John Snow Labs +name: whisper_small_cantonese_alvanlii +date: 2024-09-02 +tags: [zh, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_cantonese_alvanlii` is a Chinese model originally trained by alvanlii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_cantonese_alvanlii_zh_5.5.0_3.0_1725285684118.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_cantonese_alvanlii_zh_5.5.0_3.0_1725285684118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("whisper_small_cantonese_alvanlii","zh") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_cantonese_alvanlii", "zh") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_cantonese_alvanlii| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|zh| +|Size:|1.7 GB| + +## References + +https://huggingface.co/alvanlii/whisper-small-cantonese \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_chinese_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_chinese_base_pipeline_en.md new file mode 100644 index 00000000000000..a6a0500fc8c503 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_chinese_base_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_small_chinese_base_pipeline pipeline WhisperForCTC from Jingmiao +author: John Snow Labs +name: whisper_small_chinese_base_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_chinese_base_pipeline` is a English model originally trained by Jingmiao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_chinese_base_pipeline_en_5.5.0_3.0_1725287764838.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_chinese_base_pipeline_en_5.5.0_3.0_1725287764838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_chinese_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_chinese_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_chinese_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Jingmiao/whisper-small-chinese_base + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_kyrgyz_ky.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_kyrgyz_ky.md new file mode 100644 index 00000000000000..5d7f5216c8a5ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_kyrgyz_ky.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Kirghiz, Kyrgyz whisper_small_kyrgyz WhisperForCTC from UlutSoftLLC +author: John Snow Labs +name: whisper_small_kyrgyz +date: 2024-09-02 +tags: [ky, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: ky +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_kyrgyz` is a Kirghiz, Kyrgyz model originally trained by UlutSoftLLC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_kyrgyz_ky_5.5.0_3.0_1725287552636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_kyrgyz_ky_5.5.0_3.0_1725287552636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("whisper_small_kyrgyz","ky") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_kyrgyz", "ky") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_kyrgyz| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ky| +|Size:|1.7 GB| + +## References + +https://huggingface.co/UlutSoftLLC/whisper-small-kyrgyz \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_kyrgyz_pipeline_ky.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_kyrgyz_pipeline_ky.md new file mode 100644 index 00000000000000..9756e1d78aaa94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_kyrgyz_pipeline_ky.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Kirghiz, Kyrgyz whisper_small_kyrgyz_pipeline pipeline WhisperForCTC from UlutSoftLLC +author: John Snow Labs +name: whisper_small_kyrgyz_pipeline +date: 2024-09-02 +tags: [ky, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ky +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_kyrgyz_pipeline` is a Kirghiz, Kyrgyz model originally trained by UlutSoftLLC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_kyrgyz_pipeline_ky_5.5.0_3.0_1725287650500.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_kyrgyz_pipeline_ky_5.5.0_3.0_1725287650500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_kyrgyz_pipeline", lang = "ky") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_kyrgyz_pipeline", lang = "ky") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_kyrgyz_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ky| +|Size:|1.7 GB| + +## References + +https://huggingface.co/UlutSoftLLC/whisper-small-kyrgyz + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_multimed_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_multimed_en.md new file mode 100644 index 00000000000000..00e194152d4cc8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_multimed_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_small_multimed WhisperForCTC from Hanhpt23 +author: John Snow Labs +name: whisper_small_multimed +date: 2024-09-02 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_multimed` is a English model originally trained by Hanhpt23. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_multimed_en_5.5.0_3.0_1725248151709.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_multimed_en_5.5.0_3.0_1725248151709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("whisper_small_multimed","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_multimed", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_multimed| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/Hanhpt23/whisper-small-multimed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_multimed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_multimed_pipeline_en.md new file mode 100644 index 00000000000000..20be38c63f4922 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_multimed_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_small_multimed_pipeline pipeline WhisperForCTC from Hanhpt23 +author: John Snow Labs +name: whisper_small_multimed_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_multimed_pipeline` is a English model originally trained by Hanhpt23. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_multimed_pipeline_en_5.5.0_3.0_1725248290795.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_multimed_pipeline_en_5.5.0_3.0_1725248290795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_multimed_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_multimed_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_multimed_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/Hanhpt23/whisper-small-multimed + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_russian_phone_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_russian_phone_pipeline_ru.md new file mode 100644 index 00000000000000..5f3af7f9fb9106 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_russian_phone_pipeline_ru.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Russian whisper_small_russian_phone_pipeline pipeline WhisperForCTC from Stepler +author: John Snow Labs +name: whisper_small_russian_phone_pipeline +date: 2024-09-02 +tags: [ru, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_russian_phone_pipeline` is a Russian model originally trained by Stepler. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_russian_phone_pipeline_ru_5.5.0_3.0_1725247491482.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_russian_phone_pipeline_ru_5.5.0_3.0_1725247491482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_russian_phone_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_russian_phone_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_russian_phone_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Stepler/whisper-small-ru-phone + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_russian_phone_ru.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_russian_phone_ru.md new file mode 100644 index 00000000000000..ce7520bb64dc85 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_russian_phone_ru.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Russian whisper_small_russian_phone WhisperForCTC from Stepler +author: John Snow Labs +name: whisper_small_russian_phone +date: 2024-09-02 +tags: [ru, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_russian_phone` is a Russian model originally trained by Stepler. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_russian_phone_ru_5.5.0_3.0_1725247402550.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_russian_phone_ru_5.5.0_3.0_1725247402550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("whisper_small_russian_phone","ru") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_russian_phone", "ru") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_russian_phone| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ru| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Stepler/whisper-small-ru-phone \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_taiwanese_minnan_take2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_taiwanese_minnan_take2_pipeline_en.md new file mode 100644 index 00000000000000..4f362b23114bc0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_taiwanese_minnan_take2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_small_taiwanese_minnan_take2_pipeline pipeline WhisperForCTC from caotun +author: John Snow Labs +name: whisper_small_taiwanese_minnan_take2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_taiwanese_minnan_take2_pipeline` is a English model originally trained by caotun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_taiwanese_minnan_take2_pipeline_en_5.5.0_3.0_1725284947877.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_taiwanese_minnan_take2_pipeline_en_5.5.0_3.0_1725284947877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_taiwanese_minnan_take2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_taiwanese_minnan_take2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_taiwanese_minnan_take2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/caotun/whisper-small-taiwanese-minnan-take2 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_thai_film6912_th.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_thai_film6912_th.md new file mode 100644 index 00000000000000..b611af9571dd2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_thai_film6912_th.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Thai whisper_small_thai_film6912 WhisperForCTC from FILM6912 +author: John Snow Labs +name: whisper_small_thai_film6912 +date: 2024-09-02 +tags: [th, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: th +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_thai_film6912` is a Thai model originally trained by FILM6912. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_thai_film6912_th_5.5.0_3.0_1725289760031.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_thai_film6912_th_5.5.0_3.0_1725289760031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("whisper_small_thai_film6912","th") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_thai_film6912", "th") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_thai_film6912| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|th| +|Size:|1.7 GB| + +## References + +https://huggingface.co/FILM6912/Whisper-small-thai \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_vdv_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_vdv_en.md new file mode 100644 index 00000000000000..74f84036d18f3d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_vdv_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_small_vdv WhisperForCTC from simodo79 +author: John Snow Labs +name: whisper_small_vdv +date: 2024-09-02 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_vdv` is a English model originally trained by simodo79. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_vdv_en_5.5.0_3.0_1725285355618.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_vdv_en_5.5.0_3.0_1725285355618.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("whisper_small_vdv","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_vdv", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_vdv| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/simodo79/whisper-small-vdv \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_vdv_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_vdv_pipeline_en.md new file mode 100644 index 00000000000000..1ac2655163d106 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_vdv_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_small_vdv_pipeline pipeline WhisperForCTC from simodo79 +author: John Snow Labs +name: whisper_small_vdv_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_vdv_pipeline` is a English model originally trained by simodo79. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_vdv_pipeline_en_5.5.0_3.0_1725285444404.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_vdv_pipeline_en_5.5.0_3.0_1725285444404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_vdv_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_vdv_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_vdv_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/simodo79/whisper-small-vdv + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-wolfbbsroberta_small_en.md b/docs/_posts/ahmedlone127/2024-09-02-wolfbbsroberta_small_en.md new file mode 100644 index 00000000000000..7ad6af902fcc87 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-wolfbbsroberta_small_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English wolfbbsroberta_small CamemBertEmbeddings from itsunoda +author: John Snow Labs +name: wolfbbsroberta_small +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wolfbbsroberta_small` is a English model originally trained by itsunoda. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wolfbbsroberta_small_en_5.5.0_3.0_1725297414412.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wolfbbsroberta_small_en_5.5.0_3.0_1725297414412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = CamemBertEmbeddings.pretrained("wolfbbsroberta_small","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("wolfbbsroberta_small","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wolfbbsroberta_small| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|411.3 MB| + +## References + +https://huggingface.co/itsunoda/wolfbbsRoBERTa-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-wolfbbsroberta_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-wolfbbsroberta_small_pipeline_en.md new file mode 100644 index 00000000000000..9dd8c624ce15f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-wolfbbsroberta_small_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English wolfbbsroberta_small_pipeline pipeline CamemBertEmbeddings from itsunoda +author: John Snow Labs +name: wolfbbsroberta_small_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wolfbbsroberta_small_pipeline` is a English model originally trained by itsunoda. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wolfbbsroberta_small_pipeline_en_5.5.0_3.0_1725297435421.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wolfbbsroberta_small_pipeline_en_5.5.0_3.0_1725297435421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("wolfbbsroberta_small_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("wolfbbsroberta_small_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wolfbbsroberta_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.4 MB| + +## References + +https://huggingface.co/itsunoda/wolfbbsRoBERTa-small + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-wsd_myriade_distil_adapter_en.md b/docs/_posts/ahmedlone127/2024-09-02-wsd_myriade_distil_adapter_en.md new file mode 100644 index 00000000000000..f6f2e6b634ee97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-wsd_myriade_distil_adapter_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English wsd_myriade_distil_adapter CamemBertForTokenClassification from gguichard +author: John Snow Labs +name: wsd_myriade_distil_adapter +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, camembert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wsd_myriade_distil_adapter` is a English model originally trained by gguichard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wsd_myriade_distil_adapter_en_5.5.0_3.0_1725266490223.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wsd_myriade_distil_adapter_en_5.5.0_3.0_1725266490223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = CamemBertForTokenClassification.pretrained("wsd_myriade_distil_adapter","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = CamemBertForTokenClassification.pretrained("wsd_myriade_distil_adapter", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wsd_myriade_distil_adapter| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/gguichard/wsd_myriade_distil_adapter \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-wsd_myriade_distil_adapter_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-wsd_myriade_distil_adapter_pipeline_en.md new file mode 100644 index 00000000000000..c469caaafaadf6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-wsd_myriade_distil_adapter_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English wsd_myriade_distil_adapter_pipeline pipeline CamemBertForTokenClassification from gguichard +author: John Snow Labs +name: wsd_myriade_distil_adapter_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wsd_myriade_distil_adapter_pipeline` is a English model originally trained by gguichard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wsd_myriade_distil_adapter_pipeline_en_5.5.0_3.0_1725266578275.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wsd_myriade_distil_adapter_pipeline_en_5.5.0_3.0_1725266578275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("wsd_myriade_distil_adapter_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("wsd_myriade_distil_adapter_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wsd_myriade_distil_adapter_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/gguichard/wsd_myriade_distil_adapter + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-wsd_myriade_synth_data_gpt4turbo_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-wsd_myriade_synth_data_gpt4turbo_1_pipeline_en.md new file mode 100644 index 00000000000000..f27afeace824f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-wsd_myriade_synth_data_gpt4turbo_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English wsd_myriade_synth_data_gpt4turbo_1_pipeline pipeline CamemBertForTokenClassification from gguichard +author: John Snow Labs +name: wsd_myriade_synth_data_gpt4turbo_1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wsd_myriade_synth_data_gpt4turbo_1_pipeline` is a English model originally trained by gguichard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wsd_myriade_synth_data_gpt4turbo_1_pipeline_en_5.5.0_3.0_1725266504756.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wsd_myriade_synth_data_gpt4turbo_1_pipeline_en_5.5.0_3.0_1725266504756.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("wsd_myriade_synth_data_gpt4turbo_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("wsd_myriade_synth_data_gpt4turbo_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wsd_myriade_synth_data_gpt4turbo_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/gguichard/wsd_myriade_synth_data_gpt4turbo_1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_robert_finetune_model_vn_ver2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_robert_finetune_model_vn_ver2_pipeline_en.md new file mode 100644 index 00000000000000..c06a32febfaf24 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_robert_finetune_model_vn_ver2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_robert_finetune_model_vn_ver2_pipeline pipeline XlmRoBertaForTokenClassification from zhangwenzhe +author: John Snow Labs +name: xlm_robert_finetune_model_vn_ver2_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_robert_finetune_model_vn_ver2_pipeline` is a English model originally trained by zhangwenzhe. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_robert_finetune_model_vn_ver2_pipeline_en_5.5.0_3.0_1725316365170.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_robert_finetune_model_vn_ver2_pipeline_en_5.5.0_3.0_1725316365170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_robert_finetune_model_vn_ver2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_robert_finetune_model_vn_ver2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_robert_finetune_model_vn_ver2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|771.9 MB| + +## References + +https://huggingface.co/zhangwenzhe/XLM-Robert-finetune-model-VN-ver2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_en.md new file mode 100644 index 00000000000000..38bc1e0bde6b1a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1 XlmRoBertaForQuestionAnswering from jluckyboyj +author: John Snow Labs +name: xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1` is a English model originally trained by jluckyboyj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_en_5.5.0_3.0_1725253586992.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_en_5.5.0_3.0_1725253586992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|853.0 MB| + +## References + +https://huggingface.co/jluckyboyj/xlm-roberta-base-finetuned-augument-visquad2-14-3-2023-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_pipeline_en.md new file mode 100644 index 00000000000000..777630c2752e56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_pipeline pipeline XlmRoBertaForQuestionAnswering from jluckyboyj +author: John Snow Labs +name: xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_pipeline` is a English model originally trained by jluckyboyj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_pipeline_en_5.5.0_3.0_1725253655545.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_pipeline_en_5.5.0_3.0_1725253655545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.0 MB| + +## References + +https://huggingface.co/jluckyboyj/xlm-roberta-base-finetuned-augument-visquad2-14-3-2023-1 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_en.md new file mode 100644 index 00000000000000..62379d1a17367f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned XlmRoBertaEmbeddings from RogerB +author: John Snow Labs +name: xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned` is a English model originally trained by RogerB. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_en_5.5.0_3.0_1725270235372.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_en_5.5.0_3.0_1725270235372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kinyarwanda-kinre-finetuned-kinre-tweet-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..7f886fccfca4c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_pipeline pipeline XlmRoBertaEmbeddings from RogerB +author: John Snow Labs +name: xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_pipeline` is a English model originally trained by RogerB. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_pipeline_en_5.5.0_3.0_1725270292387.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_pipeline_en_5.5.0_3.0_1725270292387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_kinre_tweet_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kinyarwanda-kinre-finetuned-kinre-tweet-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_all_noveled_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_all_noveled_en.md new file mode 100644 index 00000000000000..5072f677161b62 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_all_noveled_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_all_noveled XlmRoBertaForTokenClassification from Noveled +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_all_noveled +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_noveled` is a English model originally trained by Noveled. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_noveled_en_5.5.0_3.0_1725316872568.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_noveled_en_5.5.0_3.0_1725316872568.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_noveled","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_noveled", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_all_noveled| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|848.0 MB| + +## References + +https://huggingface.co/Noveled/xlm-roberta-base-finetuned-panx-all \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_all_noveled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_all_noveled_pipeline_en.md new file mode 100644 index 00000000000000..7a08de99ae96be --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_all_noveled_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_all_noveled_pipeline pipeline XlmRoBertaForTokenClassification from Noveled +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_all_noveled_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_noveled_pipeline` is a English model originally trained by Noveled. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_noveled_pipeline_en_5.5.0_3.0_1725316956085.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_noveled_pipeline_en_5.5.0_3.0_1725316956085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_noveled_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_noveled_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_all_noveled_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|848.0 MB| + +## References + +https://huggingface.co/Noveled/xlm-roberta-base-finetuned-panx-all + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_english_heerak_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_english_heerak_en.md new file mode 100644 index 00000000000000..4bed71deabe8a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_english_heerak_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_english_heerak XlmRoBertaForTokenClassification from Heerak +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_english_heerak +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_heerak` is a English model originally trained by Heerak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_heerak_en_5.5.0_3.0_1725317327365.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_heerak_en_5.5.0_3.0_1725317327365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_heerak","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_heerak", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_english_heerak| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|826.4 MB| + +## References + +https://huggingface.co/Heerak/xlm-roberta-base-finetuned-panx-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_english_heerak_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_english_heerak_pipeline_en.md new file mode 100644 index 00000000000000..49ae01ba5e47d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_english_heerak_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_english_heerak_pipeline pipeline XlmRoBertaForTokenClassification from Heerak +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_english_heerak_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_heerak_pipeline` is a English model originally trained by Heerak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_heerak_pipeline_en_5.5.0_3.0_1725317425734.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_heerak_pipeline_en_5.5.0_3.0_1725317425734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_heerak_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_heerak_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_english_heerak_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|826.4 MB| + +## References + +https://huggingface.co/Heerak/xlm-roberta-base-finetuned-panx-en + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_nobody138_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_nobody138_en.md new file mode 100644 index 00000000000000..5baf5bb6c23d0e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_nobody138_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_french_nobody138 XlmRoBertaForTokenClassification from Nobody138 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_french_nobody138 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_nobody138` is a English model originally trained by Nobody138. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_nobody138_en_5.5.0_3.0_1725316352207.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_nobody138_en_5.5.0_3.0_1725316352207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_nobody138","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_nobody138", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_french_nobody138| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|840.9 MB| + +## References + +https://huggingface.co/Nobody138/xlm-roberta-base-finetuned-panx-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_nobody138_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_nobody138_pipeline_en.md new file mode 100644 index 00000000000000..864f42116f0f27 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_nobody138_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_french_nobody138_pipeline pipeline XlmRoBertaForTokenClassification from Nobody138 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_french_nobody138_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_nobody138_pipeline` is a English model originally trained by Nobody138. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_nobody138_pipeline_en_5.5.0_3.0_1725316433739.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_nobody138_pipeline_en_5.5.0_3.0_1725316433739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_nobody138_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_nobody138_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_french_nobody138_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|840.9 MB| + +## References + +https://huggingface.co/Nobody138/xlm-roberta-base-finetuned-panx-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_rlpeter70_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_rlpeter70_en.md new file mode 100644 index 00000000000000..66f4ad3b247bda --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_rlpeter70_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_french_rlpeter70 XlmRoBertaForTokenClassification from rlpeter70 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_french_rlpeter70 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_rlpeter70` is a English model originally trained by rlpeter70. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_rlpeter70_en_5.5.0_3.0_1725317680717.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_rlpeter70_en_5.5.0_3.0_1725317680717.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_rlpeter70","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_rlpeter70", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_french_rlpeter70| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|840.9 MB| + +## References + +https://huggingface.co/rlpeter70/xlm-roberta-base-finetuned-panx-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_rlpeter70_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_rlpeter70_pipeline_en.md new file mode 100644 index 00000000000000..d71e84b6518723 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_rlpeter70_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_french_rlpeter70_pipeline pipeline XlmRoBertaForTokenClassification from rlpeter70 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_french_rlpeter70_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_rlpeter70_pipeline` is a English model originally trained by rlpeter70. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_rlpeter70_pipeline_en_5.5.0_3.0_1725317762517.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_rlpeter70_pipeline_en_5.5.0_3.0_1725317762517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_rlpeter70_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_rlpeter70_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_french_rlpeter70_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|840.9 MB| + +## References + +https://huggingface.co/rlpeter70/xlm-roberta-base-finetuned-panx-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_v3rx2000_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_v3rx2000_en.md new file mode 100644 index 00000000000000..ef8f0fa34f4d95 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_v3rx2000_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_french_v3rx2000 XlmRoBertaForTokenClassification from V3RX2000 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_french_v3rx2000 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_v3rx2000` is a English model originally trained by V3RX2000. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_v3rx2000_en_5.5.0_3.0_1725316292636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_v3rx2000_en_5.5.0_3.0_1725316292636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_v3rx2000","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_v3rx2000", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_french_v3rx2000| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|840.9 MB| + +## References + +https://huggingface.co/V3RX2000/xlm-roberta-base-finetuned-panx-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_v3rx2000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_v3rx2000_pipeline_en.md new file mode 100644 index 00000000000000..643a997dff7e23 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_french_v3rx2000_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_french_v3rx2000_pipeline pipeline XlmRoBertaForTokenClassification from V3RX2000 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_french_v3rx2000_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_v3rx2000_pipeline` is a English model originally trained by V3RX2000. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_v3rx2000_pipeline_en_5.5.0_3.0_1725316374667.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_v3rx2000_pipeline_en_5.5.0_3.0_1725316374667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_v3rx2000_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_v3rx2000_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_french_v3rx2000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|840.9 MB| + +## References + +https://huggingface.co/V3RX2000/xlm-roberta-base-finetuned-panx-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_aiekek_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_aiekek_pipeline_en.md new file mode 100644 index 00000000000000..1aabf75cc38f36 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_aiekek_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_aiekek_pipeline pipeline XlmRoBertaForTokenClassification from AIEKEK +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_aiekek_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_aiekek_pipeline` is a English model originally trained by AIEKEK. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_aiekek_pipeline_en_5.5.0_3.0_1725321508383.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_aiekek_pipeline_en_5.5.0_3.0_1725321508383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_aiekek_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_aiekek_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_aiekek_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|840.8 MB| + +## References + +https://huggingface.co/AIEKEK/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_cataluna84_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_cataluna84_en.md new file mode 100644 index 00000000000000..de7c20460796c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_cataluna84_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_cataluna84 XlmRoBertaForTokenClassification from cataluna84 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_cataluna84 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_cataluna84` is a English model originally trained by cataluna84. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_cataluna84_en_5.5.0_3.0_1725317818642.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_cataluna84_en_5.5.0_3.0_1725317818642.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_cataluna84","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_cataluna84", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_cataluna84| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/cataluna84/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_cataluna84_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_cataluna84_pipeline_en.md new file mode 100644 index 00000000000000..bd405a6558e3c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_cataluna84_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_cataluna84_pipeline pipeline XlmRoBertaForTokenClassification from cataluna84 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_cataluna84_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_cataluna84_pipeline` is a English model originally trained by cataluna84. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_cataluna84_pipeline_en_5.5.0_3.0_1725317888871.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_cataluna84_pipeline_en_5.5.0_3.0_1725317888871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_cataluna84_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_cataluna84_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_cataluna84_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/cataluna84/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_clboetticher_school_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_clboetticher_school_en.md new file mode 100644 index 00000000000000..653bd57f6f3de2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_clboetticher_school_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_clboetticher_school XlmRoBertaForTokenClassification from clboetticher-school +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_clboetticher_school +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_clboetticher_school` is a English model originally trained by clboetticher-school. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_clboetticher_school_en_5.5.0_3.0_1725317616835.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_clboetticher_school_en_5.5.0_3.0_1725317616835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_clboetticher_school","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_clboetticher_school", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_clboetticher_school| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/clboetticher-school/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_alanhou_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_alanhou_en.md new file mode 100644 index 00000000000000..d4a517478d99c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_alanhou_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_french_alanhou XlmRoBertaForTokenClassification from AlanHou +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_french_alanhou +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_alanhou` is a English model originally trained by AlanHou. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_alanhou_en_5.5.0_3.0_1725307948857.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_alanhou_en_5.5.0_3.0_1725307948857.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_alanhou","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_alanhou", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_french_alanhou| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|843.4 MB| + +## References + +https://huggingface.co/AlanHou/xlm-roberta-base-finetuned-panx-de-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_feic36_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_feic36_en.md new file mode 100644 index 00000000000000..894f1d107fc690 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_feic36_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_french_feic36 XlmRoBertaForTokenClassification from feic36 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_french_feic36 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_feic36` is a English model originally trained by feic36. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_feic36_en_5.5.0_3.0_1725316588617.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_feic36_en_5.5.0_3.0_1725316588617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_feic36","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_feic36", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_french_feic36| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|858.2 MB| + +## References + +https://huggingface.co/feic36/xlm-roberta-base-finetuned-panx-de-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_fumikawa_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_fumikawa_en.md new file mode 100644 index 00000000000000..d326598b766151 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_fumikawa_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_fumikawa XlmRoBertaForTokenClassification from fumikawa +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_fumikawa +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_fumikawa` is a English model originally trained by fumikawa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_fumikawa_en_5.5.0_3.0_1725317823121.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_fumikawa_en_5.5.0_3.0_1725317823121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_fumikawa","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_fumikawa", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_fumikawa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/fumikawa/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_fumikawa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_fumikawa_pipeline_en.md new file mode 100644 index 00000000000000..764144603c2731 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_fumikawa_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_fumikawa_pipeline pipeline XlmRoBertaForTokenClassification from fumikawa +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_fumikawa_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_fumikawa_pipeline` is a English model originally trained by fumikawa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_fumikawa_pipeline_en_5.5.0_3.0_1725317893777.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_fumikawa_pipeline_en_5.5.0_3.0_1725317893777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_fumikawa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_fumikawa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_fumikawa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/fumikawa/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_g22tk021_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_g22tk021_en.md new file mode 100644 index 00000000000000..e4f476468bf78b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_g22tk021_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_g22tk021 XlmRoBertaForTokenClassification from g22tk021 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_g22tk021 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_g22tk021` is a English model originally trained by g22tk021. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_g22tk021_en_5.5.0_3.0_1725316701894.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_g22tk021_en_5.5.0_3.0_1725316701894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_g22tk021","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_g22tk021", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_g22tk021| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/g22tk021/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_heerak_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_heerak_en.md new file mode 100644 index 00000000000000..6c973b40548e7e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_heerak_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_heerak XlmRoBertaForTokenClassification from Heerak +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_heerak +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_heerak` is a English model originally trained by Heerak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_heerak_en_5.5.0_3.0_1725316971235.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_heerak_en_5.5.0_3.0_1725316971235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_heerak","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_heerak", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_heerak| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|851.7 MB| + +## References + +https://huggingface.co/Heerak/xlm-roberta-base-finetuned_panx_de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_heerak_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_heerak_pipeline_en.md new file mode 100644 index 00000000000000..3832757c7b5bce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_heerak_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_heerak_pipeline pipeline XlmRoBertaForTokenClassification from Heerak +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_heerak_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_heerak_pipeline` is a English model originally trained by Heerak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_heerak_pipeline_en_5.5.0_3.0_1725317047044.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_heerak_pipeline_en_5.5.0_3.0_1725317047044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_heerak_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_heerak_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_heerak_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|851.8 MB| + +## References + +https://huggingface.co/Heerak/xlm-roberta-base-finetuned_panx_de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_maxfrax_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_maxfrax_pipeline_en.md new file mode 100644 index 00000000000000..8937bd6fd27416 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_maxfrax_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_maxfrax_pipeline pipeline XlmRoBertaForTokenClassification from maxfrax +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_maxfrax_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_maxfrax_pipeline` is a English model originally trained by maxfrax. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_maxfrax_pipeline_en_5.5.0_3.0_1725317144349.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_maxfrax_pipeline_en_5.5.0_3.0_1725317144349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_maxfrax_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_maxfrax_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_maxfrax_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|840.8 MB| + +## References + +https://huggingface.co/maxfrax/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_noveled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_noveled_pipeline_en.md new file mode 100644 index 00000000000000..a680c13b2ba7f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_noveled_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_noveled_pipeline pipeline XlmRoBertaForTokenClassification from Noveled +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_noveled_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_noveled_pipeline` is a English model originally trained by Noveled. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_noveled_pipeline_en_5.5.0_3.0_1725316877883.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_noveled_pipeline_en_5.5.0_3.0_1725316877883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_noveled_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_noveled_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_noveled_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|832.1 MB| + +## References + +https://huggingface.co/Noveled/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_old_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_old_en.md new file mode 100644 index 00000000000000..5c6257d665bbd4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_old_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_old XlmRoBertaForTokenClassification from youngbreadho +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_old +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_old` is a English model originally trained by youngbreadho. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_old_en_5.5.0_3.0_1725315935078.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_old_en_5.5.0_3.0_1725315935078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_old","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_old", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_old| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/youngbreadho/xlm-roberta-base-finetuned-panx-de_old \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_old_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_old_pipeline_en.md new file mode 100644 index 00000000000000..1ee9c692f16d8d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_old_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_old_pipeline pipeline XlmRoBertaForTokenClassification from youngbreadho +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_old_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_old_pipeline` is a English model originally trained by youngbreadho. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_old_pipeline_en_5.5.0_3.0_1725316004534.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_old_pipeline_en_5.5.0_3.0_1725316004534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_old_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_old_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_old_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/youngbreadho/xlm-roberta-base-finetuned-panx-de_old + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_scionk_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_scionk_en.md new file mode 100644 index 00000000000000..21bdf20c83385d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_scionk_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_scionk XlmRoBertaForTokenClassification from scionk +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_scionk +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_scionk` is a English model originally trained by scionk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_scionk_en_5.5.0_3.0_1725307700860.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_scionk_en_5.5.0_3.0_1725307700860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_scionk","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_scionk", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_scionk| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|827.0 MB| + +## References + +https://huggingface.co/scionk/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_si0005hp_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_si0005hp_en.md new file mode 100644 index 00000000000000..284a622b96ed05 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_si0005hp_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_si0005hp XlmRoBertaForTokenClassification from si0005hp +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_si0005hp +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_si0005hp` is a English model originally trained by si0005hp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_si0005hp_en_5.5.0_3.0_1725317442919.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_si0005hp_en_5.5.0_3.0_1725317442919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_si0005hp","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_si0005hp", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_si0005hp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/si0005hp/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_si0005hp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_si0005hp_pipeline_en.md new file mode 100644 index 00000000000000..90184942d89215 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_si0005hp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_si0005hp_pipeline pipeline XlmRoBertaForTokenClassification from si0005hp +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_si0005hp_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_si0005hp_pipeline` is a English model originally trained by si0005hp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_si0005hp_pipeline_en_5.5.0_3.0_1725317516750.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_si0005hp_pipeline_en_5.5.0_3.0_1725317516750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_si0005hp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_si0005hp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_si0005hp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/si0005hp/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_italian_hirosay_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_italian_hirosay_en.md new file mode 100644 index 00000000000000..04c7093c53b16c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_italian_hirosay_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_italian_hirosay XlmRoBertaForTokenClassification from hirosay +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_italian_hirosay +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_hirosay` is a English model originally trained by hirosay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_hirosay_en_5.5.0_3.0_1725317347563.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_hirosay_en_5.5.0_3.0_1725317347563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_hirosay","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_hirosay", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_italian_hirosay| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|828.6 MB| + +## References + +https://huggingface.co/hirosay/xlm-roberta-base-finetuned-panx-it \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_italian_hirosay_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_italian_hirosay_pipeline_en.md new file mode 100644 index 00000000000000..bc82e0cdd5fe79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_italian_hirosay_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_italian_hirosay_pipeline pipeline XlmRoBertaForTokenClassification from hirosay +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_italian_hirosay_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_hirosay_pipeline` is a English model originally trained by hirosay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_hirosay_pipeline_en_5.5.0_3.0_1725317436464.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_hirosay_pipeline_en_5.5.0_3.0_1725317436464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_hirosay_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_hirosay_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_italian_hirosay_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|828.6 MB| + +## References + +https://huggingface.co/hirosay/xlm-roberta-base-finetuned-panx-it + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_visquad2_13_3_2023_6_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_visquad2_13_3_2023_6_en.md new file mode 100644 index 00000000000000..b825dfa3d8c097 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_visquad2_13_3_2023_6_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_visquad2_13_3_2023_6 XlmRoBertaForQuestionAnswering from jluckyboyj +author: John Snow Labs +name: xlm_roberta_base_finetuned_visquad2_13_3_2023_6 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_visquad2_13_3_2023_6` is a English model originally trained by jluckyboyj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_visquad2_13_3_2023_6_en_5.5.0_3.0_1725254692552.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_visquad2_13_3_2023_6_en_5.5.0_3.0_1725254692552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_visquad2_13_3_2023_6","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_visquad2_13_3_2023_6", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_visquad2_13_3_2023_6| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|853.1 MB| + +## References + +https://huggingface.co/jluckyboyj/xlm-roberta-base-finetuned-visquad2-13-3-2023-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_visquad2_13_3_2023_6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_visquad2_13_3_2023_6_pipeline_en.md new file mode 100644 index 00000000000000..0ff207f9c1b342 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_visquad2_13_3_2023_6_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_visquad2_13_3_2023_6_pipeline pipeline XlmRoBertaForQuestionAnswering from jluckyboyj +author: John Snow Labs +name: xlm_roberta_base_finetuned_visquad2_13_3_2023_6_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_visquad2_13_3_2023_6_pipeline` is a English model originally trained by jluckyboyj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_visquad2_13_3_2023_6_pipeline_en_5.5.0_3.0_1725254759274.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_visquad2_13_3_2023_6_pipeline_en_5.5.0_3.0_1725254759274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_visquad2_13_3_2023_6_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_visquad2_13_3_2023_6_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_visquad2_13_3_2023_6_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.1 MB| + +## References + +https://huggingface.co/jluckyboyj/xlm-roberta-base-finetuned-visquad2-13-3-2023-6 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_en.md new file mode 100644 index 00000000000000..075175fa27db71 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_ft_udpos213_top6lang_southern_sotho XlmRoBertaForTokenClassification from iceman2434 +author: John Snow Labs +name: xlm_roberta_base_ft_udpos213_top6lang_southern_sotho +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ft_udpos213_top6lang_southern_sotho` is a English model originally trained by iceman2434. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_en_5.5.0_3.0_1725316075816.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_en_5.5.0_3.0_1725316075816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_ft_udpos213_top6lang_southern_sotho","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_ft_udpos213_top6lang_southern_sotho", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_ft_udpos213_top6lang_southern_sotho| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|801.6 MB| + +## References + +https://huggingface.co/iceman2434/xlm-roberta-base_ft_udpos213-top6lang-st \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_pipeline_en.md new file mode 100644 index 00000000000000..731d4628e80e53 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_pipeline pipeline XlmRoBertaForTokenClassification from iceman2434 +author: John Snow Labs +name: xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_pipeline` is a English model originally trained by iceman2434. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_pipeline_en_5.5.0_3.0_1725316210457.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_pipeline_en_5.5.0_3.0_1725316210457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_ft_udpos213_top6lang_southern_sotho_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|801.6 MB| + +## References + +https://huggingface.co/iceman2434/xlm-roberta-base_ft_udpos213-top6lang-st + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_squad2_finetuned_squad2_covidqa_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_squad2_finetuned_squad2_covidqa_en.md new file mode 100644 index 00000000000000..84d47be41d57ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_squad2_finetuned_squad2_covidqa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English xlm_roberta_base_squad2_finetuned_squad2_covidqa XlmRoBertaForQuestionAnswering from chiendvhust +author: John Snow Labs +name: xlm_roberta_base_squad2_finetuned_squad2_covidqa +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_squad2_finetuned_squad2_covidqa` is a English model originally trained by chiendvhust. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad2_finetuned_squad2_covidqa_en_5.5.0_3.0_1725235940373.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad2_finetuned_squad2_covidqa_en_5.5.0_3.0_1725235940373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_squad2_finetuned_squad2_covidqa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_squad2_finetuned_squad2_covidqa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_squad2_finetuned_squad2_covidqa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|876.8 MB| + +## References + +https://huggingface.co/chiendvhust/xlm-roberta-base-squad2-finetuned-squad2-covidQA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_squad2_finetuned_squad2_covidqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_squad2_finetuned_squad2_covidqa_pipeline_en.md new file mode 100644 index 00000000000000..895029f7af7661 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_squad2_finetuned_squad2_covidqa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_base_squad2_finetuned_squad2_covidqa_pipeline pipeline XlmRoBertaForQuestionAnswering from chiendvhust +author: John Snow Labs +name: xlm_roberta_base_squad2_finetuned_squad2_covidqa_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_squad2_finetuned_squad2_covidqa_pipeline` is a English model originally trained by chiendvhust. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad2_finetuned_squad2_covidqa_pipeline_en_5.5.0_3.0_1725236005464.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad2_finetuned_squad2_covidqa_pipeline_en_5.5.0_3.0_1725236005464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_squad2_finetuned_squad2_covidqa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_squad2_finetuned_squad2_covidqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_squad2_finetuned_squad2_covidqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|876.8 MB| + +## References + +https://huggingface.co/chiendvhust/xlm-roberta-base-squad2-finetuned-squad2-covidQA + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_Part_1_XLM_Model_E1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_Part_1_XLM_Model_E1_pipeline_en.md new file mode 100644 index 00000000000000..71262cdc44dc8a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_Part_1_XLM_Model_E1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_Part_1_XLM_Model_E1_pipeline pipeline XlmRoBertaForQuestionAnswering from horsbug98 +author: John Snow Labs +name: xlm_roberta_qa_Part_1_XLM_Model_E1_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_Part_1_XLM_Model_E1_pipeline` is a English model originally trained by horsbug98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_Part_1_XLM_Model_E1_pipeline_en_5.5.0_3.0_1725255141638.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_Part_1_XLM_Model_E1_pipeline_en_5.5.0_3.0_1725255141638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_Part_1_XLM_Model_E1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_Part_1_XLM_Model_E1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_Part_1_XLM_Model_E1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|877.4 MB| + +## References + +https://huggingface.co/horsbug98/Part_1_XLM_Model_E1 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_addi_chamorro_xlm_r_pipeline_ch.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_addi_chamorro_xlm_r_pipeline_ch.md new file mode 100644 index 00000000000000..300e6171708d46 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_addi_chamorro_xlm_r_pipeline_ch.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Chamorro xlm_roberta_qa_addi_chamorro_xlm_r_pipeline pipeline XlmRoBertaForQuestionAnswering from Gantenbein +author: John Snow Labs +name: xlm_roberta_qa_addi_chamorro_xlm_r_pipeline +date: 2024-09-02 +tags: [ch, open_source, pipeline, onnx] +task: Question Answering +language: ch +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_addi_chamorro_xlm_r_pipeline` is a Chamorro model originally trained by Gantenbein. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_chamorro_xlm_r_pipeline_ch_5.5.0_3.0_1725254145245.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_chamorro_xlm_r_pipeline_ch_5.5.0_3.0_1725254145245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_addi_chamorro_xlm_r_pipeline", lang = "ch") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_addi_chamorro_xlm_r_pipeline", lang = "ch") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_addi_chamorro_xlm_r_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ch| +|Size:|776.3 MB| + +## References + +https://huggingface.co/Gantenbein/ADDI-CH-XLM-R + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_addi_finnish_xlm_r_fi.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_addi_finnish_xlm_r_fi.md new file mode 100644 index 00000000000000..6f38e2da0b7bee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_addi_finnish_xlm_r_fi.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Finnish xlm_roberta_qa_addi_finnish_xlm_r XlmRoBertaForQuestionAnswering from Gantenbein +author: John Snow Labs +name: xlm_roberta_qa_addi_finnish_xlm_r +date: 2024-09-02 +tags: [fi, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: fi +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_addi_finnish_xlm_r` is a Finnish model originally trained by Gantenbein. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_finnish_xlm_r_fi_5.5.0_3.0_1725236205799.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_finnish_xlm_r_fi_5.5.0_3.0_1725236205799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_addi_finnish_xlm_r","fi") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_addi_finnish_xlm_r", "fi") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_addi_finnish_xlm_r| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|fi| +|Size:|777.3 MB| + +## References + +https://huggingface.co/Gantenbein/ADDI-FI-XLM-R \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_addi_finnish_xlm_r_pipeline_fi.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_addi_finnish_xlm_r_pipeline_fi.md new file mode 100644 index 00000000000000..06d8c563e03bea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_addi_finnish_xlm_r_pipeline_fi.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Finnish xlm_roberta_qa_addi_finnish_xlm_r_pipeline pipeline XlmRoBertaForQuestionAnswering from Gantenbein +author: John Snow Labs +name: xlm_roberta_qa_addi_finnish_xlm_r_pipeline +date: 2024-09-02 +tags: [fi, open_source, pipeline, onnx] +task: Question Answering +language: fi +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_addi_finnish_xlm_r_pipeline` is a Finnish model originally trained by Gantenbein. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_finnish_xlm_r_pipeline_fi_5.5.0_3.0_1725236347329.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_finnish_xlm_r_pipeline_fi_5.5.0_3.0_1725236347329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_addi_finnish_xlm_r_pipeline", lang = "fi") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_addi_finnish_xlm_r_pipeline", lang = "fi") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_addi_finnish_xlm_r_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fi| +|Size:|777.3 MB| + +## References + +https://huggingface.co/Gantenbein/ADDI-FI-XLM-R + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_en.md new file mode 100644 index 00000000000000..dca5128ef84309 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from teacookies) +author: John Snow Labs +name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899 +date: 2024-09-02 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-more_fine_tune_24465520-26265899` is a English model originally trained by `teacookies`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_en_5.5.0_3.0_1725235403968.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_en_5.5.0_3.0_1725235403968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.xlm_roberta.fine_tune_24465520_26265899").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|888.2 MB| + +## References + +References + +- https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265899 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_pipeline_en.md new file mode 100644 index 00000000000000..50345a59b7115d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies +author: John Snow Labs +name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_pipeline` is a English model originally trained by teacookies. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_pipeline_en_5.5.0_3.0_1725235481300.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_pipeline_en_5.5.0_3.0_1725235481300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265899_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|888.2 MB| + +## References + +https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265899 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_en.md new file mode 100644 index 00000000000000..f1294ef31ea1cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from teacookies) +author: John Snow Labs +name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903 +date: 2024-09-02 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-more_fine_tune_24465520-26265903` is a English model originally trained by `teacookies`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_en_5.5.0_3.0_1725253797272.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_en_5.5.0_3.0_1725253797272.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.xlm_roberta.fine_tune_24465520_26265903").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|888.2 MB| + +## References + +References + +- https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265903 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_pipeline_en.md new file mode 100644 index 00000000000000..e460d787bcd418 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies +author: John Snow Labs +name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_pipeline` is a English model originally trained by teacookies. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_pipeline_en_5.5.0_3.0_1725253867322.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_pipeline_en_5.5.0_3.0_1725253867322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265903_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|888.2 MB| + +## References + +https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265903 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_en.md new file mode 100644 index 00000000000000..9071f08d5cf011 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from teacookies) +author: John Snow Labs +name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906 +date: 2024-09-02 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-more_fine_tune_24465520-26265906` is a English model originally trained by `teacookies`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_en_5.5.0_3.0_1725235877770.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_en_5.5.0_3.0_1725235877770.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.xlm_roberta.fine_tune_24465520_26265906").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|888.2 MB| + +## References + +References + +- https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265906 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_pipeline_en.md new file mode 100644 index 00000000000000..4356a09f4440d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies +author: John Snow Labs +name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_pipeline` is a English model originally trained by teacookies. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_pipeline_en_5.5.0_3.0_1725235950419.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_pipeline_en_5.5.0_3.0_1725235950419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265906_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|888.2 MB| + +## References + +https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265906 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_en.md new file mode 100644 index 00000000000000..77e39c04cb38aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from teacookies) +author: John Snow Labs +name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465514 +date: 2024-09-02 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-roberta-base-squad2-24465514` is a English model originally trained by `teacookies`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_en_5.5.0_3.0_1725254063381.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_en_5.5.0_3.0_1725254063381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465514","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465514","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squadv2.xlm_roberta.base_24465514.by_teacookies").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465514| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|887.3 MB| + +## References + +References + +- https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465514 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_pipeline_en.md new file mode 100644 index 00000000000000..b01675cafb7bf9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies +author: John Snow Labs +name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_pipeline` is a English model originally trained by teacookies. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_pipeline_en_5.5.0_3.0_1725254134732.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_pipeline_en_5.5.0_3.0_1725254134732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465514_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|887.3 MB| + +## References + +https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465514 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_pipeline_en.md new file mode 100644 index 00000000000000..dde2148889e29f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies +author: John Snow Labs +name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_pipeline` is a English model originally trained by teacookies. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_pipeline_en_5.5.0_3.0_1725254028435.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_pipeline_en_5.5.0_3.0_1725254028435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|887.2 MB| + +## References + +https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465522 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_en.md new file mode 100644 index 00000000000000..9fb209e89de901 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from teacookies) +author: John Snow Labs +name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465524 +date: 2024-09-02 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-roberta-base-squad2-24465524` is a English model originally trained by `teacookies`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_en_5.5.0_3.0_1725254720061.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_en_5.5.0_3.0_1725254720061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465524","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465524","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squadv2.xlm_roberta.base_24465524.by_teacookies").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465524| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|887.3 MB| + +## References + +References + +- https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465524 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_pipeline_en.md new file mode 100644 index 00000000000000..103bc8d4f173e3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies +author: John Snow Labs +name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_pipeline` is a English model originally trained by teacookies. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_pipeline_en_5.5.0_3.0_1725254790351.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_pipeline_en_5.5.0_3.0_1725254790351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465524_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|887.3 MB| + +## References + +https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465524 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_en.md new file mode 100644 index 00000000000000..1412c89e4da171 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from teacookies) +author: John Snow Labs +name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465525 +date: 2024-09-02 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-roberta-base-squad2-24465525` is a English model originally trained by `teacookies`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_en_5.5.0_3.0_1725253240422.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_en_5.5.0_3.0_1725253240422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465525","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465525","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squadv2.xlm_roberta.base_24465525.by_teacookies").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465525| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|887.3 MB| + +## References + +References + +- https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465525 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_pipeline_en.md new file mode 100644 index 00000000000000..382b277a81a550 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies +author: John Snow Labs +name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_pipeline` is a English model originally trained by teacookies. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_pipeline_en_5.5.0_3.0_1725253311735.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_pipeline_en_5.5.0_3.0_1725253311735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465525_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|887.3 MB| + +## References + +https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465525 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_arabic_ar.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_arabic_ar.md new file mode 100644 index 00000000000000..12dd4ff48f6158 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_arabic_ar.md @@ -0,0 +1,106 @@ +--- +layout: model +title: Arabic XlmRoBertaForQuestionAnswering (from bhavikardeshna) +author: John Snow Labs +name: xlm_roberta_qa_xlm_roberta_base_arabic +date: 2024-09-02 +tags: [ar, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-arabic` is a Arabic model originally trained by `bhavikardeshna`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_arabic_ar_5.5.0_3.0_1725235395653.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_arabic_ar_5.5.0_3.0_1725235395653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_base_arabic","ar") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_xlm_roberta_base_arabic","ar") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("ar.answer_question.xlm_roberta.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlm_roberta_base_arabic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|ar| +|Size:|884.1 MB| + +## References + +References + +- https://huggingface.co/bhavikardeshna/xlm-roberta-base-arabic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_german_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_german_de.md new file mode 100644 index 00000000000000..b1f6c7101685fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_german_de.md @@ -0,0 +1,106 @@ +--- +layout: model +title: German XlmRoBertaForQuestionAnswering (from bhavikardeshna) +author: John Snow Labs +name: xlm_roberta_qa_xlm_roberta_base_german +date: 2024-09-02 +tags: [de, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-german` is a German model originally trained by `bhavikardeshna`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_german_de_5.5.0_3.0_1725254209852.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_german_de_5.5.0_3.0_1725254209852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_base_german","de") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_xlm_roberta_base_german","de") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.answer_question.xlm_roberta.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlm_roberta_base_german| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|de| +|Size:|882.7 MB| + +## References + +References + +- https://huggingface.co/bhavikardeshna/xlm-roberta-base-german \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_german_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_german_pipeline_de.md new file mode 100644 index 00000000000000..e0615b5d6f472d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_german_pipeline_de.md @@ -0,0 +1,69 @@ +--- +layout: model +title: German xlm_roberta_qa_xlm_roberta_base_german_pipeline pipeline XlmRoBertaForQuestionAnswering from bhavikardeshna +author: John Snow Labs +name: xlm_roberta_qa_xlm_roberta_base_german_pipeline +date: 2024-09-02 +tags: [de, open_source, pipeline, onnx] +task: Question Answering +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_base_german_pipeline` is a German model originally trained by bhavikardeshna. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_german_pipeline_de_5.5.0_3.0_1725254274044.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_german_pipeline_de_5.5.0_3.0_1725254274044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_german_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_german_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlm_roberta_base_german_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|882.7 MB| + +## References + +https://huggingface.co/bhavikardeshna/xlm-roberta-base-german + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_en.md new file mode 100644 index 00000000000000..5b21a328b753d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from ncduy) +author: John Snow Labs +name: xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small +date: 2024-09-02 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-squad2-distilled-finetuned-chaii-small` is a English model originally trained by `ncduy`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_en_5.5.0_3.0_1725253420817.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_en_5.5.0_3.0_1725253420817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.squadv2_chaii.xlm_roberta.distilled_base_small").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|880.8 MB| + +## References + +References + +- https://huggingface.co/ncduy/xlm-roberta-base-squad2-distilled-finetuned-chaii-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_pipeline_en.md new file mode 100644 index 00000000000000..d1b57d3b737d46 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_pipeline pipeline XlmRoBertaForQuestionAnswering from ncduy +author: John Snow Labs +name: xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_pipeline` is a English model originally trained by ncduy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_pipeline_en_5.5.0_3.0_1725253494487.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_pipeline_en_5.5.0_3.0_1725253494487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|880.8 MB| + +## References + +https://huggingface.co/ncduy/xlm-roberta-base-squad2-distilled-finetuned-chaii-small + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_squad2_distilled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_squad2_distilled_pipeline_en.md new file mode 100644 index 00000000000000..67050fc3935d77 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_squad2_distilled_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_xlm_roberta_base_squad2_distilled_pipeline pipeline XlmRoBertaForQuestionAnswering from deepset +author: John Snow Labs +name: xlm_roberta_qa_xlm_roberta_base_squad2_distilled_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_base_squad2_distilled_pipeline` is a English model originally trained by deepset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_squad2_distilled_pipeline_en_5.5.0_3.0_1725255128945.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_squad2_distilled_pipeline_en_5.5.0_3.0_1725255128945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_squad2_distilled_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_squad2_distilled_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlm_roberta_base_squad2_distilled_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/deepset/xlm-roberta-base-squad2-distilled + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_ckpt_95000_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_ckpt_95000_en.md new file mode 100644 index 00000000000000..ee874552444d12 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_ckpt_95000_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English XlmRoBertaForQuestionAnswering (from jeew) +author: John Snow Labs +name: xlm_roberta_qa_xlm_roberta_ckpt_95000 +date: 2024-09-02 +tags: [en, open_source, question_answering, xlmroberta, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-ckpt-95000` is a English model originally trained by `jeew`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_ckpt_95000_en_5.5.0_3.0_1725253600639.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_ckpt_95000_en_5.5.0_3.0_1725253600639.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_ckpt_95000","en") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer") \ +.setCaseSensitive(True) + +pipeline = Pipeline().setStages([ +document_assembler, +spanClassifier +]) + +example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context") + +result = pipeline.fit(example).transform(example) +``` +```scala +val document = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering +.pretrained("xlm_roberta_qa_xlm_roberta_ckpt_95000","en") +.setInputCols(Array("document_question", "document_context")) +.setOutputCol("answer") +.setCaseSensitive(true) +.setMaxSentenceLength(512) + +val pipeline = new Pipeline().setStages(Array(document, spanClassifier)) + +val example = Seq( +("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."), +("What's my name?", "My name is Clara and I live in Berkeley.")) +.toDF("question", "context") + +val result = pipeline.fit(example).transform(example) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.answer_question.xlm_roberta.by_jeew").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlm_roberta_ckpt_95000| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|807.4 MB| + +## References + +References + +- https://huggingface.co/jeew/xlm-roberta-ckpt-95000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_ckpt_95000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_ckpt_95000_pipeline_en.md new file mode 100644 index 00000000000000..daa636b4273fa1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_ckpt_95000_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlm_roberta_qa_xlm_roberta_ckpt_95000_pipeline pipeline XlmRoBertaForQuestionAnswering from jeew +author: John Snow Labs +name: xlm_roberta_qa_xlm_roberta_ckpt_95000_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_ckpt_95000_pipeline` is a English model originally trained by jeew. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_ckpt_95000_pipeline_en_5.5.0_3.0_1725253735999.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_ckpt_95000_pipeline_en_5.5.0_3.0_1725253735999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_ckpt_95000_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_ckpt_95000_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlm_roberta_ckpt_95000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|807.4 MB| + +## References + +https://huggingface.co/jeew/xlm-roberta-ckpt-95000 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_fr.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_fr.md new file mode 100644 index 00000000000000..8b007972f049c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_fr.md @@ -0,0 +1,86 @@ +--- +layout: model +title: French xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan XlmRoBertaForQuestionAnswering from saattrupdan +author: John Snow Labs +name: xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan +date: 2024-09-02 +tags: [fr, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan` is a French model originally trained by saattrupdan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_fr_5.5.0_3.0_1725235794020.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_fr_5.5.0_3.0_1725235794020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan","fr") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan", "fr") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|fr| +|Size:|873.3 MB| + +## References + +https://huggingface.co/saattrupdan/xlmr-base-texas-squad-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_pipeline_fr.md new file mode 100644 index 00000000000000..c4845bb9a6f2bf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_pipeline_fr.md @@ -0,0 +1,69 @@ +--- +layout: model +title: French xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_pipeline pipeline XlmRoBertaForQuestionAnswering from saattrupdan +author: John Snow Labs +name: xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_pipeline +date: 2024-09-02 +tags: [fr, open_source, pipeline, onnx] +task: Question Answering +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_pipeline` is a French model originally trained by saattrupdan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_pipeline_fr_5.5.0_3.0_1725235862679.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_pipeline_fr_5.5.0_3.0_1725235862679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_qa_xlmr_base_texas_squad_french_french_saattrupdan_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|873.3 MB| + +## References + +https://huggingface.co/saattrupdan/xlmr-base-texas-squad-fr + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmr_base_igbo_5e_5_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmr_base_igbo_5e_5_en.md new file mode 100644 index 00000000000000..b426cb9c0627e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmr_base_igbo_5e_5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlmr_base_igbo_5e_5 XlmRoBertaForTokenClassification from grace-pro +author: John Snow Labs +name: xlmr_base_igbo_5e_5 +date: 2024-09-02 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_base_igbo_5e_5` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_base_igbo_5e_5_en_5.5.0_3.0_1725316562162.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_base_igbo_5e_5_en_5.5.0_3.0_1725316562162.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmr_base_igbo_5e_5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmr_base_igbo_5e_5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmr_base_igbo_5e_5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|867.0 MB| + +## References + +https://huggingface.co/grace-pro/xlmr-base-igbo-5e-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmr_base_igbo_5e_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmr_base_igbo_5e_5_pipeline_en.md new file mode 100644 index 00000000000000..4d2b2ab6f83263 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmr_base_igbo_5e_5_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlmr_base_igbo_5e_5_pipeline pipeline XlmRoBertaForTokenClassification from grace-pro +author: John Snow Labs +name: xlmr_base_igbo_5e_5_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_base_igbo_5e_5_pipeline` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_base_igbo_5e_5_pipeline_en_5.5.0_3.0_1725316627277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_base_igbo_5e_5_pipeline_en_5.5.0_3.0_1725316627277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmr_base_igbo_5e_5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmr_base_igbo_5e_5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmr_base_igbo_5e_5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|867.0 MB| + +## References + +https://huggingface.co/grace-pro/xlmr-base-igbo-5e-5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmr_base_trained_panx_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmr_base_trained_panx_english_pipeline_en.md new file mode 100644 index 00000000000000..01d4ad462cd10a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmr_base_trained_panx_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlmr_base_trained_panx_english_pipeline pipeline XlmRoBertaForTokenClassification from DeepaPeri +author: John Snow Labs +name: xlmr_base_trained_panx_english_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_base_trained_panx_english_pipeline` is a English model originally trained by DeepaPeri. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_base_trained_panx_english_pipeline_en_5.5.0_3.0_1725316142457.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_base_trained_panx_english_pipeline_en_5.5.0_3.0_1725316142457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmr_base_trained_panx_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmr_base_trained_panx_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmr_base_trained_panx_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|797.4 MB| + +## References + +https://huggingface.co/DeepaPeri/XLMR-BASE-TRAINED-PANX-en + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_finetuned_tydiqa_ben_tel_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_finetuned_tydiqa_ben_tel_en.md new file mode 100644 index 00000000000000..2ad6feb2080492 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_finetuned_tydiqa_ben_tel_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English xlmroberta_finetuned_tydiqa_ben_tel XlmRoBertaForQuestionAnswering from Auracle7 +author: John Snow Labs +name: xlmroberta_finetuned_tydiqa_ben_tel +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_finetuned_tydiqa_ben_tel` is a English model originally trained by Auracle7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_finetuned_tydiqa_ben_tel_en_5.5.0_3.0_1725235261521.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_finetuned_tydiqa_ben_tel_en_5.5.0_3.0_1725235261521.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlmroberta_finetuned_tydiqa_ben_tel","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlmroberta_finetuned_tydiqa_ben_tel", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_finetuned_tydiqa_ben_tel| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|924.3 MB| + +## References + +https://huggingface.co/Auracle7/XLMRoberta-finetuned-TyDIQA-Ben-Tel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_finetuned_tydiqa_ben_tel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_finetuned_tydiqa_ben_tel_pipeline_en.md new file mode 100644 index 00000000000000..8599e97f088d90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_finetuned_tydiqa_ben_tel_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlmroberta_finetuned_tydiqa_ben_tel_pipeline pipeline XlmRoBertaForQuestionAnswering from Auracle7 +author: John Snow Labs +name: xlmroberta_finetuned_tydiqa_ben_tel_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_finetuned_tydiqa_ben_tel_pipeline` is a English model originally trained by Auracle7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_finetuned_tydiqa_ben_tel_pipeline_en_5.5.0_3.0_1725235325658.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_finetuned_tydiqa_ben_tel_pipeline_en_5.5.0_3.0_1725235325658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_finetuned_tydiqa_ben_tel_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_finetuned_tydiqa_ben_tel_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_finetuned_tydiqa_ben_tel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|924.3 MB| + +## References + +https://huggingface.co/Auracle7/XLMRoberta-finetuned-TyDIQA-Ben-Tel + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_pipeline_rw.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_pipeline_rw.md new file mode 100644 index 00000000000000..0c5ab19a553e4d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_pipeline_rw.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Kinyarwanda xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_pipeline pipeline XlmRoBertaForTokenClassification from mbeukman +author: John Snow Labs +name: xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_pipeline +date: 2024-09-02 +tags: [rw, open_source, pipeline, onnx] +task: Named Entity Recognition +language: rw +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_pipeline` is a Kinyarwanda model originally trained by mbeukman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_pipeline_rw_5.5.0_3.0_1725308431316.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_pipeline_rw_5.5.0_3.0_1725308431316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_pipeline", lang = "rw") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_pipeline", lang = "rw") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|rw| +|Size:|1.0 GB| + +## References + +https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-kinyarwanda-finetuned-ner-kinyarwanda + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_rw.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_rw.md new file mode 100644 index 00000000000000..b36ff4f806debe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_rw.md @@ -0,0 +1,115 @@ +--- +layout: model +title: Kinyarwanda XLMRobertaForTokenClassification Base Cased model (from mbeukman) +author: John Snow Labs +name: xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand +date: 2024-09-02 +tags: [rw, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: rw +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-kinyarwanda-finetuned-ner-kinyarwanda` is a Kinyarwanda model originally trained by `mbeukman`. + +## Predicted Entities + +`PER`, `DATE`, `ORG`, `LOC` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_rw_5.5.0_3.0_1725308378320.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand_rw_5.5.0_3.0_1725308378320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand","rw") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand","rw") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("rw.ner.xlmr_roberta.base_finetuned").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_finetuned_kinyarwanda_finetuned_ner_kinyarwand| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|rw| +|Size:|1.0 GB| + +## References + +References + +- https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-kinyarwanda-finetuned-ner-kinyarwanda +- https://arxiv.org/abs/2103.11811 +- https://github.com/Michael-Beukman/NERTransfer +- https://github.com/masakhane-io/masakhane-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_panx_german_data_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_panx_german_data_de.md new file mode 100644 index 00000000000000..df591f3bc4e619 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_panx_german_data_de.md @@ -0,0 +1,94 @@ +--- +layout: model +title: German xlmroberta_ner_base_finetuned_panx_german_data XlmRoBertaForTokenClassification from moghis +author: John Snow Labs +name: xlmroberta_ner_base_finetuned_panx_german_data +date: 2024-09-02 +tags: [de, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_finetuned_panx_german_data` is a German model originally trained by moghis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_panx_german_data_de_5.5.0_3.0_1725308117015.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_panx_german_data_de_5.5.0_3.0_1725308117015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_panx_german_data","de") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_panx_german_data", "de") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_finetuned_panx_german_data| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|853.8 MB| + +## References + +https://huggingface.co/moghis/xlm-roberta-base-finetuned-panx-de-data \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_panx_german_data_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_panx_german_data_pipeline_de.md new file mode 100644 index 00000000000000..a6b20e36a4e190 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_panx_german_data_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German xlmroberta_ner_base_finetuned_panx_german_data_pipeline pipeline XlmRoBertaForTokenClassification from moghis +author: John Snow Labs +name: xlmroberta_ner_base_finetuned_panx_german_data_pipeline +date: 2024-09-02 +tags: [de, open_source, pipeline, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_finetuned_panx_german_data_pipeline` is a German model originally trained by moghis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_panx_german_data_pipeline_de_5.5.0_3.0_1725308188861.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_panx_german_data_pipeline_de_5.5.0_3.0_1725308188861.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_base_finetuned_panx_german_data_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_base_finetuned_panx_german_data_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_finetuned_panx_german_data_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|853.8 MB| + +## References + +https://huggingface.co/moghis/xlm-roberta-base-finetuned-panx-de-data + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_peyma_fa.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_peyma_fa.md new file mode 100644 index 00000000000000..18fcdc8ad888a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_peyma_fa.md @@ -0,0 +1,112 @@ +--- +layout: model +title: Persian XLMRobertaForTokenClassification Base Cased model (from BK-V) +author: John Snow Labs +name: xlmroberta_ner_base_finetuned_peyma +date: 2024-09-02 +tags: [fa, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: fa +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-peyma-fa` is a Persian model originally trained by `BK-V`. + +## Predicted Entities + +`LOC`, `PER`, `MON`, `ORG`, `TIM`, `PCT`, `DAT` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_peyma_fa_5.5.0_3.0_1725309203226.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_peyma_fa_5.5.0_3.0_1725309203226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_peyma","fa") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_peyma","fa") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("fa.ner.xlmr_roberta.peyma.base_finetuned").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_finetuned_peyma| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|fa| +|Size:|842.3 MB| + +## References + +References + +- https://huggingface.co/BK-V/xlm-roberta-base-finetuned-peyma-fa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_peyma_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_peyma_pipeline_fa.md new file mode 100644 index 00000000000000..e5a999b618cfa6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_finetuned_peyma_pipeline_fa.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Persian xlmroberta_ner_base_finetuned_peyma_pipeline pipeline XlmRoBertaForTokenClassification from BK-V +author: John Snow Labs +name: xlmroberta_ner_base_finetuned_peyma_pipeline +date: 2024-09-02 +tags: [fa, open_source, pipeline, onnx] +task: Named Entity Recognition +language: fa +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_finetuned_peyma_pipeline` is a Persian model originally trained by BK-V. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_peyma_pipeline_fa_5.5.0_3.0_1725309267541.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_peyma_pipeline_fa_5.5.0_3.0_1725309267541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_base_finetuned_peyma_pipeline", lang = "fa") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_base_finetuned_peyma_pipeline", lang = "fa") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_finetuned_peyma_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fa| +|Size:|842.3 MB| + +## References + +https://huggingface.co/BK-V/xlm-roberta-base-finetuned-peyma-fa + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_uncased_bionlp2004_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_uncased_bionlp2004_en.md new file mode 100644 index 00000000000000..03708576b8cb89 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_uncased_bionlp2004_en.md @@ -0,0 +1,113 @@ +--- +layout: model +title: English XLMRobertaForTokenClassification Base Uncased model (from tner) +author: John Snow Labs +name: xlmroberta_ner_base_uncased_bionlp2004 +date: 2024-09-02 +tags: [en, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-uncased-bionlp2004` is a English model originally trained by `tner`. + +## Predicted Entities + +`protein`, `dna`, `cell line`, `rna`, `cell type` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_uncased_bionlp2004_en_5.5.0_3.0_1725307623832.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_uncased_bionlp2004_en_5.5.0_3.0_1725307623832.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_uncased_bionlp2004","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_uncased_bionlp2004","en") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.ner.xlmr_roberta.bionlp2004.uncased_base.by_tner").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_uncased_bionlp2004| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|780.5 MB| + +## References + +References + +- https://huggingface.co/tner/xlm-roberta-base-uncased-bionlp2004 +- https://github.com/asahi417/tner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_uncased_bionlp2004_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_uncased_bionlp2004_pipeline_en.md new file mode 100644 index 00000000000000..657010694c24de --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_uncased_bionlp2004_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlmroberta_ner_base_uncased_bionlp2004_pipeline pipeline XlmRoBertaForTokenClassification from tner +author: John Snow Labs +name: xlmroberta_ner_base_uncased_bionlp2004_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_uncased_bionlp2004_pipeline` is a English model originally trained by tner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_uncased_bionlp2004_pipeline_en_5.5.0_3.0_1725307772549.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_uncased_bionlp2004_pipeline_en_5.5.0_3.0_1725307772549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_base_uncased_bionlp2004_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_base_uncased_bionlp2004_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_uncased_bionlp2004_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|780.5 MB| + +## References + +https://huggingface.co/tner/xlm-roberta-base-uncased-bionlp2004 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_wnut2017_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_wnut2017_pipeline_en.md new file mode 100644 index 00000000000000..b9dfdcae1c0746 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_wnut2017_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlmroberta_ner_base_wnut2017_pipeline pipeline XlmRoBertaForTokenClassification from tner +author: John Snow Labs +name: xlmroberta_ner_base_wnut2017_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_wnut2017_pipeline` is a English model originally trained by tner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_wnut2017_pipeline_en_5.5.0_3.0_1725308629560.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_wnut2017_pipeline_en_5.5.0_3.0_1725308629560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_base_wnut2017_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_base_wnut2017_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_base_wnut2017_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|786.5 MB| + +## References + +https://huggingface.co/tner/xlm-roberta-base-wnut2017 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_clisi2000_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_clisi2000_base_finetuned_panx_de.md new file mode 100644 index 00000000000000..68120815813b0b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_clisi2000_base_finetuned_panx_de.md @@ -0,0 +1,113 @@ +--- +layout: model +title: German XLMRobertaForTokenClassification Base Cased model (from clisi2000) +author: John Snow Labs +name: xlmroberta_ner_clisi2000_base_finetuned_panx +date: 2024-09-02 +tags: [de, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `clisi2000`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_clisi2000_base_finetuned_panx_de_5.5.0_3.0_1725309397603.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_clisi2000_base_finetuned_panx_de_5.5.0_3.0_1725309397603.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_clisi2000_base_finetuned_panx","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_clisi2000_base_finetuned_panx","de") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_clisi2000").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_clisi2000_base_finetuned_panx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|853.8 MB| + +## References + +References + +- https://huggingface.co/clisi2000/xlm-roberta-base-finetuned-panx-de +- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_clisi2000_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_clisi2000_base_finetuned_panx_pipeline_de.md new file mode 100644 index 00000000000000..050c181312c3d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_clisi2000_base_finetuned_panx_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German xlmroberta_ner_clisi2000_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from clisi2000 +author: John Snow Labs +name: xlmroberta_ner_clisi2000_base_finetuned_panx_pipeline +date: 2024-09-02 +tags: [de, open_source, pipeline, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_clisi2000_base_finetuned_panx_pipeline` is a German model originally trained by clisi2000. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_clisi2000_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725309466450.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_clisi2000_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725309466450.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_clisi2000_base_finetuned_panx_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_clisi2000_base_finetuned_panx_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_clisi2000_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|853.8 MB| + +## References + +https://huggingface.co/clisi2000/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_davinam_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_davinam_base_finetuned_panx_de.md new file mode 100644 index 00000000000000..68adcabc83dc29 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_davinam_base_finetuned_panx_de.md @@ -0,0 +1,113 @@ +--- +layout: model +title: German XLMRobertaForTokenClassification Base Cased model (from davidenam) +author: John Snow Labs +name: xlmroberta_ner_davinam_base_finetuned_panx +date: 2024-09-02 +tags: [de, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `davidenam`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_davinam_base_finetuned_panx_de_5.5.0_3.0_1725307782772.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_davinam_base_finetuned_panx_de_5.5.0_3.0_1725307782772.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_davinam_base_finetuned_panx","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_davinam_base_finetuned_panx","de") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_davidenam").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_davinam_base_finetuned_panx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|853.8 MB| + +## References + +References + +- https://huggingface.co/davidenam/xlm-roberta-base-finetuned-panx-de +- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_davinam_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_davinam_base_finetuned_panx_pipeline_de.md new file mode 100644 index 00000000000000..69f64b9b65d2f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_davinam_base_finetuned_panx_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German xlmroberta_ner_davinam_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from davidenam +author: John Snow Labs +name: xlmroberta_ner_davinam_base_finetuned_panx_pipeline +date: 2024-09-02 +tags: [de, open_source, pipeline, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_davinam_base_finetuned_panx_pipeline` is a German model originally trained by davidenam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_davinam_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725307857291.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_davinam_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725307857291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_davinam_base_finetuned_panx_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_davinam_base_finetuned_panx_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_davinam_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|853.8 MB| + +## References + +https://huggingface.co/davidenam/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_edwardjross_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_edwardjross_base_finetuned_panx_de.md new file mode 100644 index 00000000000000..cc552cb76057a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_edwardjross_base_finetuned_panx_de.md @@ -0,0 +1,113 @@ +--- +layout: model +title: German XLMRobertaForTokenClassification Base Cased model (from edwardjross) +author: John Snow Labs +name: xlmroberta_ner_edwardjross_base_finetuned_panx +date: 2024-09-02 +tags: [de, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `edwardjross`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_edwardjross_base_finetuned_panx_de_5.5.0_3.0_1725308257485.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_edwardjross_base_finetuned_panx_de_5.5.0_3.0_1725308257485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_edwardjross_base_finetuned_panx","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_edwardjross_base_finetuned_panx","de") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_edwardjross").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_edwardjross_base_finetuned_panx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|853.4 MB| + +## References + +References + +- https://huggingface.co/edwardjross/xlm-roberta-base-finetuned-panx-de +- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_edwardjross_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_edwardjross_base_finetuned_panx_pipeline_de.md new file mode 100644 index 00000000000000..b8b985ad117429 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_edwardjross_base_finetuned_panx_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German xlmroberta_ner_edwardjross_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from edwardjross +author: John Snow Labs +name: xlmroberta_ner_edwardjross_base_finetuned_panx_pipeline +date: 2024-09-02 +tags: [de, open_source, pipeline, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_edwardjross_base_finetuned_panx_pipeline` is a German model originally trained by edwardjross. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_edwardjross_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725308325111.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_edwardjross_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725308325111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_edwardjross_base_finetuned_panx_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_edwardjross_base_finetuned_panx_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_edwardjross_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|853.4 MB| + +## References + +https://huggingface.co/edwardjross/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_jplu_r_40_lang_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_jplu_r_40_lang_pipeline_xx.md new file mode 100644 index 00000000000000..b246cca2dd95f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_jplu_r_40_lang_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual xlmroberta_ner_jplu_r_40_lang_pipeline pipeline XlmRoBertaForTokenClassification from nbroad +author: John Snow Labs +name: xlmroberta_ner_jplu_r_40_lang_pipeline +date: 2024-09-02 +tags: [xx, open_source, pipeline, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_jplu_r_40_lang_pipeline` is a Multilingual model originally trained by nbroad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jplu_r_40_lang_pipeline_xx_5.5.0_3.0_1725308074812.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jplu_r_40_lang_pipeline_xx_5.5.0_3.0_1725308074812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_jplu_r_40_lang_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_jplu_r_40_lang_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_jplu_r_40_lang_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|967.0 MB| + +## References + +https://huggingface.co/nbroad/jplu-xlm-r-ner-40-lang + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_jplu_r_40_lang_xx.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_jplu_r_40_lang_xx.md new file mode 100644 index 00000000000000..7f66f1d91f0cc1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_jplu_r_40_lang_xx.md @@ -0,0 +1,112 @@ +--- +layout: model +title: Multilingual XLMRobertaForTokenClassification Cased model (from nbroad) +author: John Snow Labs +name: xlmroberta_ner_jplu_r_40_lang +date: 2024-09-02 +tags: [xx, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `jplu-xlm-r-ner-40-lang` is a Multilingual model originally trained by `nbroad`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jplu_r_40_lang_xx_5.5.0_3.0_1725308016405.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jplu_r_40_lang_xx_5.5.0_3.0_1725308016405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_jplu_r_40_lang","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_jplu_r_40_lang","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("xx.ner.xlmr_roberta.lang.by_nbroad").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_jplu_r_40_lang| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|xx| +|Size:|967.0 MB| + +## References + +References + +- https://huggingface.co/nbroad/jplu-xlm-r-ner-40-lang \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_lijingxin_base_finetuned_panx_all_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_lijingxin_base_finetuned_panx_all_pipeline_xx.md new file mode 100644 index 00000000000000..7e57444ca1b23c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_lijingxin_base_finetuned_panx_all_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual xlmroberta_ner_lijingxin_base_finetuned_panx_all_pipeline pipeline XlmRoBertaForTokenClassification from lijingxin +author: John Snow Labs +name: xlmroberta_ner_lijingxin_base_finetuned_panx_all_pipeline +date: 2024-09-02 +tags: [xx, open_source, pipeline, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_lijingxin_base_finetuned_panx_all_pipeline` is a Multilingual model originally trained by lijingxin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_lijingxin_base_finetuned_panx_all_pipeline_xx_5.5.0_3.0_1725308959021.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_lijingxin_base_finetuned_panx_all_pipeline_xx_5.5.0_3.0_1725308959021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_lijingxin_base_finetuned_panx_all_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_lijingxin_base_finetuned_panx_all_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_lijingxin_base_finetuned_panx_all_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|861.0 MB| + +## References + +https://huggingface.co/lijingxin/xlm-roberta-base-finetuned-panx-all + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_lijingxin_base_finetuned_panx_all_xx.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_lijingxin_base_finetuned_panx_all_xx.md new file mode 100644 index 00000000000000..040343ad3ba573 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_lijingxin_base_finetuned_panx_all_xx.md @@ -0,0 +1,112 @@ +--- +layout: model +title: Multilingual XLMRobertaForTokenClassification Base Cased model (from lijingxin) +author: John Snow Labs +name: xlmroberta_ner_lijingxin_base_finetuned_panx_all +date: 2024-09-02 +tags: [xx, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-all` is a Multilingual model originally trained by `lijingxin`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_lijingxin_base_finetuned_panx_all_xx_5.5.0_3.0_1725308889935.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_lijingxin_base_finetuned_panx_all_xx_5.5.0_3.0_1725308889935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_lijingxin_base_finetuned_panx_all","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_lijingxin_base_finetuned_panx_all","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("xx.ner.xlmr_roberta.base_finetuned_panx_all.by_lijingxin").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_lijingxin_base_finetuned_panx_all| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|xx| +|Size:|861.0 MB| + +## References + +References + +- https://huggingface.co/lijingxin/xlm-roberta-base-finetuned-panx-all \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_lijingxin_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_lijingxin_base_finetuned_panx_de.md new file mode 100644 index 00000000000000..6539592e146583 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_lijingxin_base_finetuned_panx_de.md @@ -0,0 +1,113 @@ +--- +layout: model +title: German XLMRobertaForTokenClassification Base Cased model (from lijingxin) +author: John Snow Labs +name: xlmroberta_ner_lijingxin_base_finetuned_panx +date: 2024-09-02 +tags: [de, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `lijingxin`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_lijingxin_base_finetuned_panx_de_5.5.0_3.0_1725309055323.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_lijingxin_base_finetuned_panx_de_5.5.0_3.0_1725309055323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_lijingxin_base_finetuned_panx","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_lijingxin_base_finetuned_panx","de") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_lijingxin").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_lijingxin_base_finetuned_panx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|853.8 MB| + +## References + +References + +- https://huggingface.co/lijingxin/xlm-roberta-base-finetuned-panx-de +- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_v3rx2000_base_finetuned_panx_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_v3rx2000_base_finetuned_panx_pipeline_xx.md new file mode 100644 index 00000000000000..106fc172271fbf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_v3rx2000_base_finetuned_panx_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual xlmroberta_ner_v3rx2000_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from V3RX2000 +author: John Snow Labs +name: xlmroberta_ner_v3rx2000_base_finetuned_panx_pipeline +date: 2024-09-02 +tags: [xx, open_source, pipeline, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_v3rx2000_base_finetuned_panx_pipeline` is a Multilingual model originally trained by V3RX2000. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_v3rx2000_base_finetuned_panx_pipeline_xx_5.5.0_3.0_1725308970837.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_v3rx2000_base_finetuned_panx_pipeline_xx_5.5.0_3.0_1725308970837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_v3rx2000_base_finetuned_panx_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_v3rx2000_base_finetuned_panx_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_v3rx2000_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|858.2 MB| + +## References + +https://huggingface.co/V3RX2000/xlm-roberta-base-finetuned-panx-de-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_v3rx2000_base_finetuned_panx_xx.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_v3rx2000_base_finetuned_panx_xx.md new file mode 100644 index 00000000000000..e5d257ab7cc476 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_v3rx2000_base_finetuned_panx_xx.md @@ -0,0 +1,112 @@ +--- +layout: model +title: Multilingual XLMRobertaForTokenClassification Base Cased model (from V3RX2000) +author: John Snow Labs +name: xlmroberta_ner_v3rx2000_base_finetuned_panx +date: 2024-09-02 +tags: [de, fr, open_source, xlm_roberta, ner, xx, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de-fr` is a Multilingual model originally trained by `V3RX2000`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_v3rx2000_base_finetuned_panx_xx_5.5.0_3.0_1725308902809.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_v3rx2000_base_finetuned_panx_xx_5.5.0_3.0_1725308902809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_v3rx2000_base_finetuned_panx","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_v3rx2000_base_finetuned_panx","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("xx.ner.xlmr_roberta.base_finetuned_panx.by_v3rx2000").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_v3rx2000_base_finetuned_panx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|xx| +|Size:|858.2 MB| + +## References + +References + +- https://huggingface.co/V3RX2000/xlm-roberta-base-finetuned-panx-de-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_venturaville_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_venturaville_base_finetuned_panx_de.md new file mode 100644 index 00000000000000..d32b8d55743ae5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_venturaville_base_finetuned_panx_de.md @@ -0,0 +1,113 @@ +--- +layout: model +title: German XLMRobertaForTokenClassification Base Cased model (from venturaville) +author: John Snow Labs +name: xlmroberta_ner_venturaville_base_finetuned_panx +date: 2024-09-02 +tags: [de, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `venturaville`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_venturaville_base_finetuned_panx_de_5.5.0_3.0_1725309258304.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_venturaville_base_finetuned_panx_de_5.5.0_3.0_1725309258304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_venturaville_base_finetuned_panx","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_venturaville_base_finetuned_panx","de") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_venturaville").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_venturaville_base_finetuned_panx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|853.8 MB| + +## References + +References + +- https://huggingface.co/venturaville/xlm-roberta-base-finetuned-panx-de +- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_xml_roberta_base_finetuned_panx_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_xml_roberta_base_finetuned_panx_pipeline_fr.md new file mode 100644 index 00000000000000..bceb9bc731863a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_xml_roberta_base_finetuned_panx_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French xlmroberta_ner_xml_roberta_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from olpa +author: John Snow Labs +name: xlmroberta_ner_xml_roberta_base_finetuned_panx_pipeline +date: 2024-09-02 +tags: [fr, open_source, pipeline, onnx] +task: Named Entity Recognition +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_xml_roberta_base_finetuned_panx_pipeline` is a French model originally trained by olpa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xml_roberta_base_finetuned_panx_pipeline_fr_5.5.0_3.0_1725308810051.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xml_roberta_base_finetuned_panx_pipeline_fr_5.5.0_3.0_1725308810051.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_xml_roberta_base_finetuned_panx_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_xml_roberta_base_finetuned_panx_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_xml_roberta_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|840.9 MB| + +## References + +https://huggingface.co/olpa/xml-roberta-base-finetuned-panx-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_qa_ukrainian_pipeline_uk.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_qa_ukrainian_pipeline_uk.md new file mode 100644 index 00000000000000..2f352d9c881a38 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_qa_ukrainian_pipeline_uk.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Ukrainian xlmroberta_qa_ukrainian_pipeline pipeline XlmRoBertaForQuestionAnswering from robinhad +author: John Snow Labs +name: xlmroberta_qa_ukrainian_pipeline +date: 2024-09-02 +tags: [uk, open_source, pipeline, onnx] +task: Question Answering +language: uk +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_qa_ukrainian_pipeline` is a Ukrainian model originally trained by robinhad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_qa_ukrainian_pipeline_uk_5.5.0_3.0_1725254384538.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_qa_ukrainian_pipeline_uk_5.5.0_3.0_1725254384538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_qa_ukrainian_pipeline", lang = "uk") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_qa_ukrainian_pipeline", lang = "uk") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_qa_ukrainian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|uk| +|Size:|401.3 MB| + +## References + +https://huggingface.co/robinhad/ukrainian-qa + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_qa_ukrainian_uk.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_qa_ukrainian_uk.md new file mode 100644 index 00000000000000..e0a312d0ff0819 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_qa_ukrainian_uk.md @@ -0,0 +1,100 @@ +--- +layout: model +title: Ukrainian XlmRoBertaForQuestionAnswering model (from robinhad) +author: John Snow Labs +name: xlmroberta_qa_ukrainian +date: 2024-09-02 +tags: [uk, open_source, xlmroberta, question_answering, onnx] +task: Question Answering +language: uk +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `ukrainian-qa` is a Ukrainian model originally trained by `robinhad`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_qa_ukrainian_uk_5.5.0_3.0_1725254362143.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_qa_ukrainian_uk_5.5.0_3.0_1725254362143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = MultiDocumentAssembler() \ +.setInputCols(["question", "context"]) \ +.setOutputCols(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlmroberta_qa_ukrainian","uk") \ +.setInputCols(["document_question", "document_context"]) \ +.setOutputCol("answer")\ +.setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, spanClassifier]) + +data = spark.createDataFrame([["Як мене звати?", "Мене звуть Клара, і я живу в Берклі."]]).toDF("question", "context") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new MultiDocumentAssembler() +.setInputCols(Array("question", "context")) +.setOutputCols(Array("document_question", "document_context")) + +val spanClassifer = XlmRoBertaForQuestionAnswering.pretrained("xlmroberta_qa_ukrainian","uk") +.setInputCols(Array("document", "token")) +.setOutputCol("answer") +.setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) + +val data = Seq("Як мене звати?", "Мене звуть Клара, і я живу в Берклі.").toDF("question", "context") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("uk.answer_question.xlmr_roberta").predict("""Як мене звати?|||"Мене звуть Клара, і я живу в Берклі.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_qa_ukrainian| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|uk| +|Size:|401.3 MB| + +## References + +References + +- https://huggingface.co/robinhad/ukrainian-qa +- https://github.com/fido-ai/ua-datasets/tree/main/ua_datasets/src/question_answering +- https://github.com/robinhad/ukrainian-qa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_twi_eng_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_twi_eng_en.md new file mode 100644 index 00000000000000..c66c6449439413 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_twi_eng_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlmroberta_twi_eng XlmRoBertaEmbeddings from sgjwong +author: John Snow Labs +name: xlmroberta_twi_eng +date: 2024-09-02 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_twi_eng` is a English model originally trained by sgjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_twi_eng_en_5.5.0_3.0_1725270957913.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_twi_eng_en_5.5.0_3.0_1725270957913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("xlmroberta_twi_eng","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("xlmroberta_twi_eng","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_twi_eng| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/sgjwong/xlmroberta-tw_eng \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_twi_eng_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_twi_eng_pipeline_en.md new file mode 100644 index 00000000000000..eea59b21a41779 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_twi_eng_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlmroberta_twi_eng_pipeline pipeline XlmRoBertaEmbeddings from sgjwong +author: John Snow Labs +name: xlmroberta_twi_eng_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_twi_eng_pipeline` is a English model originally trained by sgjwong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_twi_eng_pipeline_en_5.5.0_3.0_1725271019440.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_twi_eng_pipeline_en_5.5.0_3.0_1725271019440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_twi_eng_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_twi_eng_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_twi_eng_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/sgjwong/xlmroberta-tw_eng + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmrobertalongforquestionanswering_base_squad2_256_4096_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmrobertalongforquestionanswering_base_squad2_256_4096_en.md new file mode 100644 index 00000000000000..663fc965f03ac0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmrobertalongforquestionanswering_base_squad2_256_4096_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English xlmrobertalongforquestionanswering_base_squad2_256_4096 XlmRoBertaForQuestionAnswering from sadaqabdo +author: John Snow Labs +name: xlmrobertalongforquestionanswering_base_squad2_256_4096 +date: 2024-09-02 +tags: [en, open_source, onnx, question_answering, xlm_roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmrobertalongforquestionanswering_base_squad2_256_4096` is a English model originally trained by sadaqabdo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmrobertalongforquestionanswering_base_squad2_256_4096_en_5.5.0_3.0_1725254868712.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmrobertalongforquestionanswering_base_squad2_256_4096_en_5.5.0_3.0_1725254868712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlmrobertalongforquestionanswering_base_squad2_256_4096","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlmrobertalongforquestionanswering_base_squad2_256_4096", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmrobertalongforquestionanswering_base_squad2_256_4096| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|883.5 MB| + +## References + +https://huggingface.co/sadaqabdo/XLMRobertaLongForQuestionAnswering-base-squad2-256-4096 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmrobertalongforquestionanswering_base_squad2_256_4096_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmrobertalongforquestionanswering_base_squad2_256_4096_pipeline_en.md new file mode 100644 index 00000000000000..03b1a19cf0f4e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-02-xlmrobertalongforquestionanswering_base_squad2_256_4096_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English xlmrobertalongforquestionanswering_base_squad2_256_4096_pipeline pipeline XlmRoBertaForQuestionAnswering from sadaqabdo +author: John Snow Labs +name: xlmrobertalongforquestionanswering_base_squad2_256_4096_pipeline +date: 2024-09-02 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmrobertalongforquestionanswering_base_squad2_256_4096_pipeline` is a English model originally trained by sadaqabdo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmrobertalongforquestionanswering_base_squad2_256_4096_pipeline_en_5.5.0_3.0_1725254942451.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmrobertalongforquestionanswering_base_squad2_256_4096_pipeline_en_5.5.0_3.0_1725254942451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmrobertalongforquestionanswering_base_squad2_256_4096_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmrobertalongforquestionanswering_base_squad2_256_4096_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmrobertalongforquestionanswering_base_squad2_256_4096_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|883.5 MB| + +## References + +https://huggingface.co/sadaqabdo/XLMRobertaLongForQuestionAnswering-base-squad2-256-4096 + +## Included Models + +- MultiDocumentAssembler +- XlmRoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_pipeline_en.md new file mode 100644 index 00000000000000..ab4031cf4bdd76 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English 2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_pipeline pipeline XlmRoBertaEmbeddings from JEdward7777 +author: John Snow Labs +name: 2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_pipeline` is a English model originally trained by JEdward7777. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_pipeline_en_5.5.0_3.0_1725342704655.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_pipeline_en_5.5.0_3.0_1725342704655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/JEdward7777/2-finetuned-xlm-r-masakhaner-swa-whole-word-phonetic + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-ai_hackathon_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-03-ai_hackathon_distilbert_en.md new file mode 100644 index 00000000000000..96595c116957eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-ai_hackathon_distilbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ai_hackathon_distilbert DistilBertForSequenceClassification from Darshan03 +author: John Snow Labs +name: ai_hackathon_distilbert +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_hackathon_distilbert` is a English model originally trained by Darshan03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_hackathon_distilbert_en_5.5.0_3.0_1725330169515.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_hackathon_distilbert_en_5.5.0_3.0_1725330169515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("ai_hackathon_distilbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("ai_hackathon_distilbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ai_hackathon_distilbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Darshan03/AI-Hackathon-DistilBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_1_lr_1_en.md b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_1_lr_1_en.md new file mode 100644 index 00000000000000..3096757edc9302 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_1_lr_1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_base_qa_1_lr_1 AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_1_lr_1 +date: 2024-09-03 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_1_lr_1` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_1_lr_1_en_5.5.0_3.0_1725341675905.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_1_lr_1_en_5.5.0_3.0_1725341675905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_1_lr_1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_1_lr_1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_1_lr_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-1-lr-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_1_lr_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_1_lr_1_pipeline_en.md new file mode 100644 index 00000000000000..5e3f396697ae7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_1_lr_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_1_lr_1_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_1_lr_1_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_1_lr_1_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_1_lr_1_pipeline_en_5.5.0_3.0_1725341678213.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_1_lr_1_pipeline_en_5.5.0_3.0_1725341678213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_1_lr_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_1_lr_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_1_lr_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-1-lr-1 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_2_batch_1_en.md b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_2_batch_1_en.md new file mode 100644 index 00000000000000..ef19d700ac42cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_2_batch_1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_base_qa_2_batch_1 AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_2_batch_1 +date: 2024-09-03 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2_batch_1` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_batch_1_en_5.5.0_3.0_1725341431380.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_batch_1_en_5.5.0_3.0_1725341431380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_2_batch_1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_2_batch_1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_2_batch_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-2-batch-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_2_batch_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_2_batch_1_pipeline_en.md new file mode 100644 index 00000000000000..223e388350f91f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_2_batch_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_2_batch_1_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_2_batch_1_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2_batch_1_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_batch_1_pipeline_en_5.5.0_3.0_1725341433909.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_batch_1_pipeline_en_5.5.0_3.0_1725341433909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_2_batch_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_2_batch_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_2_batch_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-2-batch-1 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_2_k_fold_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_2_k_fold_3_pipeline_en.md new file mode 100644 index 00000000000000..eb5dee55418265 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_2_k_fold_3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_2_k_fold_3_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_2_k_fold_3_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2_k_fold_3_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_3_pipeline_en_5.5.0_3.0_1725341728882.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_3_pipeline_en_5.5.0_3.0_1725341728882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_2_k_fold_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_2_k_fold_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_2_k_fold_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-2-k-fold-3 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_coqa_2_k_fold_1_en.md b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_coqa_2_k_fold_1_en.md new file mode 100644 index 00000000000000..6d3fba52d86e58 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_coqa_2_k_fold_1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English albert_base_qa_coqa_2_k_fold_1 AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_coqa_2_k_fold_1 +date: 2024-09-03 +tags: [en, open_source, onnx, question_answering, albert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_coqa_2_k_fold_1` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_1_en_5.5.0_3.0_1725341805611.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_1_en_5.5.0_3.0_1725341805611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_2_k_fold_1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_2_k_fold_1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_coqa_2_k_fold_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-coQA-2-k-fold-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_coqa_2_k_fold_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_coqa_2_k_fold_1_pipeline_en.md new file mode 100644 index 00000000000000..2a972de96197b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_coqa_2_k_fold_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English albert_base_qa_coqa_2_k_fold_1_pipeline pipeline AlbertForQuestionAnswering from mateiaass +author: John Snow Labs +name: albert_base_qa_coqa_2_k_fold_1_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_coqa_2_k_fold_1_pipeline` is a English model originally trained by mateiaass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_1_pipeline_en_5.5.0_3.0_1725341808096.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_2_k_fold_1_pipeline_en_5.5.0_3.0_1725341808096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_qa_coqa_2_k_fold_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_qa_coqa_2_k_fold_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_qa_coqa_2_k_fold_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.0 MB| + +## References + +https://huggingface.co/mateiaass/albert-base-qa-coQA-2-k-fold-1 + +## Included Models + +- MultiDocumentAssembler +- AlbertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-ancient_greek_to_1453_alignment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-ancient_greek_to_1453_alignment_pipeline_en.md new file mode 100644 index 00000000000000..3b16114335bd54 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-ancient_greek_to_1453_alignment_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ancient_greek_to_1453_alignment_pipeline pipeline XlmRoBertaEmbeddings from UGARIT +author: John Snow Labs +name: ancient_greek_to_1453_alignment_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ancient_greek_to_1453_alignment_pipeline` is a English model originally trained by UGARIT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ancient_greek_to_1453_alignment_pipeline_en_5.5.0_3.0_1725343696028.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ancient_greek_to_1453_alignment_pipeline_en_5.5.0_3.0_1725343696028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ancient_greek_to_1453_alignment_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ancient_greek_to_1453_alignment_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ancient_greek_to_1453_alignment_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/UGARIT/grc-alignment + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-angela_shuffle_test_en.md b/docs/_posts/ahmedlone127/2024-09-03-angela_shuffle_test_en.md new file mode 100644 index 00000000000000..ee91186203bc84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-angela_shuffle_test_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English angela_shuffle_test XlmRoBertaForTokenClassification from azhang1212 +author: John Snow Labs +name: angela_shuffle_test +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`angela_shuffle_test` is a English model originally trained by azhang1212. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/angela_shuffle_test_en_5.5.0_3.0_1725322034427.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/angela_shuffle_test_en_5.5.0_3.0_1725322034427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("angela_shuffle_test","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("angela_shuffle_test", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|angela_shuffle_test| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/azhang1212/angela_shuffle_test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-autotrain_okr_iptal_v4_48282117445_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-autotrain_okr_iptal_v4_48282117445_pipeline_en.md new file mode 100644 index 00000000000000..038d149ab1f0e5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-autotrain_okr_iptal_v4_48282117445_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English autotrain_okr_iptal_v4_48282117445_pipeline pipeline XlmRoBertaForSequenceClassification from ekincanozcelik +author: John Snow Labs +name: autotrain_okr_iptal_v4_48282117445_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_okr_iptal_v4_48282117445_pipeline` is a English model originally trained by ekincanozcelik. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v4_48282117445_pipeline_en_5.5.0_3.0_1725329023604.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v4_48282117445_pipeline_en_5.5.0_3.0_1725329023604.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_okr_iptal_v4_48282117445_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_okr_iptal_v4_48282117445_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_okr_iptal_v4_48282117445_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|778.4 MB| + +## References + +https://huggingface.co/ekincanozcelik/autotrain-okr_iptal_v4-48282117445 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_reranker_base_baai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_reranker_base_baai_pipeline_en.md new file mode 100644 index 00000000000000..17637cbf2ca6b9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-bge_reranker_base_baai_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bge_reranker_base_baai_pipeline pipeline XlmRoBertaForSequenceClassification from BAAI +author: John Snow Labs +name: bge_reranker_base_baai_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_reranker_base_baai_pipeline` is a English model originally trained by BAAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_reranker_base_baai_pipeline_en_5.5.0_3.0_1725328052285.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_reranker_base_baai_pipeline_en_5.5.0_3.0_1725328052285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_reranker_base_baai_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_reranker_base_baai_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_reranker_base_baai_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|994.1 MB| + +## References + +https://huggingface.co/BAAI/bge-reranker-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-bookmebus_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bookmebus_sentiment_analysis_pipeline_en.md new file mode 100644 index 00000000000000..bd85d11214332c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-bookmebus_sentiment_analysis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bookmebus_sentiment_analysis_pipeline pipeline XlmRoBertaForSequenceClassification from seanghay +author: John Snow Labs +name: bookmebus_sentiment_analysis_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bookmebus_sentiment_analysis_pipeline` is a English model originally trained by seanghay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bookmebus_sentiment_analysis_pipeline_en_5.5.0_3.0_1725327839500.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bookmebus_sentiment_analysis_pipeline_en_5.5.0_3.0_1725327839500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bookmebus_sentiment_analysis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bookmebus_sentiment_analysis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bookmebus_sentiment_analysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|839.1 MB| + +## References + +https://huggingface.co/seanghay/bookmebus-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-bsc_bio_ehr_spanish_drugtemist_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bsc_bio_ehr_spanish_drugtemist_ner_pipeline_en.md new file mode 100644 index 00000000000000..1636d6167e7fa5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-bsc_bio_ehr_spanish_drugtemist_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bsc_bio_ehr_spanish_drugtemist_ner_pipeline pipeline RoBertaForTokenClassification from Rodrigo1771 +author: John Snow Labs +name: bsc_bio_ehr_spanish_drugtemist_ner_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_drugtemist_ner_pipeline` is a English model originally trained by Rodrigo1771. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_drugtemist_ner_pipeline_en_5.5.0_3.0_1725326509860.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_drugtemist_ner_pipeline_en_5.5.0_3.0_1725326509860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bsc_bio_ehr_spanish_drugtemist_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bsc_bio_ehr_spanish_drugtemist_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bsc_bio_ehr_spanish_drugtemist_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|440.5 MB| + +## References + +https://huggingface.co/Rodrigo1771/bsc-bio-ehr-es-drugtemist-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_model_alynn_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_model_alynn_en.md new file mode 100644 index 00000000000000..b8ac4a4050ada6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_model_alynn_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_model_alynn DistilBertForSequenceClassification from Alynn +author: John Snow Labs +name: burmese_awesome_model_alynn +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_alynn` is a English model originally trained by Alynn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_alynn_en_5.5.0_3.0_1725329695269.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_alynn_en_5.5.0_3.0_1725329695269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_alynn","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_alynn", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_model_alynn| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Alynn/my_awesome_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_model_alynn_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_model_alynn_pipeline_en.md new file mode 100644 index 00000000000000..2d9eb5369aa9f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_model_alynn_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_awesome_model_alynn_pipeline pipeline DistilBertForSequenceClassification from Alynn +author: John Snow Labs +name: burmese_awesome_model_alynn_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_alynn_pipeline` is a English model originally trained by Alynn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_alynn_pipeline_en_5.5.0_3.0_1725329707365.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_alynn_pipeline_en_5.5.0_3.0_1725329707365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_model_alynn_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_model_alynn_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_model_alynn_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Alynn/my_awesome_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_text_classification_finetuned_v1_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_text_classification_finetuned_v1_en.md new file mode 100644 index 00000000000000..8b306f17cdf028 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_text_classification_finetuned_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_text_classification_finetuned_v1 DistilBertForSequenceClassification from cwchang +author: John Snow Labs +name: burmese_text_classification_finetuned_v1 +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_text_classification_finetuned_v1` is a English model originally trained by cwchang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_text_classification_finetuned_v1_en_5.5.0_3.0_1725330054912.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_text_classification_finetuned_v1_en_5.5.0_3.0_1725330054912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_text_classification_finetuned_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_text_classification_finetuned_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_text_classification_finetuned_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.9 MB| + +## References + +https://huggingface.co/cwchang/my-text-classification-finetuned-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_translation_helsinki_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_translation_helsinki_pipeline_en.md new file mode 100644 index 00000000000000..5bf2060dada6d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_translation_helsinki_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_translation_helsinki_pipeline pipeline MarianTransformer from duwuonline +author: John Snow Labs +name: burmese_translation_helsinki_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_translation_helsinki_pipeline` is a English model originally trained by duwuonline. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_translation_helsinki_pipeline_en_5.5.0_3.0_1725345520066.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_translation_helsinki_pipeline_en_5.5.0_3.0_1725345520066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_translation_helsinki_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_translation_helsinki_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_translation_helsinki_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|475.4 MB| + +## References + +https://huggingface.co/duwuonline/my-translation-helsinki + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-cat_ner_xlmr_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-cat_ner_xlmr_3_pipeline_en.md new file mode 100644 index 00000000000000..0dc58f48f290bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-cat_ner_xlmr_3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cat_ner_xlmr_3_pipeline pipeline XlmRoBertaForTokenClassification from homersimpson +author: John Snow Labs +name: cat_ner_xlmr_3_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cat_ner_xlmr_3_pipeline` is a English model originally trained by homersimpson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cat_ner_xlmr_3_pipeline_en_5.5.0_3.0_1725321687649.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cat_ner_xlmr_3_pipeline_en_5.5.0_3.0_1725321687649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cat_ner_xlmr_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cat_ner_xlmr_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cat_ner_xlmr_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|814.3 MB| + +## References + +https://huggingface.co/homersimpson/cat-ner-xlmr-3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-checkpoint_12600_en.md b/docs/_posts/ahmedlone127/2024-09-03-checkpoint_12600_en.md new file mode 100644 index 00000000000000..f2e8838e82bf27 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-checkpoint_12600_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English checkpoint_12600 XlmRoBertaEmbeddings from yemen2016 +author: John Snow Labs +name: checkpoint_12600 +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`checkpoint_12600` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/checkpoint_12600_en_5.5.0_3.0_1725343297597.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checkpoint_12600_en_5.5.0_3.0_1725343297597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("checkpoint_12600","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("checkpoint_12600","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|checkpoint_12600| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/checkpoint-12600 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-checkpoint_12600_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-checkpoint_12600_pipeline_en.md new file mode 100644 index 00000000000000..fa5e88dd26b6ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-checkpoint_12600_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English checkpoint_12600_pipeline pipeline XlmRoBertaEmbeddings from yemen2016 +author: John Snow Labs +name: checkpoint_12600_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`checkpoint_12600_pipeline` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/checkpoint_12600_pipeline_en_5.5.0_3.0_1725343347883.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checkpoint_12600_pipeline_en_5.5.0_3.0_1725343347883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("checkpoint_12600_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("checkpoint_12600_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|checkpoint_12600_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/checkpoint-12600 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-citation_classifier_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-citation_classifier_roberta_base_pipeline_en.md new file mode 100644 index 00000000000000..e246cce09c3f29 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-citation_classifier_roberta_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English citation_classifier_roberta_base_pipeline pipeline RoBertaForSequenceClassification from selink +author: John Snow Labs +name: citation_classifier_roberta_base_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`citation_classifier_roberta_base_pipeline` is a English model originally trained by selink. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/citation_classifier_roberta_base_pipeline_en_5.5.0_3.0_1725337523488.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/citation_classifier_roberta_base_pipeline_en_5.5.0_3.0_1725337523488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("citation_classifier_roberta_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("citation_classifier_roberta_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|citation_classifier_roberta_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/selink/citation-classifier-roberta-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_base_500_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_base_500_pipeline_en.md new file mode 100644 index 00000000000000..f6f419559a0b21 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_base_500_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English cleaned_e5_base_500_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: cleaned_e5_base_500_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_e5_base_500_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_500_pipeline_en_5.5.0_3.0_1725340946372.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_500_pipeline_en_5.5.0_3.0_1725340946372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cleaned_e5_base_500_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cleaned_e5_base_500_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cleaned_e5_base_500_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.4 MB| + +## References + +https://huggingface.co/rithwik-db/cleaned-e5-base-500 + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_base_unsupervised_16_en.md b/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_base_unsupervised_16_en.md new file mode 100644 index 00000000000000..f8d98e6bdb92d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_base_unsupervised_16_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English cleaned_e5_base_unsupervised_16 E5Embeddings from rithwik-db +author: John Snow Labs +name: cleaned_e5_base_unsupervised_16 +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_e5_base_unsupervised_16` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_unsupervised_16_en_5.5.0_3.0_1725332681619.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_unsupervised_16_en_5.5.0_3.0_1725332681619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("cleaned_e5_base_unsupervised_16","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("cleaned_e5_base_unsupervised_16","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cleaned_e5_base_unsupervised_16| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|386.2 MB| + +## References + +https://huggingface.co/rithwik-db/cleaned-e5-base-unsupervised-16 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_large_unsupervised_8_en.md b/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_large_unsupervised_8_en.md new file mode 100644 index 00000000000000..b2cc675ac344d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_large_unsupervised_8_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English cleaned_e5_large_unsupervised_8 E5Embeddings from rithwik-db +author: John Snow Labs +name: cleaned_e5_large_unsupervised_8 +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_e5_large_unsupervised_8` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_e5_large_unsupervised_8_en_5.5.0_3.0_1725340307178.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_e5_large_unsupervised_8_en_5.5.0_3.0_1725340307178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("cleaned_e5_large_unsupervised_8","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("cleaned_e5_large_unsupervised_8","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cleaned_e5_large_unsupervised_8| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/rithwik-db/cleaned-e5-large-unsupervised-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-climateattention_10k_upscaled_en.md b/docs/_posts/ahmedlone127/2024-09-03-climateattention_10k_upscaled_en.md new file mode 100644 index 00000000000000..9cf668b364a1f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-climateattention_10k_upscaled_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English climateattention_10k_upscaled RoBertaForTokenClassification from kruthof +author: John Snow Labs +name: climateattention_10k_upscaled +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`climateattention_10k_upscaled` is a English model originally trained by kruthof. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/climateattention_10k_upscaled_en_5.5.0_3.0_1725326506576.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/climateattention_10k_upscaled_en_5.5.0_3.0_1725326506576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = RoBertaForTokenClassification.pretrained("climateattention_10k_upscaled","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("climateattention_10k_upscaled", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|climateattention_10k_upscaled| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|307.4 MB| + +## References + +https://huggingface.co/kruthof/climateattention-10k-upscaled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_base_patch16_supervised_mulitilingual_400_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_base_patch16_supervised_mulitilingual_400_en.md new file mode 100644 index 00000000000000..aa29be55079cc9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-clip_base_patch16_supervised_mulitilingual_400_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_base_patch16_supervised_mulitilingual_400 CLIPForZeroShotClassification from gowitheflowlab +author: John Snow Labs +name: clip_base_patch16_supervised_mulitilingual_400 +date: 2024-09-03 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_base_patch16_supervised_mulitilingual_400` is a English model originally trained by gowitheflowlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_400_en_5.5.0_3.0_1725338654334.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_400_en_5.5.0_3.0_1725338654334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_base_patch16_supervised_mulitilingual_400","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_base_patch16_supervised_mulitilingual_400","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_base_patch16_supervised_mulitilingual_400| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|509.7 MB| + +## References + +https://huggingface.co/gowitheflowlab/clip-base-patch16-supervised-mulitilingual-400 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_base_patch16_supervised_mulitilingual_800_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_base_patch16_supervised_mulitilingual_800_en.md new file mode 100644 index 00000000000000..bddc7f46149f94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-clip_base_patch16_supervised_mulitilingual_800_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_base_patch16_supervised_mulitilingual_800 CLIPForZeroShotClassification from gowitheflowlab +author: John Snow Labs +name: clip_base_patch16_supervised_mulitilingual_800 +date: 2024-09-03 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_base_patch16_supervised_mulitilingual_800` is a English model originally trained by gowitheflowlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_800_en_5.5.0_3.0_1725338079922.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_800_en_5.5.0_3.0_1725338079922.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_base_patch16_supervised_mulitilingual_800","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_base_patch16_supervised_mulitilingual_800","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_base_patch16_supervised_mulitilingual_800| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|509.7 MB| + +## References + +https://huggingface.co/gowitheflowlab/clip-base-patch16-supervised-mulitilingual-800 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_fashion_attribute_model_try_2_base32_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_fashion_attribute_model_try_2_base32_pipeline_en.md new file mode 100644 index 00000000000000..d6d37f50485da6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-clip_fashion_attribute_model_try_2_base32_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_fashion_attribute_model_try_2_base32_pipeline pipeline CLIPForZeroShotClassification from Geetansh13 +author: John Snow Labs +name: clip_fashion_attribute_model_try_2_base32_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_fashion_attribute_model_try_2_base32_pipeline` is a English model originally trained by Geetansh13. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_fashion_attribute_model_try_2_base32_pipeline_en_5.5.0_3.0_1725339266748.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_fashion_attribute_model_try_2_base32_pipeline_en_5.5.0_3.0_1725339266748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_fashion_attribute_model_try_2_base32_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_fashion_attribute_model_try_2_base32_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_fashion_attribute_model_try_2_base32_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|580.7 MB| + +## References + +https://huggingface.co/Geetansh13/clip-fashion-attribute-model-try-2-base32 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_ft_sim_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_ft_sim_en.md new file mode 100644 index 00000000000000..b71afd43649780 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-clip_ft_sim_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_ft_sim CLIPForZeroShotClassification from masterhaniwa +author: John Snow Labs +name: clip_ft_sim +date: 2024-09-03 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_ft_sim` is a English model originally trained by masterhaniwa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_ft_sim_en_5.5.0_3.0_1725338971823.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_ft_sim_en_5.5.0_3.0_1725338971823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_ft_sim","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_ft_sim","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_ft_sim| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|561.2 MB| + +## References + +https://huggingface.co/masterhaniwa/CLIP_ft_sim \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_ft_sim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_ft_sim_pipeline_en.md new file mode 100644 index 00000000000000..845eb807b39685 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-clip_ft_sim_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English clip_ft_sim_pipeline pipeline CLIPForZeroShotClassification from masterhaniwa +author: John Snow Labs +name: clip_ft_sim_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_ft_sim_pipeline` is a English model originally trained by masterhaniwa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_ft_sim_pipeline_en_5.5.0_3.0_1725338999003.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_ft_sim_pipeline_en_5.5.0_3.0_1725338999003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clip_ft_sim_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clip_ft_sim_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_ft_sim_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|561.2 MB| + +## References + +https://huggingface.co/masterhaniwa/CLIP_ft_sim + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_vit_large_patch14_krnl_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_large_patch14_krnl_en.md new file mode 100644 index 00000000000000..083e259bcedddf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_large_patch14_krnl_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_large_patch14_krnl CLIPForZeroShotClassification from krnl +author: John Snow Labs +name: clip_vit_large_patch14_krnl +date: 2024-09-03 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_krnl` is a English model originally trained by krnl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_krnl_en_5.5.0_3.0_1725339339531.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_krnl_en_5.5.0_3.0_1725339339531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_krnl","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_krnl","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_large_patch14_krnl| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/krnl/clip-vit-large-patch14 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_vit_tjklein_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_tjklein_en.md new file mode 100644 index 00000000000000..d06f6ab27b8d78 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_tjklein_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English clip_vit_tjklein CLIPForZeroShotClassification from TJKlein +author: John Snow Labs +name: clip_vit_tjklein +date: 2024-09-03 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_tjklein` is a English model originally trained by TJKlein. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_tjklein_en_5.5.0_3.0_1725339504206.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_tjklein_en_5.5.0_3.0_1725339504206.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_tjklein","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_tjklein","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clip_vit_tjklein| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/TJKlein/CLIP-ViT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_l2_mmarcofr_fr.md b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_l2_mmarcofr_fr.md new file mode 100644 index 00000000000000..87f0a01ff051de --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_l2_mmarcofr_fr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: French crossencoder_camembert_l2_mmarcofr CamemBertForSequenceClassification from antoinelouis +author: John Snow Labs +name: crossencoder_camembert_l2_mmarcofr +date: 2024-09-03 +tags: [fr, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_camembert_l2_mmarcofr` is a French model originally trained by antoinelouis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l2_mmarcofr_fr_5.5.0_3.0_1725324994778.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l2_mmarcofr_fr_5.5.0_3.0_1725324994778.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("crossencoder_camembert_l2_mmarcofr","fr") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("crossencoder_camembert_l2_mmarcofr", "fr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|crossencoder_camembert_l2_mmarcofr| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|fr| +|Size:|149.0 MB| + +## References + +https://huggingface.co/antoinelouis/crossencoder-camembert-L2-mmarcoFR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_l2_mmarcofr_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_l2_mmarcofr_pipeline_fr.md new file mode 100644 index 00000000000000..89dcee302e2fd8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_l2_mmarcofr_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French crossencoder_camembert_l2_mmarcofr_pipeline pipeline CamemBertForSequenceClassification from antoinelouis +author: John Snow Labs +name: crossencoder_camembert_l2_mmarcofr_pipeline +date: 2024-09-03 +tags: [fr, open_source, pipeline, onnx] +task: Text Classification +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_camembert_l2_mmarcofr_pipeline` is a French model originally trained by antoinelouis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l2_mmarcofr_pipeline_fr_5.5.0_3.0_1725325002068.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l2_mmarcofr_pipeline_fr_5.5.0_3.0_1725325002068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("crossencoder_camembert_l2_mmarcofr_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("crossencoder_camembert_l2_mmarcofr_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|crossencoder_camembert_l2_mmarcofr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|149.0 MB| + +## References + +https://huggingface.co/antoinelouis/crossencoder-camembert-L2-mmarcoFR + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-custom_clip_en.md b/docs/_posts/ahmedlone127/2024-09-03-custom_clip_en.md new file mode 100644 index 00000000000000..1c11c26b00b15e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-custom_clip_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English custom_clip CLIPForZeroShotClassification from gokuls +author: John Snow Labs +name: custom_clip +date: 2024-09-03 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_clip` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_clip_en_5.5.0_3.0_1725338121149.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_clip_en_5.5.0_3.0_1725338121149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("custom_clip","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("custom_clip","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|custom_clip| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|567.2 MB| + +## References + +https://huggingface.co/gokuls/custom_clip \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_nbme_V3_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_nbme_V3_large_pipeline_en.md new file mode 100644 index 00000000000000..3137e82a33cb7b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_nbme_V3_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_embeddings_nbme_V3_large_pipeline pipeline DeBertaEmbeddings from smeoni +author: John Snow Labs +name: deberta_embeddings_nbme_V3_large_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_embeddings_nbme_V3_large_pipeline` is a English model originally trained by smeoni. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_nbme_V3_large_pipeline_en_5.5.0_3.0_1725331079649.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_nbme_V3_large_pipeline_en_5.5.0_3.0_1725331079649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_embeddings_nbme_V3_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_embeddings_nbme_V3_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_nbme_V3_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/smeoni/nbme-deberta-V3-large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_base_lm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_base_lm_pipeline_en.md new file mode 100644 index 00000000000000..77dadfe00c1fc3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_base_lm_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_embeddings_v3_base_lm_pipeline pipeline DeBertaEmbeddings from iewaij +author: John Snow Labs +name: deberta_embeddings_v3_base_lm_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_embeddings_v3_base_lm_pipeline` is a English model originally trained by iewaij. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_v3_base_lm_pipeline_en_5.5.0_3.0_1725331047860.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_v3_base_lm_pipeline_en_5.5.0_3.0_1725331047860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_embeddings_v3_base_lm_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_embeddings_v3_base_lm_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_v3_base_lm_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|689.6 MB| + +## References + +https://huggingface.co/iewaij/deberta-v3-base-lm + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_en.md new file mode 100644 index 00000000000000..19655a5d0a1f20 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_en.md @@ -0,0 +1,100 @@ +--- +layout: model +title: English Deberta Embeddings model (from domenicrosati) +author: John Snow Labs +name: deberta_embeddings_v3_large_dapt_scientific_papers_pubmed +date: 2024-09-03 +tags: [deberta, open_source, deberta_embeddings, debertav2formaskedlm, en, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DebertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `deberta-v3-large-dapt-scientific-papers-pubmed` is a English model originally trained by `domenicrosati`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_en_5.5.0_3.0_1725331696326.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_en_5.5.0_3.0_1725331696326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_v3_large_dapt_scientific_papers_pubmed","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") \ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings]) + +data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_v3_large_dapt_scientific_papers_pubmed","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) + +val data = Seq("I love Spark NLP").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_v3_large_dapt_scientific_papers_pubmed| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|1.6 GB| + +## References + +References + +https://huggingface.co/domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_pipeline_en.md new file mode 100644 index 00000000000000..1d62b73cd40015 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_pipeline pipeline DeBertaEmbeddings from domenicrosati +author: John Snow Labs +name: deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_pipeline_en_5.5.0_3.0_1725331774689.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_pipeline_en_5.5.0_3.0_1725331774689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_en.md new file mode 100644 index 00000000000000..f6ad69a51d29fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_en.md @@ -0,0 +1,100 @@ +--- +layout: model +title: English Deberta Embeddings model (from domenicrosati) +author: John Snow Labs +name: deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt +date: 2024-09-03 +tags: [deberta, open_source, deberta_embeddings, debertav2formaskedlm, en, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DebertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `deberta-v3-large-dapt-scientific-papers-pubmed-tapt` is a English model originally trained by `domenicrosati`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_en_5.5.0_3.0_1725331508803.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_en_5.5.0_3.0_1725331508803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") \ + .setCaseSensitive(True) + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings]) + +data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + .setCaseSensitive(true) + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) + +val data = Seq("I love Spark NLP").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|1.6 GB| + +## References + +References + +https://huggingface.co/domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed-tapt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline_en.md new file mode 100644 index 00000000000000..e2a7b6ab01241e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline pipeline DeBertaEmbeddings from domenicrosati +author: John Snow Labs +name: deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline_en_5.5.0_3.0_1725331585326.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline_en_5.5.0_3.0_1725331585326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed-tapt + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_base_japanese_izumi_lab_ja.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_base_japanese_izumi_lab_ja.md new file mode 100644 index 00000000000000..d27e044694c876 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_base_japanese_izumi_lab_ja.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Japanese deberta_v2_base_japanese_izumi_lab DeBertaEmbeddings from izumi-lab +author: John Snow Labs +name: deberta_v2_base_japanese_izumi_lab +date: 2024-09-03 +tags: [ja, open_source, onnx, embeddings, deberta] +task: Embeddings +language: ja +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_base_japanese_izumi_lab` is a Japanese model originally trained by izumi-lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_base_japanese_izumi_lab_ja_5.5.0_3.0_1725331703040.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_base_japanese_izumi_lab_ja_5.5.0_3.0_1725331703040.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_v2_base_japanese_izumi_lab","ja") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_v2_base_japanese_izumi_lab","ja") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v2_base_japanese_izumi_lab| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|ja| +|Size:|263.1 MB| + +## References + +https://huggingface.co/izumi-lab/deberta-v2-base-japanese \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_small_japanese_ja.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_small_japanese_ja.md new file mode 100644 index 00000000000000..b0b7b987ce4598 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_small_japanese_ja.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Japanese deberta_v2_small_japanese DeBertaEmbeddings from izumi-lab +author: John Snow Labs +name: deberta_v2_small_japanese +date: 2024-09-03 +tags: [ja, open_source, onnx, embeddings, deberta] +task: Embeddings +language: ja +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_small_japanese` is a Japanese model originally trained by izumi-lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_small_japanese_ja_5.5.0_3.0_1725331532712.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_small_japanese_ja_5.5.0_3.0_1725331532712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_v2_small_japanese","ja") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_v2_small_japanese","ja") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v2_small_japanese| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|ja| +|Size:|34.5 MB| + +## References + +https://huggingface.co/izumi-lab/deberta-v2-small-japanese \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_small_japanese_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_small_japanese_pipeline_ja.md new file mode 100644 index 00000000000000..ccabb62133376a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_small_japanese_pipeline_ja.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Japanese deberta_v2_small_japanese_pipeline pipeline DeBertaEmbeddings from izumi-lab +author: John Snow Labs +name: deberta_v2_small_japanese_pipeline +date: 2024-09-03 +tags: [ja, open_source, pipeline, onnx] +task: Embeddings +language: ja +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_small_japanese_pipeline` is a Japanese model originally trained by izumi-lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_small_japanese_pipeline_ja_5.5.0_3.0_1725331544357.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_small_japanese_pipeline_ja_5.5.0_3.0_1725331544357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v2_small_japanese_pipeline", lang = "ja") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v2_small_japanese_pipeline", lang = "ja") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v2_small_japanese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ja| +|Size:|34.5 MB| + +## References + +https://huggingface.co/izumi-lab/deberta-v2-small-japanese + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_autotrain_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_autotrain_en.md new file mode 100644 index 00000000000000..88ad2a78307ee9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_autotrain_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_base_autotrain DeBertaEmbeddings from abhishek +author: John Snow Labs +name: deberta_v3_base_autotrain +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_autotrain` is a English model originally trained by abhishek. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_autotrain_en_5.5.0_3.0_1725331007086.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_autotrain_en_5.5.0_3.0_1725331007086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_v3_base_autotrain","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_v3_base_autotrain","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_autotrain| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|435.2 MB| + +## References + +https://huggingface.co/abhishek/deberta-v3-base-autotrain \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_autotrain_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_autotrain_pipeline_en.md new file mode 100644 index 00000000000000..3a5aab33165e5b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_autotrain_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_base_autotrain_pipeline pipeline DeBertaEmbeddings from abhishek +author: John Snow Labs +name: deberta_v3_base_autotrain_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_autotrain_pipeline` is a English model originally trained by abhishek. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_autotrain_pipeline_en_5.5.0_3.0_1725331138023.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_autotrain_pipeline_en_5.5.0_3.0_1725331138023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_base_autotrain_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_base_autotrain_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_base_autotrain_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|435.2 MB| + +## References + +https://huggingface.co/abhishek/deberta-v3-base-autotrain + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_xsmall_dapt_scientific_papers_pubmed_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_xsmall_dapt_scientific_papers_pubmed_en.md new file mode 100644 index 00000000000000..d498c5506a18ce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_xsmall_dapt_scientific_papers_pubmed_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_xsmall_dapt_scientific_papers_pubmed DeBertaEmbeddings from domenicrosati +author: John Snow Labs +name: deberta_xsmall_dapt_scientific_papers_pubmed +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_xsmall_dapt_scientific_papers_pubmed` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_xsmall_dapt_scientific_papers_pubmed_en_5.5.0_3.0_1725331279124.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_xsmall_dapt_scientific_papers_pubmed_en_5.5.0_3.0_1725331279124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("deberta_xsmall_dapt_scientific_papers_pubmed","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("deberta_xsmall_dapt_scientific_papers_pubmed","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_xsmall_dapt_scientific_papers_pubmed| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|244.9 MB| + +## References + +https://huggingface.co/domenicrosati/deberta-xsmall-dapt-scientific-papers-pubmed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-deepdanbooruclip_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deepdanbooruclip_pipeline_en.md new file mode 100644 index 00000000000000..58d54e374368ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-deepdanbooruclip_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English deepdanbooruclip_pipeline pipeline CLIPForZeroShotClassification from Chars +author: John Snow Labs +name: deepdanbooruclip_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepdanbooruclip_pipeline` is a English model originally trained by Chars. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepdanbooruclip_pipeline_en_5.5.0_3.0_1725338856824.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepdanbooruclip_pipeline_en_5.5.0_3.0_1725338856824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deepdanbooruclip_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deepdanbooruclip_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deepdanbooruclip_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/Chars/DeepDanbooruClip + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-dictabert_tiny_he.md b/docs/_posts/ahmedlone127/2024-09-03-dictabert_tiny_he.md new file mode 100644 index 00000000000000..610c8cc6c4e7f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-dictabert_tiny_he.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Hebrew dictabert_tiny BertEmbeddings from dicta-il +author: John Snow Labs +name: dictabert_tiny +date: 2024-09-03 +tags: [he, open_source, onnx, embeddings, bert] +task: Embeddings +language: he +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dictabert_tiny` is a Hebrew model originally trained by dicta-il. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dictabert_tiny_he_5.5.0_3.0_1725323979089.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dictabert_tiny_he_5.5.0_3.0_1725323979089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = BertEmbeddings.pretrained("dictabert_tiny","he") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("dictabert_tiny","he") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dictabert_tiny| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|he| +|Size:|108.4 MB| + +## References + +https://huggingface.co/dicta-il/dictabert-tiny \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-dictabert_tiny_pipeline_he.md b/docs/_posts/ahmedlone127/2024-09-03-dictabert_tiny_pipeline_he.md new file mode 100644 index 00000000000000..147c2701de6b6d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-dictabert_tiny_pipeline_he.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Hebrew dictabert_tiny_pipeline pipeline BertEmbeddings from dicta-il +author: John Snow Labs +name: dictabert_tiny_pipeline +date: 2024-09-03 +tags: [he, open_source, pipeline, onnx] +task: Embeddings +language: he +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dictabert_tiny_pipeline` is a Hebrew model originally trained by dicta-il. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dictabert_tiny_pipeline_he_5.5.0_3.0_1725324010367.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dictabert_tiny_pipeline_he_5.5.0_3.0_1725324010367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dictabert_tiny_pipeline", lang = "he") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dictabert_tiny_pipeline", lang = "he") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dictabert_tiny_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|he| +|Size:|108.4 MB| + +## References + +https://huggingface.co/dicta-il/dictabert-tiny + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-dirty_e5_base_unsupervised_en.md b/docs/_posts/ahmedlone127/2024-09-03-dirty_e5_base_unsupervised_en.md new file mode 100644 index 00000000000000..50a90c4690465c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-dirty_e5_base_unsupervised_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English dirty_e5_base_unsupervised E5Embeddings from rithwik-db +author: John Snow Labs +name: dirty_e5_base_unsupervised +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dirty_e5_base_unsupervised` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dirty_e5_base_unsupervised_en_5.5.0_3.0_1725344560807.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dirty_e5_base_unsupervised_en_5.5.0_3.0_1725344560807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("dirty_e5_base_unsupervised","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("dirty_e5_base_unsupervised","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dirty_e5_base_unsupervised| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|386.0 MB| + +## References + +https://huggingface.co/rithwik-db/dirty-e5-base-unsupervised \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_fake_news_tfg_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_fake_news_tfg_en.md new file mode 100644 index 00000000000000..726343028581d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_fake_news_tfg_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_fake_news_tfg DistilBertForSequenceClassification from LittleFish-Coder +author: John Snow Labs +name: distilbert_base_uncased_fake_news_tfg +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_fake_news_tfg` is a English model originally trained by LittleFish-Coder. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_fake_news_tfg_en_5.5.0_3.0_1725329952629.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_fake_news_tfg_en_5.5.0_3.0_1725329952629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_fake_news_tfg","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_fake_news_tfg", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_fake_news_tfg| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/LittleFish-Coder/distilbert-base-uncased-fake-news-tfg \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotions_depi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotions_depi_pipeline_en.md new file mode 100644 index 00000000000000..dd82e7e29dd495 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotions_depi_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotions_depi_pipeline pipeline DistilBertForSequenceClassification from agoor97 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotions_depi_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotions_depi_pipeline` is a English model originally trained by agoor97. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_depi_pipeline_en_5.5.0_3.0_1725330056214.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_depi_pipeline_en_5.5.0_3.0_1725330056214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotions_depi_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotions_depi_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotions_depi_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/agoor97/distilbert-base-uncased-finetuned-emotions-DEPI + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_french_chamorro_cree_entry_classification_fr.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_french_chamorro_cree_entry_classification_fr.md new file mode 100644 index 00000000000000..da8786d6dcb901 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_french_chamorro_cree_entry_classification_fr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: French distilbert_base_uncased_french_chamorro_cree_entry_classification DistilBertForSequenceClassification from reflex-project +author: John Snow Labs +name: distilbert_base_uncased_french_chamorro_cree_entry_classification +date: 2024-09-03 +tags: [fr, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_french_chamorro_cree_entry_classification` is a French model originally trained by reflex-project. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_french_chamorro_cree_entry_classification_fr_5.5.0_3.0_1725330112014.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_french_chamorro_cree_entry_classification_fr_5.5.0_3.0_1725330112014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_french_chamorro_cree_entry_classification","fr") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_french_chamorro_cree_entry_classification", "fr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_french_chamorro_cree_entry_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|fr| +|Size:|249.5 MB| + +## References + +https://huggingface.co/reflex-project/distilbert-base-uncased-french-ch-cr-entry-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_french_chamorro_cree_entry_classification_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_french_chamorro_cree_entry_classification_pipeline_fr.md new file mode 100644 index 00000000000000..045263d77f1978 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_french_chamorro_cree_entry_classification_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French distilbert_base_uncased_french_chamorro_cree_entry_classification_pipeline pipeline DistilBertForSequenceClassification from reflex-project +author: John Snow Labs +name: distilbert_base_uncased_french_chamorro_cree_entry_classification_pipeline +date: 2024-09-03 +tags: [fr, open_source, pipeline, onnx] +task: Text Classification +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_french_chamorro_cree_entry_classification_pipeline` is a French model originally trained by reflex-project. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_french_chamorro_cree_entry_classification_pipeline_fr_5.5.0_3.0_1725330124035.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_french_chamorro_cree_entry_classification_pipeline_fr_5.5.0_3.0_1725330124035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_french_chamorro_cree_entry_classification_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_french_chamorro_cree_entry_classification_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_french_chamorro_cree_entry_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|249.5 MB| + +## References + +https://huggingface.co/reflex-project/distilbert-base-uncased-french-ch-cr-entry-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_mic_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_mic_en.md new file mode 100644 index 00000000000000..5d9b6e738ffcf4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_mic_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilroberta_base_mic RoBertaForSequenceClassification from agi-css +author: John Snow Labs +name: distilroberta_base_mic +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_mic` is a English model originally trained by agi-css. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_mic_en_5.5.0_3.0_1725337484042.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_mic_en_5.5.0_3.0_1725337484042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_base_mic","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_base_mic", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilroberta_base_mic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|309.0 MB| + +## References + +https://huggingface.co/agi-css/distilroberta-base-mic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_nsfw_prompt_stable_diffusion_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_nsfw_prompt_stable_diffusion_en.md new file mode 100644 index 00000000000000..927bd8bacc1f95 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_nsfw_prompt_stable_diffusion_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilroberta_nsfw_prompt_stable_diffusion RoBertaForSequenceClassification from AdamCodd +author: John Snow Labs +name: distilroberta_nsfw_prompt_stable_diffusion +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_nsfw_prompt_stable_diffusion` is a English model originally trained by AdamCodd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_nsfw_prompt_stable_diffusion_en_5.5.0_3.0_1725336545805.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_nsfw_prompt_stable_diffusion_en_5.5.0_3.0_1725336545805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_nsfw_prompt_stable_diffusion","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_nsfw_prompt_stable_diffusion", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilroberta_nsfw_prompt_stable_diffusion| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|309.0 MB| + +## References + +https://huggingface.co/AdamCodd/distilroberta-nsfw-prompt-stable-diffusion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_spam_comments_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_spam_comments_detection_pipeline_en.md new file mode 100644 index 00000000000000..a81d23fa5e950b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_spam_comments_detection_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilroberta_spam_comments_detection_pipeline pipeline RoBertaForSequenceClassification from valurank +author: John Snow Labs +name: distilroberta_spam_comments_detection_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_spam_comments_detection_pipeline` is a English model originally trained by valurank. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_spam_comments_detection_pipeline_en_5.5.0_3.0_1725337164011.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_spam_comments_detection_pipeline_en_5.5.0_3.0_1725337164011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilroberta_spam_comments_detection_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilroberta_spam_comments_detection_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilroberta_spam_comments_detection_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|309.1 MB| + +## References + +https://huggingface.co/valurank/distilroberta-spam-comments-detection + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-drawify_snapsearch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-drawify_snapsearch_pipeline_en.md new file mode 100644 index 00000000000000..213f6de1a3c07a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-drawify_snapsearch_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English drawify_snapsearch_pipeline pipeline CLIPForZeroShotClassification from drift-ai +author: John Snow Labs +name: drawify_snapsearch_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`drawify_snapsearch_pipeline` is a English model originally trained by drift-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/drawify_snapsearch_pipeline_en_5.5.0_3.0_1725338118710.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/drawify_snapsearch_pipeline_en_5.5.0_3.0_1725338118710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("drawify_snapsearch_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("drawify_snapsearch_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|drawify_snapsearch_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/drift-ai/drawify-snapsearch + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_en.md new file mode 100644 index 00000000000000..e02ef427d8e197 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English dummy CamemBertForSequenceClassification from Longtong +author: John Snow Labs +name: dummy +date: 2024-09-03 +tags: [camembert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy` is a English model originally trained by Longtong. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_en_5.5.0_3.0_1725325427885.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_en_5.5.0_3.0_1725325427885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("dummy","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("dummy","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|266.2 MB| + +## References + +References + +https://huggingface.co/Longtong/dummy \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_100k_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_100k_en.md new file mode 100644 index 00000000000000..7e4002a2bbb302 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_100k_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_100k E5Embeddings from heka-ai +author: John Snow Labs +name: e5_100k +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_100k` is a English model originally trained by heka-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_100k_en_5.5.0_3.0_1725344907168.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_100k_en_5.5.0_3.0_1725344907168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_100k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_100k","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_100k| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/heka-ai/e5-100k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_100k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_100k_pipeline_en.md new file mode 100644 index 00000000000000..493feadf0dbe95 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_100k_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English e5_100k_pipeline pipeline E5Embeddings from heka-ai +author: John Snow Labs +name: e5_100k_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_100k_pipeline` is a English model originally trained by heka-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_100k_pipeline_en_5.5.0_3.0_1725344919306.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_100k_pipeline_en_5.5.0_3.0_1725344919306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_100k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_100k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_100k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/heka-ai/e5-100k + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_4k_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_4k_en.md new file mode 100644 index 00000000000000..eecc0008ad4880 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_4k_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_base_4k E5Embeddings from dwzhu +author: John Snow Labs +name: e5_base_4k +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_4k` is a English model originally trained by dwzhu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_4k_en_5.5.0_3.0_1725332593236.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_4k_en_5.5.0_3.0_1725332593236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_base_4k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_base_4k","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_4k| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|265.3 MB| + +## References + +https://huggingface.co/dwzhu/e5-base-4k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_4k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_4k_pipeline_en.md new file mode 100644 index 00000000000000..56b2aceb2c0884 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_4k_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English e5_base_4k_pipeline pipeline E5Embeddings from dwzhu +author: John Snow Labs +name: e5_base_4k_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_4k_pipeline` is a English model originally trained by dwzhu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_4k_pipeline_en_5.5.0_3.0_1725332673749.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_4k_pipeline_en_5.5.0_3.0_1725332673749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_base_4k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_base_4k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_4k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|265.3 MB| + +## References + +https://huggingface.co/dwzhu/e5-base-4k + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_banking77_10000_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_banking77_10000_en.md new file mode 100644 index 00000000000000..94d3fac94eb0e5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_banking77_10000_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_base_banking77_10000 E5Embeddings from rithwik-db +author: John Snow Labs +name: e5_base_banking77_10000 +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_banking77_10000` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_banking77_10000_en_5.5.0_3.0_1725332127648.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_banking77_10000_en_5.5.0_3.0_1725332127648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_base_banking77_10000","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_base_banking77_10000","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_banking77_10000| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|380.6 MB| + +## References + +https://huggingface.co/rithwik-db/e5-base_banking77_10000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_banking77_10000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_banking77_10000_pipeline_en.md new file mode 100644 index 00000000000000..0e92ab08d48251 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_banking77_10000_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English e5_base_banking77_10000_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: e5_base_banking77_10000_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_banking77_10000_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_banking77_10000_pipeline_en_5.5.0_3.0_1725332154581.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_banking77_10000_pipeline_en_5.5.0_3.0_1725332154581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_base_banking77_10000_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_base_banking77_10000_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_banking77_10000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|380.7 MB| + +## References + +https://huggingface.co/rithwik-db/e5-base_banking77_10000 + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_consensus_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_consensus_pipeline_en.md new file mode 100644 index 00000000000000..f373eade9ab5d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_consensus_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English e5_base_consensus_pipeline pipeline E5Embeddings from Consensus +author: John Snow Labs +name: e5_base_consensus_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_consensus_pipeline` is a English model originally trained by Consensus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_consensus_pipeline_en_5.5.0_3.0_1725332938718.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_consensus_pipeline_en_5.5.0_3.0_1725332938718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_base_consensus_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_base_consensus_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_consensus_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|258.6 MB| + +## References + +https://huggingface.co/Consensus/e5-base + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_scifact_10000_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_scifact_10000_en.md new file mode 100644 index 00000000000000..562b0a4b383ad1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_scifact_10000_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_base_scifact_10000 E5Embeddings from rithwik-db +author: John Snow Labs +name: e5_base_scifact_10000 +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_scifact_10000` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_scifact_10000_en_5.5.0_3.0_1725345025049.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_scifact_10000_en_5.5.0_3.0_1725345025049.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_base_scifact_10000","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_base_scifact_10000","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_scifact_10000| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|389.8 MB| + +## References + +https://huggingface.co/rithwik-db/e5-base_scifact_10000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_scifact_5000_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_scifact_5000_en.md new file mode 100644 index 00000000000000..a2d71a9e7d6cd4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_scifact_5000_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_base_unsupervised_scifact_5000 E5Embeddings from rithwik-db +author: John Snow Labs +name: e5_base_unsupervised_scifact_5000 +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_scifact_5000` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_scifact_5000_en_5.5.0_3.0_1725344915885.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_scifact_5000_en_5.5.0_3.0_1725344915885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_base_unsupervised_scifact_5000","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_base_unsupervised_scifact_5000","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_unsupervised_scifact_5000| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|393.9 MB| + +## References + +https://huggingface.co/rithwik-db/e5-base-unsupervised_scifact_5000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_v2_intfloat_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_v2_intfloat_en.md new file mode 100644 index 00000000000000..3760804b87a467 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_v2_intfloat_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_base_v2_intfloat E5Embeddings from intfloat +author: John Snow Labs +name: e5_base_v2_intfloat +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_v2_intfloat` is a English model originally trained by intfloat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_v2_intfloat_en_5.5.0_3.0_1725332416348.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_v2_intfloat_en_5.5.0_3.0_1725332416348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_base_v2_intfloat","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_base_v2_intfloat","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_v2_intfloat| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|258.7 MB| + +## References + +https://huggingface.co/intfloat/e5-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_v2_vectoriseai_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_v2_vectoriseai_en.md new file mode 100644 index 00000000000000..e2b032469f778a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_v2_vectoriseai_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_base_v2_vectoriseai E5Embeddings from vectoriseai +author: John Snow Labs +name: e5_base_v2_vectoriseai +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_v2_vectoriseai` is a English model originally trained by vectoriseai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_v2_vectoriseai_en_5.5.0_3.0_1725344429058.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_v2_vectoriseai_en_5.5.0_3.0_1725344429058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_base_v2_vectoriseai","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_base_v2_vectoriseai","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_v2_vectoriseai| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|258.7 MB| + +## References + +https://huggingface.co/vectoriseai/e5-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_vectoriseai_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_vectoriseai_en.md new file mode 100644 index 00000000000000..c01ac7d4d0251f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_vectoriseai_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_base_vectoriseai E5Embeddings from vectoriseai +author: John Snow Labs +name: e5_base_vectoriseai +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_vectoriseai` is a English model originally trained by vectoriseai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_vectoriseai_en_5.5.0_3.0_1725344288266.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_vectoriseai_en_5.5.0_3.0_1725344288266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_base_vectoriseai","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_base_vectoriseai","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_vectoriseai| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|258.6 MB| + +## References + +https://huggingface.co/vectoriseai/e5-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_large_unsupervised_pseudo_genq_1_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_large_unsupervised_pseudo_genq_1_en.md new file mode 100644 index 00000000000000..493221e7dfa0e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_large_unsupervised_pseudo_genq_1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_large_unsupervised_pseudo_genq_1 E5Embeddings from rithwik-db +author: John Snow Labs +name: e5_large_unsupervised_pseudo_genq_1 +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_unsupervised_pseudo_genq_1` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_unsupervised_pseudo_genq_1_en_5.5.0_3.0_1725340660633.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_unsupervised_pseudo_genq_1_en_5.5.0_3.0_1725340660633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_large_unsupervised_pseudo_genq_1","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_large_unsupervised_pseudo_genq_1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_large_unsupervised_pseudo_genq_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/rithwik-db/e5-large-unsupervised-pseudo-genq-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_large_unsupervised_pseudo_genq_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_large_unsupervised_pseudo_genq_1_pipeline_en.md new file mode 100644 index 00000000000000..4865b19ca6cea9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_large_unsupervised_pseudo_genq_1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English e5_large_unsupervised_pseudo_genq_1_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: e5_large_unsupervised_pseudo_genq_1_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_unsupervised_pseudo_genq_1_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_unsupervised_pseudo_genq_1_pipeline_en_5.5.0_3.0_1725340730917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_unsupervised_pseudo_genq_1_pipeline_en_5.5.0_3.0_1725340730917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_large_unsupervised_pseudo_genq_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_large_unsupervised_pseudo_genq_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_large_unsupervised_pseudo_genq_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/rithwik-db/e5-large-unsupervised-pseudo-genq-1 + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_small_unsupervised_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_small_unsupervised_en.md new file mode 100644 index 00000000000000..16c6d737ec6f04 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_small_unsupervised_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_small_unsupervised E5Embeddings from intfloat +author: John Snow Labs +name: e5_small_unsupervised +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_small_unsupervised` is a English model originally trained by intfloat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_small_unsupervised_en_5.5.0_3.0_1725332347555.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_small_unsupervised_en_5.5.0_3.0_1725332347555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_small_unsupervised","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_small_unsupervised","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_small_unsupervised| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|80.0 MB| + +## References + +https://huggingface.co/intfloat/e5-small-unsupervised \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_small_v2_intfloat_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_small_v2_intfloat_en.md new file mode 100644 index 00000000000000..566642c216801c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_small_v2_intfloat_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_small_v2_intfloat E5Embeddings from intfloat +author: John Snow Labs +name: e5_small_v2_intfloat +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_small_v2_intfloat` is a English model originally trained by intfloat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_small_v2_intfloat_en_5.5.0_3.0_1725332407809.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_small_v2_intfloat_en_5.5.0_3.0_1725332407809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_small_v2_intfloat","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_small_v2_intfloat","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_small_v2_intfloat| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|79.9 MB| + +## References + +https://huggingface.co/intfloat/e5-small-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_small_v2_vectoriseai_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_small_v2_vectoriseai_en.md new file mode 100644 index 00000000000000..d6d9914e48a60c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_small_v2_vectoriseai_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English e5_small_v2_vectoriseai E5Embeddings from vectoriseai +author: John Snow Labs +name: e5_small_v2_vectoriseai +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_small_v2_vectoriseai` is a English model originally trained by vectoriseai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_small_v2_vectoriseai_en_5.5.0_3.0_1725340345635.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_small_v2_vectoriseai_en_5.5.0_3.0_1725340345635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("e5_small_v2_vectoriseai","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("e5_small_v2_vectoriseai","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_small_v2_vectoriseai| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|79.9 MB| + +## References + +https://huggingface.co/vectoriseai/e5-small-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_small_v2_vectoriseai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_small_v2_vectoriseai_pipeline_en.md new file mode 100644 index 00000000000000..e7ce21e9430182 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-e5_small_v2_vectoriseai_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English e5_small_v2_vectoriseai_pipeline pipeline E5Embeddings from vectoriseai +author: John Snow Labs +name: e5_small_v2_vectoriseai_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_small_v2_vectoriseai_pipeline` is a English model originally trained by vectoriseai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_small_v2_vectoriseai_pipeline_en_5.5.0_3.0_1725340369811.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_small_v2_vectoriseai_pipeline_en_5.5.0_3.0_1725340369811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_small_v2_vectoriseai_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_small_v2_vectoriseai_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_small_v2_vectoriseai_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|79.9 MB| + +## References + +https://huggingface.co/vectoriseai/e5-small-v2 + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_base_500_en.md b/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_base_500_en.md new file mode 100644 index 00000000000000..88ad64f788e75e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_base_500_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English embedded_e5_base_500 E5Embeddings from rithwik-db +author: John Snow Labs +name: embedded_e5_base_500 +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`embedded_e5_base_500` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/embedded_e5_base_500_en_5.5.0_3.0_1725344468403.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/embedded_e5_base_500_en_5.5.0_3.0_1725344468403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("embedded_e5_base_500","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("embedded_e5_base_500","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|embedded_e5_base_500| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|387.6 MB| + +## References + +https://huggingface.co/rithwik-db/embedded-e5-base-500 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_base_50_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_base_50_10_pipeline_en.md new file mode 100644 index 00000000000000..2b89cdff80bfe8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_base_50_10_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English embedded_e5_base_50_10_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: embedded_e5_base_50_10_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`embedded_e5_base_50_10_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/embedded_e5_base_50_10_pipeline_en_5.5.0_3.0_1725340904635.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/embedded_e5_base_50_10_pipeline_en_5.5.0_3.0_1725340904635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("embedded_e5_base_50_10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("embedded_e5_base_50_10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|embedded_e5_base_50_10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|382.1 MB| + +## References + +https://huggingface.co/rithwik-db/embedded-e5-base-50-10 + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_large_500_correct_en.md b/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_large_500_correct_en.md new file mode 100644 index 00000000000000..dd9c32cb3983db --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_large_500_correct_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English embedded_e5_large_500_correct E5Embeddings from rithwik-db +author: John Snow Labs +name: embedded_e5_large_500_correct +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`embedded_e5_large_500_correct` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/embedded_e5_large_500_correct_en_5.5.0_3.0_1725341055498.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/embedded_e5_large_500_correct_en_5.5.0_3.0_1725341055498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("embedded_e5_large_500_correct","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("embedded_e5_large_500_correct","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|embedded_e5_large_500_correct| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/rithwik-db/embedded-e5-large-500-correct \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_large_500_correct_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_large_500_correct_pipeline_en.md new file mode 100644 index 00000000000000..10e31710a6604d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_large_500_correct_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English embedded_e5_large_500_correct_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: embedded_e5_large_500_correct_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`embedded_e5_large_500_correct_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/embedded_e5_large_500_correct_pipeline_en_5.5.0_3.0_1725341123045.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/embedded_e5_large_500_correct_pipeline_en_5.5.0_3.0_1725341123045.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("embedded_e5_large_500_correct_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("embedded_e5_large_500_correct_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|embedded_e5_large_500_correct_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/rithwik-db/embedded-e5-large-500-correct + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-fashion_clip_emaghakyan_en.md b/docs/_posts/ahmedlone127/2024-09-03-fashion_clip_emaghakyan_en.md new file mode 100644 index 00000000000000..a2f72b043ce4e8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-fashion_clip_emaghakyan_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English fashion_clip_emaghakyan CLIPForZeroShotClassification from EMaghakyan +author: John Snow Labs +name: fashion_clip_emaghakyan +date: 2024-09-03 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_clip_emaghakyan` is a English model originally trained by EMaghakyan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_clip_emaghakyan_en_5.5.0_3.0_1725338595709.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_clip_emaghakyan_en_5.5.0_3.0_1725338595709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("fashion_clip_emaghakyan","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("fashion_clip_emaghakyan","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fashion_clip_emaghakyan| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.7 MB| + +## References + +https://huggingface.co/EMaghakyan/fashion-clip \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-fashion_clip_emaghakyan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-fashion_clip_emaghakyan_pipeline_en.md new file mode 100644 index 00000000000000..a0a0445f681f6a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-fashion_clip_emaghakyan_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fashion_clip_emaghakyan_pipeline pipeline CLIPForZeroShotClassification from EMaghakyan +author: John Snow Labs +name: fashion_clip_emaghakyan_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_clip_emaghakyan_pipeline` is a English model originally trained by EMaghakyan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_clip_emaghakyan_pipeline_en_5.5.0_3.0_1725338691505.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_clip_emaghakyan_pipeline_en_5.5.0_3.0_1725338691505.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fashion_clip_emaghakyan_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fashion_clip_emaghakyan_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fashion_clip_emaghakyan_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.7 MB| + +## References + +https://huggingface.co/EMaghakyan/fashion-clip + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-fashion_pattern_clip_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-fashion_pattern_clip_pipeline_en.md new file mode 100644 index 00000000000000..21eeefd53481c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-fashion_pattern_clip_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fashion_pattern_clip_pipeline pipeline CLIPForZeroShotClassification from yainage90 +author: John Snow Labs +name: fashion_pattern_clip_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_pattern_clip_pipeline` is a English model originally trained by yainage90. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_pattern_clip_pipeline_en_5.5.0_3.0_1725338295159.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_pattern_clip_pipeline_en_5.5.0_3.0_1725338295159.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fashion_pattern_clip_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fashion_pattern_clip_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fashion_pattern_clip_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|568.0 MB| + +## References + +https://huggingface.co/yainage90/fashion-pattern-clip + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-feel_italian_finetuned_pro_emit_big6_en.md b/docs/_posts/ahmedlone127/2024-09-03-feel_italian_finetuned_pro_emit_big6_en.md new file mode 100644 index 00000000000000..354b3e20e9653f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-feel_italian_finetuned_pro_emit_big6_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English feel_italian_finetuned_pro_emit_big6 CamemBertForSequenceClassification from lupobricco +author: John Snow Labs +name: feel_italian_finetuned_pro_emit_big6 +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`feel_italian_finetuned_pro_emit_big6` is a English model originally trained by lupobricco. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_big6_en_5.5.0_3.0_1725324952514.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_big6_en_5.5.0_3.0_1725324952514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("feel_italian_finetuned_pro_emit_big6","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("feel_italian_finetuned_pro_emit_big6", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|feel_italian_finetuned_pro_emit_big6| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|399.1 MB| + +## References + +https://huggingface.co/lupobricco/feel_it_finetuned_pro_emit_big6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-feel_italian_finetuned_pro_emit_big6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-feel_italian_finetuned_pro_emit_big6_pipeline_en.md new file mode 100644 index 00000000000000..89fb7d38ec6494 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-feel_italian_finetuned_pro_emit_big6_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English feel_italian_finetuned_pro_emit_big6_pipeline pipeline CamemBertForSequenceClassification from lupobricco +author: John Snow Labs +name: feel_italian_finetuned_pro_emit_big6_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`feel_italian_finetuned_pro_emit_big6_pipeline` is a English model originally trained by lupobricco. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_big6_pipeline_en_5.5.0_3.0_1725324976260.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_big6_pipeline_en_5.5.0_3.0_1725324976260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("feel_italian_finetuned_pro_emit_big6_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("feel_italian_finetuned_pro_emit_big6_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|feel_italian_finetuned_pro_emit_big6_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|399.1 MB| + +## References + +https://huggingface.co/lupobricco/feel_it_finetuned_pro_emit_big6 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-final_luna_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-final_luna_sentiment_analysis_pipeline_en.md new file mode 100644 index 00000000000000..388198658024b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-final_luna_sentiment_analysis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English final_luna_sentiment_analysis_pipeline pipeline RoBertaForSequenceClassification from snoneeightfive +author: John Snow Labs +name: final_luna_sentiment_analysis_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`final_luna_sentiment_analysis_pipeline` is a English model originally trained by snoneeightfive. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/final_luna_sentiment_analysis_pipeline_en_5.5.0_3.0_1725336922949.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_luna_sentiment_analysis_pipeline_en_5.5.0_3.0_1725336922949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("final_luna_sentiment_analysis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("final_luna_sentiment_analysis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|final_luna_sentiment_analysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/snoneeightfive/final-luna-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-fine_tuned_hf_language_identification_model_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-fine_tuned_hf_language_identification_model_pipeline_xx.md new file mode 100644 index 00000000000000..86fabec42072c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-fine_tuned_hf_language_identification_model_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual fine_tuned_hf_language_identification_model_pipeline pipeline XlmRoBertaForSequenceClassification from Joshi-Aryan +author: John Snow Labs +name: fine_tuned_hf_language_identification_model_pipeline +date: 2024-09-03 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_hf_language_identification_model_pipeline` is a Multilingual model originally trained by Joshi-Aryan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_hf_language_identification_model_pipeline_xx_5.5.0_3.0_1725328580103.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_hf_language_identification_model_pipeline_xx_5.5.0_3.0_1725328580103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_hf_language_identification_model_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_hf_language_identification_model_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_hf_language_identification_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|854.4 MB| + +## References + +https://huggingface.co/Joshi-Aryan/Fine_Tuned_HF_Language_Identification_Model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuned_kde4_english_tonga_tonga_islands_french_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuned_kde4_english_tonga_tonga_islands_french_pipeline_en.md new file mode 100644 index 00000000000000..c007667f6e785f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-finetuned_kde4_english_tonga_tonga_islands_french_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_kde4_english_tonga_tonga_islands_french_pipeline pipeline MarianTransformer from jcheigh +author: John Snow Labs +name: finetuned_kde4_english_tonga_tonga_islands_french_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_kde4_english_tonga_tonga_islands_french_pipeline` is a English model originally trained by jcheigh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_kde4_english_tonga_tonga_islands_french_pipeline_en_5.5.0_3.0_1725346121403.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_kde4_english_tonga_tonga_islands_french_pipeline_en_5.5.0_3.0_1725346121403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_kde4_english_tonga_tonga_islands_french_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_kde4_english_tonga_tonga_islands_french_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_kde4_english_tonga_tonga_islands_french_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.8 MB| + +## References + +https://huggingface.co/jcheigh/finetuned-kde4-en-to-fr + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuned_polish_tonga_tonga_islands_szl_siling_corrected_aligned_20e_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuned_polish_tonga_tonga_islands_szl_siling_corrected_aligned_20e_en.md new file mode 100644 index 00000000000000..0130dccb41a863 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-finetuned_polish_tonga_tonga_islands_szl_siling_corrected_aligned_20e_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_polish_tonga_tonga_islands_szl_siling_corrected_aligned_20e MarianTransformer from brjezierski +author: John Snow Labs +name: finetuned_polish_tonga_tonga_islands_szl_siling_corrected_aligned_20e +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_polish_tonga_tonga_islands_szl_siling_corrected_aligned_20e` is a English model originally trained by brjezierski. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_polish_tonga_tonga_islands_szl_siling_corrected_aligned_20e_en_5.5.0_3.0_1725345674922.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_polish_tonga_tonga_islands_szl_siling_corrected_aligned_20e_en_5.5.0_3.0_1725345674922.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("finetuned_polish_tonga_tonga_islands_szl_siling_corrected_aligned_20e","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("finetuned_polish_tonga_tonga_islands_szl_siling_corrected_aligned_20e","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_polish_tonga_tonga_islands_szl_siling_corrected_aligned_20e| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|385.9 MB| + +## References + +https://huggingface.co/brjezierski/finetuned-pl-to-szl-siling-corrected-aligned-20e \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuned_twitter_xlm_roberta_base_emotion_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuned_twitter_xlm_roberta_base_emotion_en.md new file mode 100644 index 00000000000000..9d8bb7d8c50e93 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-finetuned_twitter_xlm_roberta_base_emotion_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_twitter_xlm_roberta_base_emotion XlmRoBertaForSequenceClassification from 02shanky +author: John Snow Labs +name: finetuned_twitter_xlm_roberta_base_emotion +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_twitter_xlm_roberta_base_emotion` is a English model originally trained by 02shanky. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_twitter_xlm_roberta_base_emotion_en_5.5.0_3.0_1725328616140.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_twitter_xlm_roberta_base_emotion_en_5.5.0_3.0_1725328616140.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("finetuned_twitter_xlm_roberta_base_emotion","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("finetuned_twitter_xlm_roberta_base_emotion", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_twitter_xlm_roberta_base_emotion| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/02shanky/finetuned-twitter-xlm-roberta-base-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuned_twitter_xlm_roberta_base_emotion_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuned_twitter_xlm_roberta_base_emotion_pipeline_en.md new file mode 100644 index 00000000000000..9a19dc0f10143e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-finetuned_twitter_xlm_roberta_base_emotion_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_twitter_xlm_roberta_base_emotion_pipeline pipeline XlmRoBertaForSequenceClassification from 02shanky +author: John Snow Labs +name: finetuned_twitter_xlm_roberta_base_emotion_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_twitter_xlm_roberta_base_emotion_pipeline` is a English model originally trained by 02shanky. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_twitter_xlm_roberta_base_emotion_pipeline_en_5.5.0_3.0_1725328668176.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_twitter_xlm_roberta_base_emotion_pipeline_en_5.5.0_3.0_1725328668176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_twitter_xlm_roberta_base_emotion_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_twitter_xlm_roberta_base_emotion_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_twitter_xlm_roberta_base_emotion_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/02shanky/finetuned-twitter-xlm-roberta-base-emotion + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-flip_base_16_en.md b/docs/_posts/ahmedlone127/2024-09-03-flip_base_16_en.md new file mode 100644 index 00000000000000..dbd17ea5933a6d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-flip_base_16_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English flip_base_16 CLIPForZeroShotClassification from FLIP-dataset +author: John Snow Labs +name: flip_base_16 +date: 2024-09-03 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flip_base_16` is a English model originally trained by FLIP-dataset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flip_base_16_en_5.5.0_3.0_1725338254078.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flip_base_16_en_5.5.0_3.0_1725338254078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("flip_base_16","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("flip_base_16","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|flip_base_16| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|561.2 MB| + +## References + +https://huggingface.co/FLIP-dataset/FLIP-base-16 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-flip_base_16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-flip_base_16_pipeline_en.md new file mode 100644 index 00000000000000..6db91ace53f6df --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-flip_base_16_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English flip_base_16_pipeline pipeline CLIPForZeroShotClassification from FLIP-dataset +author: John Snow Labs +name: flip_base_16_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flip_base_16_pipeline` is a English model originally trained by FLIP-dataset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flip_base_16_pipeline_en_5.5.0_3.0_1725338281908.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flip_base_16_pipeline_en_5.5.0_3.0_1725338281908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("flip_base_16_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("flip_base_16_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|flip_base_16_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|561.2 MB| + +## References + +https://huggingface.co/FLIP-dataset/FLIP-base-16 + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-french_wolof_classification_en.md b/docs/_posts/ahmedlone127/2024-09-03-french_wolof_classification_en.md new file mode 100644 index 00000000000000..1489381df3fcb3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-french_wolof_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English french_wolof_classification DistilBertForSequenceClassification from Alwaly +author: John Snow Labs +name: french_wolof_classification +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`french_wolof_classification` is a English model originally trained by Alwaly. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/french_wolof_classification_en_5.5.0_3.0_1725329642452.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/french_wolof_classification_en_5.5.0_3.0_1725329642452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("french_wolof_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("french_wolof_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|french_wolof_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Alwaly/fr-wo-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-furina_with_transliteration_average_en.md b/docs/_posts/ahmedlone127/2024-09-03-furina_with_transliteration_average_en.md new file mode 100644 index 00000000000000..fe969276233575 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-furina_with_transliteration_average_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English furina_with_transliteration_average XlmRoBertaEmbeddings from yihongLiu +author: John Snow Labs +name: furina_with_transliteration_average +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`furina_with_transliteration_average` is a English model originally trained by yihongLiu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/furina_with_transliteration_average_en_5.5.0_3.0_1725342388904.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/furina_with_transliteration_average_en_5.5.0_3.0_1725342388904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("furina_with_transliteration_average","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("furina_with_transliteration_average","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|furina_with_transliteration_average| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|1.9 GB| + +## References + +https://huggingface.co/yihongLiu/furina-with-transliteration-average \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-gal_ner_iw_3_en.md b/docs/_posts/ahmedlone127/2024-09-03-gal_ner_iw_3_en.md new file mode 100644 index 00000000000000..0b990d0d5507a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-gal_ner_iw_3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English gal_ner_iw_3 XlmRoBertaForTokenClassification from homersimpson +author: John Snow Labs +name: gal_ner_iw_3 +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gal_ner_iw_3` is a English model originally trained by homersimpson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gal_ner_iw_3_en_5.5.0_3.0_1725322657554.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gal_ner_iw_3_en_5.5.0_3.0_1725322657554.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("gal_ner_iw_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("gal_ner_iw_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gal_ner_iw_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|419.5 MB| + +## References + +https://huggingface.co/homersimpson/gal-ner-iw-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-gal_ner_iw_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-gal_ner_iw_3_pipeline_en.md new file mode 100644 index 00000000000000..225cb3b942ecc4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-gal_ner_iw_3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English gal_ner_iw_3_pipeline pipeline XlmRoBertaForTokenClassification from homersimpson +author: John Snow Labs +name: gal_ner_iw_3_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gal_ner_iw_3_pipeline` is a English model originally trained by homersimpson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gal_ner_iw_3_pipeline_en_5.5.0_3.0_1725322688034.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gal_ner_iw_3_pipeline_en_5.5.0_3.0_1725322688034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gal_ner_iw_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gal_ner_iw_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gal_ner_iw_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|419.5 MB| + +## References + +https://huggingface.co/homersimpson/gal-ner-iw-3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-geoloc_entity_linking_cross_encoder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-geoloc_entity_linking_cross_encoder_pipeline_en.md new file mode 100644 index 00000000000000..d0bbf2c9455f5b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-geoloc_entity_linking_cross_encoder_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English geoloc_entity_linking_cross_encoder_pipeline pipeline CamemBertForSequenceClassification from gcaillaut +author: John Snow Labs +name: geoloc_entity_linking_cross_encoder_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`geoloc_entity_linking_cross_encoder_pipeline` is a English model originally trained by gcaillaut. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/geoloc_entity_linking_cross_encoder_pipeline_en_5.5.0_3.0_1725325593991.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/geoloc_entity_linking_cross_encoder_pipeline_en_5.5.0_3.0_1725325593991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("geoloc_entity_linking_cross_encoder_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("geoloc_entity_linking_cross_encoder_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|geoloc_entity_linking_cross_encoder_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|202.2 MB| + +## References + +https://huggingface.co/gcaillaut/geoloc-entity-linking-cross-encoder + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-glot500_with_transliteration_max_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-glot500_with_transliteration_max_pipeline_en.md new file mode 100644 index 00000000000000..8695ee7fb31a51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-glot500_with_transliteration_max_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English glot500_with_transliteration_max_pipeline pipeline XlmRoBertaEmbeddings from yihongLiu +author: John Snow Labs +name: glot500_with_transliteration_max_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`glot500_with_transliteration_max_pipeline` is a English model originally trained by yihongLiu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/glot500_with_transliteration_max_pipeline_en_5.5.0_3.0_1725343940770.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/glot500_with_transliteration_max_pipeline_en_5.5.0_3.0_1725343940770.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("glot500_with_transliteration_max_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("glot500_with_transliteration_max_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|glot500_with_transliteration_max_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.9 GB| + +## References + +https://huggingface.co/yihongLiu/glot500-with-transliteration-max + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-glot500_with_transliteration_minangkabau_en.md b/docs/_posts/ahmedlone127/2024-09-03-glot500_with_transliteration_minangkabau_en.md new file mode 100644 index 00000000000000..e1e2cc02a994ef --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-glot500_with_transliteration_minangkabau_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English glot500_with_transliteration_minangkabau XlmRoBertaEmbeddings from yihongLiu +author: John Snow Labs +name: glot500_with_transliteration_minangkabau +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`glot500_with_transliteration_minangkabau` is a English model originally trained by yihongLiu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/glot500_with_transliteration_minangkabau_en_5.5.0_3.0_1725342871851.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/glot500_with_transliteration_minangkabau_en_5.5.0_3.0_1725342871851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("glot500_with_transliteration_minangkabau","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("glot500_with_transliteration_minangkabau","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|glot500_with_transliteration_minangkabau| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|1.9 GB| + +## References + +https://huggingface.co/yihongLiu/glot500-with-transliteration-min \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_arguana_1_en.md b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_arguana_1_en.md new file mode 100644 index 00000000000000..2e73b5cd5189ce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_arguana_1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English gpl_e5_base_unsupervised_arguana_1 E5Embeddings from rithwik-db +author: John Snow Labs +name: gpl_e5_base_unsupervised_arguana_1 +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpl_e5_base_unsupervised_arguana_1` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_arguana_1_en_5.5.0_3.0_1725341200336.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_arguana_1_en_5.5.0_3.0_1725341200336.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("gpl_e5_base_unsupervised_arguana_1","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("gpl_e5_base_unsupervised_arguana_1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gpl_e5_base_unsupervised_arguana_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|400.3 MB| + +## References + +https://huggingface.co/rithwik-db/gpl-e5-base-unsupervised-arguana-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_curated_2_small_en.md b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_curated_2_small_en.md new file mode 100644 index 00000000000000..f4e76f92aa2f51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_curated_2_small_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English gpl_e5_base_unsupervised_curated_2_small E5Embeddings from rithwik-db +author: John Snow Labs +name: gpl_e5_base_unsupervised_curated_2_small +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpl_e5_base_unsupervised_curated_2_small` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_curated_2_small_en_5.5.0_3.0_1725340463549.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_curated_2_small_en_5.5.0_3.0_1725340463549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("gpl_e5_base_unsupervised_curated_2_small","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("gpl_e5_base_unsupervised_curated_2_small","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gpl_e5_base_unsupervised_curated_2_small| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|388.6 MB| + +## References + +https://huggingface.co/rithwik-db/gpl-e5-base-unsupervised-curated-2-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_scifact_k10_en.md b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_scifact_k10_en.md new file mode 100644 index 00000000000000..f4faa2fa2db701 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_scifact_k10_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English gpl_e5_base_unsupervised_scifact_k10 E5Embeddings from rithwik-db +author: John Snow Labs +name: gpl_e5_base_unsupervised_scifact_k10 +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpl_e5_base_unsupervised_scifact_k10` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_scifact_k10_en_5.5.0_3.0_1725340900167.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_scifact_k10_en_5.5.0_3.0_1725340900167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("gpl_e5_base_unsupervised_scifact_k10","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("gpl_e5_base_unsupervised_scifact_k10","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gpl_e5_base_unsupervised_scifact_k10| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|395.7 MB| + +## References + +https://huggingface.co/rithwik-db/gpl-e5-base-unsupervised-scifact-k10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-gptfuzz_en.md b/docs/_posts/ahmedlone127/2024-09-03-gptfuzz_en.md new file mode 100644 index 00000000000000..16ce917cd952c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-gptfuzz_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English gptfuzz RoBertaForSequenceClassification from hubert233 +author: John Snow Labs +name: gptfuzz +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gptfuzz` is a English model originally trained by hubert233. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gptfuzz_en_5.5.0_3.0_1725337575692.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gptfuzz_en_5.5.0_3.0_1725337575692.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("gptfuzz","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("gptfuzz", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gptfuzz| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/hubert233/GPTFuzz \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-gptfuzz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-gptfuzz_pipeline_en.md new file mode 100644 index 00000000000000..ef39db76c74a9c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-gptfuzz_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English gptfuzz_pipeline pipeline RoBertaForSequenceClassification from hubert233 +author: John Snow Labs +name: gptfuzz_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gptfuzz_pipeline` is a English model originally trained by hubert233. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gptfuzz_pipeline_en_5.5.0_3.0_1725337655677.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gptfuzz_pipeline_en_5.5.0_3.0_1725337655677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gptfuzz_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gptfuzz_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gptfuzz_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/hubert233/GPTFuzz + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-gujibert_jian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-gujibert_jian_pipeline_en.md new file mode 100644 index 00000000000000..b379b7912a8e56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-gujibert_jian_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English gujibert_jian_pipeline pipeline BertEmbeddings from hsc748NLP +author: John Snow Labs +name: gujibert_jian_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gujibert_jian_pipeline` is a English model originally trained by hsc748NLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gujibert_jian_pipeline_en_5.5.0_3.0_1725323981054.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gujibert_jian_pipeline_en_5.5.0_3.0_1725323981054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gujibert_jian_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gujibert_jian_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gujibert_jian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|420.3 MB| + +## References + +https://huggingface.co/hsc748NLP/GujiBERT_jian + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-hel_english_french_4_layers_en.md b/docs/_posts/ahmedlone127/2024-09-03-hel_english_french_4_layers_en.md new file mode 100644 index 00000000000000..a489b4872cc2e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-hel_english_french_4_layers_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hel_english_french_4_layers MarianTransformer from Momo200519 +author: John Snow Labs +name: hel_english_french_4_layers +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hel_english_french_4_layers` is a English model originally trained by Momo200519. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hel_english_french_4_layers_en_5.5.0_3.0_1725346420834.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hel_english_french_4_layers_en_5.5.0_3.0_1725346420834.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("hel_english_french_4_layers","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("hel_english_french_4_layers","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hel_english_french_4_layers| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.1 MB| + +## References + +https://huggingface.co/Momo200519/hel_en_fr_4_layers \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-jmedroberta_base_sentencepiece_vocab50000_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-09-03-jmedroberta_base_sentencepiece_vocab50000_pipeline_ja.md new file mode 100644 index 00000000000000..255bb6c9b9e933 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-jmedroberta_base_sentencepiece_vocab50000_pipeline_ja.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Japanese jmedroberta_base_sentencepiece_vocab50000_pipeline pipeline BertEmbeddings from alabnii +author: John Snow Labs +name: jmedroberta_base_sentencepiece_vocab50000_pipeline +date: 2024-09-03 +tags: [ja, open_source, pipeline, onnx] +task: Embeddings +language: ja +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jmedroberta_base_sentencepiece_vocab50000_pipeline` is a Japanese model originally trained by alabnii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jmedroberta_base_sentencepiece_vocab50000_pipeline_ja_5.5.0_3.0_1725324221952.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jmedroberta_base_sentencepiece_vocab50000_pipeline_ja_5.5.0_3.0_1725324221952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("jmedroberta_base_sentencepiece_vocab50000_pipeline", lang = "ja") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("jmedroberta_base_sentencepiece_vocab50000_pipeline", lang = "ja") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|jmedroberta_base_sentencepiece_vocab50000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ja| +|Size:|464.0 MB| + +## References + +https://huggingface.co/alabnii/jmedroberta-base-sentencepiece-vocab50000 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-lab1_random_minhngca_en.md b/docs/_posts/ahmedlone127/2024-09-03-lab1_random_minhngca_en.md new file mode 100644 index 00000000000000..f61cbb40e3ca50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-lab1_random_minhngca_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English lab1_random_minhngca MarianTransformer from minhngca +author: John Snow Labs +name: lab1_random_minhngca +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_random_minhngca` is a English model originally trained by minhngca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lab1_random_minhngca_en_5.5.0_3.0_1725345499584.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_random_minhngca_en_5.5.0_3.0_1725345499584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("lab1_random_minhngca","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("lab1_random_minhngca","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lab1_random_minhngca| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.2 MB| + +## References + +https://huggingface.co/minhngca/lab1_random \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-lab1_random_minhngca_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-lab1_random_minhngca_pipeline_en.md new file mode 100644 index 00000000000000..29b0525f083e57 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-lab1_random_minhngca_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lab1_random_minhngca_pipeline pipeline MarianTransformer from minhngca +author: John Snow Labs +name: lab1_random_minhngca_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_random_minhngca_pipeline` is a English model originally trained by minhngca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lab1_random_minhngca_pipeline_en_5.5.0_3.0_1725345525437.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_random_minhngca_pipeline_en_5.5.0_3.0_1725345525437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lab1_random_minhngca_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lab1_random_minhngca_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lab1_random_minhngca_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.8 MB| + +## References + +https://huggingface.co/minhngca/lab1_random + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-literaturetyp_recognizer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-literaturetyp_recognizer_pipeline_en.md new file mode 100644 index 00000000000000..ba67485c0a4df8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-literaturetyp_recognizer_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English literaturetyp_recognizer_pipeline pipeline DistilBertForSequenceClassification from LaLaf93 +author: John Snow Labs +name: literaturetyp_recognizer_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`literaturetyp_recognizer_pipeline` is a English model originally trained by LaLaf93. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/literaturetyp_recognizer_pipeline_en_5.5.0_3.0_1725329805819.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/literaturetyp_recognizer_pipeline_en_5.5.0_3.0_1725329805819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("literaturetyp_recognizer_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("literaturetyp_recognizer_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|literaturetyp_recognizer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/LaLaf93/LiteratureTyp_recognizer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-m_e5_base_v2_e_2_t_llama_index_nan.md b/docs/_posts/ahmedlone127/2024-09-03-m_e5_base_v2_e_2_t_llama_index_nan.md new file mode 100644 index 00000000000000..d01fd4186abf61 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-m_e5_base_v2_e_2_t_llama_index_nan.md @@ -0,0 +1,86 @@ +--- +layout: model +title: None m_e5_base_v2_e_2_t_llama_index E5Embeddings from shrijayan +author: John Snow Labs +name: m_e5_base_v2_e_2_t_llama_index +date: 2024-09-03 +tags: [nan, open_source, onnx, embeddings, e5] +task: Embeddings +language: nan +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m_e5_base_v2_e_2_t_llama_index` is a None model originally trained by shrijayan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m_e5_base_v2_e_2_t_llama_index_nan_5.5.0_3.0_1725344799985.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m_e5_base_v2_e_2_t_llama_index_nan_5.5.0_3.0_1725344799985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("m_e5_base_v2_e_2_t_llama_index","nan") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("m_e5_base_v2_e_2_t_llama_index","nan") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|m_e5_base_v2_e_2_t_llama_index| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|nan| +|Size:|385.3 MB| + +## References + +https://huggingface.co/shrijayan/M-e5-base-v2_E-2_T-Llama.Index \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-m_e5_base_v2_e_2_t_llama_index_pipeline_nan.md b/docs/_posts/ahmedlone127/2024-09-03-m_e5_base_v2_e_2_t_llama_index_pipeline_nan.md new file mode 100644 index 00000000000000..9ca2a21c6f54bc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-m_e5_base_v2_e_2_t_llama_index_pipeline_nan.md @@ -0,0 +1,69 @@ +--- +layout: model +title: None m_e5_base_v2_e_2_t_llama_index_pipeline pipeline E5Embeddings from shrijayan +author: John Snow Labs +name: m_e5_base_v2_e_2_t_llama_index_pipeline +date: 2024-09-03 +tags: [nan, open_source, pipeline, onnx] +task: Embeddings +language: nan +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m_e5_base_v2_e_2_t_llama_index_pipeline` is a None model originally trained by shrijayan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m_e5_base_v2_e_2_t_llama_index_pipeline_nan_5.5.0_3.0_1725344827314.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m_e5_base_v2_e_2_t_llama_index_pipeline_nan_5.5.0_3.0_1725344827314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("m_e5_base_v2_e_2_t_llama_index_pipeline", lang = "nan") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("m_e5_base_v2_e_2_t_llama_index_pipeline", lang = "nan") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|m_e5_base_v2_e_2_t_llama_index_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|nan| +|Size:|385.3 MB| + +## References + +https://huggingface.co/shrijayan/M-e5-base-v2_E-2_T-Llama.Index + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_portuguese_breton_en.md b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_portuguese_breton_en.md new file mode 100644 index 00000000000000..87300b0f9148ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_portuguese_breton_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marian_finetuned_kde4_english_tonga_tonga_islands_portuguese_breton MarianTransformer from DarioLopes +author: John Snow Labs +name: marian_finetuned_kde4_english_tonga_tonga_islands_portuguese_breton +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_portuguese_breton` is a English model originally trained by DarioLopes. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_portuguese_breton_en_5.5.0_3.0_1725346004190.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_portuguese_breton_en_5.5.0_3.0_1725346004190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_portuguese_breton","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_portuguese_breton","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_portuguese_breton| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/DarioLopes/marian-finetuned-kde4-en-to-pt_BR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-mariancg_conala_en.md b/docs/_posts/ahmedlone127/2024-09-03-mariancg_conala_en.md new file mode 100644 index 00000000000000..2da4dbe208da80 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-mariancg_conala_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mariancg_conala MarianTransformer from AhmedSSoliman +author: John Snow Labs +name: mariancg_conala +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mariancg_conala` is a English model originally trained by AhmedSSoliman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mariancg_conala_en_5.5.0_3.0_1725347028527.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mariancg_conala_en_5.5.0_3.0_1725347028527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("mariancg_conala","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("mariancg_conala","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mariancg_conala| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|548.4 MB| + +## References + +https://huggingface.co/AhmedSSoliman/MarianCG-CoNaLa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-mariancg_conala_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mariancg_conala_pipeline_en.md new file mode 100644 index 00000000000000..e99f5fe1ad7e3b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-mariancg_conala_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mariancg_conala_pipeline pipeline MarianTransformer from AhmedSSoliman +author: John Snow Labs +name: mariancg_conala_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mariancg_conala_pipeline` is a English model originally trained by AhmedSSoliman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mariancg_conala_pipeline_en_5.5.0_3.0_1725347057412.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mariancg_conala_pipeline_en_5.5.0_3.0_1725347057412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mariancg_conala_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mariancg_conala_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mariancg_conala_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|549.0 MB| + +## References + +https://huggingface.co/AhmedSSoliman/MarianCG-CoNaLa + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-marianmt_tatoeba_enru_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-marianmt_tatoeba_enru_pipeline_en.md new file mode 100644 index 00000000000000..37388dfa3d6a51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-marianmt_tatoeba_enru_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marianmt_tatoeba_enru_pipeline pipeline MarianTransformer from DeepPavlov +author: John Snow Labs +name: marianmt_tatoeba_enru_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt_tatoeba_enru_pipeline` is a English model originally trained by DeepPavlov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_tatoeba_enru_pipeline_en_5.5.0_3.0_1725346564091.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_tatoeba_enru_pipeline_en_5.5.0_3.0_1725346564091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marianmt_tatoeba_enru_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marianmt_tatoeba_enru_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marianmt_tatoeba_enru_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|528.2 MB| + +## References + +https://huggingface.co/DeepPavlov/marianmt-tatoeba-enru + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-math_structure_deberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-math_structure_deberta_pipeline_en.md new file mode 100644 index 00000000000000..c9a60a72b7bf20 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-math_structure_deberta_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English math_structure_deberta_pipeline pipeline DeBertaEmbeddings from ddrg +author: John Snow Labs +name: math_structure_deberta_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`math_structure_deberta_pipeline` is a English model originally trained by ddrg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/math_structure_deberta_pipeline_en_5.5.0_3.0_1725330730175.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/math_structure_deberta_pipeline_en_5.5.0_3.0_1725330730175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("math_structure_deberta_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("math_structure_deberta_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|math_structure_deberta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|690.5 MB| + +## References + +https://huggingface.co/ddrg/math_structure_deberta + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-mi_roberta_base_finetuned_mental_health_en.md b/docs/_posts/ahmedlone127/2024-09-03-mi_roberta_base_finetuned_mental_health_en.md new file mode 100644 index 00000000000000..e684c0210dd96b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-mi_roberta_base_finetuned_mental_health_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mi_roberta_base_finetuned_mental_health RoBertaForSequenceClassification from mavinsao +author: John Snow Labs +name: mi_roberta_base_finetuned_mental_health +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mi_roberta_base_finetuned_mental_health` is a English model originally trained by mavinsao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mi_roberta_base_finetuned_mental_health_en_5.5.0_3.0_1725336729088.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mi_roberta_base_finetuned_mental_health_en_5.5.0_3.0_1725336729088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("mi_roberta_base_finetuned_mental_health","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("mi_roberta_base_finetuned_mental_health", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mi_roberta_base_finetuned_mental_health| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|468.3 MB| + +## References + +https://huggingface.co/mavinsao/mi-roberta-base-finetuned-mental-health \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-mmarco_mminilmv2_l12_h384_v1_nreimers_en.md b/docs/_posts/ahmedlone127/2024-09-03-mmarco_mminilmv2_l12_h384_v1_nreimers_en.md new file mode 100644 index 00000000000000..60169aafb10617 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-mmarco_mminilmv2_l12_h384_v1_nreimers_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mmarco_mminilmv2_l12_h384_v1_nreimers XlmRoBertaForSequenceClassification from nreimers +author: John Snow Labs +name: mmarco_mminilmv2_l12_h384_v1_nreimers +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mmarco_mminilmv2_l12_h384_v1_nreimers` is a English model originally trained by nreimers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mmarco_mminilmv2_l12_h384_v1_nreimers_en_5.5.0_3.0_1725328255356.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mmarco_mminilmv2_l12_h384_v1_nreimers_en_5.5.0_3.0_1725328255356.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("mmarco_mminilmv2_l12_h384_v1_nreimers","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("mmarco_mminilmv2_l12_h384_v1_nreimers", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mmarco_mminilmv2_l12_h384_v1_nreimers| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|399.6 MB| + +## References + +https://huggingface.co/nreimers/mmarco-mMiniLMv2-L12-H384-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-multilingual_e5_base_ling_cls_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-multilingual_e5_base_ling_cls_pipeline_xx.md new file mode 100644 index 00000000000000..9009d683a526ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-multilingual_e5_base_ling_cls_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual multilingual_e5_base_ling_cls_pipeline pipeline XlmRoBertaForSequenceClassification from CeroShrijver +author: John Snow Labs +name: multilingual_e5_base_ling_cls_pipeline +date: 2024-09-03 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_e5_base_ling_cls_pipeline` is a Multilingual model originally trained by CeroShrijver. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_e5_base_ling_cls_pipeline_xx_5.5.0_3.0_1725327537426.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_e5_base_ling_cls_pipeline_xx_5.5.0_3.0_1725327537426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("multilingual_e5_base_ling_cls_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("multilingual_e5_base_ling_cls_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multilingual_e5_base_ling_cls_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|841.9 MB| + +## References + +https://huggingface.co/CeroShrijver/multilingual-e5-base-ling-cls + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-multilingual_e5_base_ling_cls_xx.md b/docs/_posts/ahmedlone127/2024-09-03-multilingual_e5_base_ling_cls_xx.md new file mode 100644 index 00000000000000..ea805f7ff294bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-multilingual_e5_base_ling_cls_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual multilingual_e5_base_ling_cls XlmRoBertaForSequenceClassification from CeroShrijver +author: John Snow Labs +name: multilingual_e5_base_ling_cls +date: 2024-09-03 +tags: [xx, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_e5_base_ling_cls` is a Multilingual model originally trained by CeroShrijver. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_e5_base_ling_cls_xx_5.5.0_3.0_1725327457111.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_e5_base_ling_cls_xx_5.5.0_3.0_1725327457111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("multilingual_e5_base_ling_cls","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("multilingual_e5_base_ling_cls", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multilingual_e5_base_ling_cls| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|841.8 MB| + +## References + +https://huggingface.co/CeroShrijver/multilingual-e5-base-ling-cls \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-multilingual_toxic_xlm_roberta_unitary_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-multilingual_toxic_xlm_roberta_unitary_pipeline_xx.md new file mode 100644 index 00000000000000..42ab0400a14eb3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-multilingual_toxic_xlm_roberta_unitary_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual multilingual_toxic_xlm_roberta_unitary_pipeline pipeline XlmRoBertaForSequenceClassification from unitary +author: John Snow Labs +name: multilingual_toxic_xlm_roberta_unitary_pipeline +date: 2024-09-03 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_toxic_xlm_roberta_unitary_pipeline` is a Multilingual model originally trained by unitary. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_toxic_xlm_roberta_unitary_pipeline_xx_5.5.0_3.0_1725328207606.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_toxic_xlm_roberta_unitary_pipeline_xx_5.5.0_3.0_1725328207606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("multilingual_toxic_xlm_roberta_unitary_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("multilingual_toxic_xlm_roberta_unitary_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multilingual_toxic_xlm_roberta_unitary_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|982.4 MB| + +## References + +https://huggingface.co/unitary/multilingual-toxic-xlm-roberta + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-multilingual_toxic_xlm_roberta_unitary_xx.md b/docs/_posts/ahmedlone127/2024-09-03-multilingual_toxic_xlm_roberta_unitary_xx.md new file mode 100644 index 00000000000000..b264635efd7ebc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-multilingual_toxic_xlm_roberta_unitary_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual multilingual_toxic_xlm_roberta_unitary XlmRoBertaForSequenceClassification from unitary +author: John Snow Labs +name: multilingual_toxic_xlm_roberta_unitary +date: 2024-09-03 +tags: [xx, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_toxic_xlm_roberta_unitary` is a Multilingual model originally trained by unitary. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_toxic_xlm_roberta_unitary_xx_5.5.0_3.0_1725328158570.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_toxic_xlm_roberta_unitary_xx_5.5.0_3.0_1725328158570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("multilingual_toxic_xlm_roberta_unitary","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("multilingual_toxic_xlm_roberta_unitary", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multilingual_toxic_xlm_roberta_unitary| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|982.4 MB| + +## References + +https://huggingface.co/unitary/multilingual-toxic-xlm-roberta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-n_roberta_twitterfin_padding60model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-n_roberta_twitterfin_padding60model_pipeline_en.md new file mode 100644 index 00000000000000..fe7fd5f0d595bc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-n_roberta_twitterfin_padding60model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English n_roberta_twitterfin_padding60model_pipeline pipeline RoBertaForSequenceClassification from Realgon +author: John Snow Labs +name: n_roberta_twitterfin_padding60model_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_roberta_twitterfin_padding60model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_roberta_twitterfin_padding60model_pipeline_en_5.5.0_3.0_1725337047293.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_roberta_twitterfin_padding60model_pipeline_en_5.5.0_3.0_1725337047293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("n_roberta_twitterfin_padding60model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("n_roberta_twitterfin_padding60model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_roberta_twitterfin_padding60model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|443.2 MB| + +## References + +https://huggingface.co/Realgon/N_roberta_twitterfin_padding60model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-newsentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-newsentiment_analysis_pipeline_en.md new file mode 100644 index 00000000000000..8e54714dbd2a64 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-newsentiment_analysis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English newsentiment_analysis_pipeline pipeline DistilBertForSequenceClassification from 1gen23dec +author: John Snow Labs +name: newsentiment_analysis_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`newsentiment_analysis_pipeline` is a English model originally trained by 1gen23dec. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/newsentiment_analysis_pipeline_en_5.5.0_3.0_1725329770536.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/newsentiment_analysis_pipeline_en_5.5.0_3.0_1725329770536.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("newsentiment_analysis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("newsentiment_analysis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|newsentiment_analysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/1gen23dec/newsentiment_analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-nlpcw_ner_en.md b/docs/_posts/ahmedlone127/2024-09-03-nlpcw_ner_en.md new file mode 100644 index 00000000000000..27c6ee7f70e22c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-nlpcw_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nlpcw_ner RoBertaForTokenClassification from cogniveon +author: John Snow Labs +name: nlpcw_ner +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlpcw_ner` is a English model originally trained by cogniveon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlpcw_ner_en_5.5.0_3.0_1725326002882.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlpcw_ner_en_5.5.0_3.0_1725326002882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = RoBertaForTokenClassification.pretrained("nlpcw_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("nlpcw_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nlpcw_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/cogniveon/nlpcw-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-odabert_en.md b/docs/_posts/ahmedlone127/2024-09-03-odabert_en.md new file mode 100644 index 00000000000000..71f88d19d97ceb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-odabert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English odabert BertEmbeddings from alex-miller +author: John Snow Labs +name: odabert +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`odabert` is a English model originally trained by alex-miller. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/odabert_en_5.5.0_3.0_1725323817283.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/odabert_en_5.5.0_3.0_1725323817283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = BertEmbeddings.pretrained("odabert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("odabert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|odabert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|en| +|Size:|628.7 MB| + +## References + +https://huggingface.co/alex-miller/ODABert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-odabert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-odabert_pipeline_en.md new file mode 100644 index 00000000000000..feabec9cf19c14 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-odabert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English odabert_pipeline pipeline BertEmbeddings from alex-miller +author: John Snow Labs +name: odabert_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`odabert_pipeline` is a English model originally trained by alex-miller. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/odabert_pipeline_en_5.5.0_3.0_1725323857554.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/odabert_pipeline_en_5.5.0_3.0_1725323857554.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("odabert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("odabert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|odabert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|628.7 MB| + +## References + +https://huggingface.co/alex-miller/ODABert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_bkm_10e4encdec_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_bkm_10e4encdec_en.md new file mode 100644 index 00000000000000..261bb2b6c27285 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_bkm_10e4encdec_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_english_bkm_10e4encdec MarianTransformer from kalese +author: John Snow Labs +name: opus_maltese_english_bkm_10e4encdec +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_bkm_10e4encdec` is a English model originally trained by kalese. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_10e4encdec_en_5.5.0_3.0_1725347000887.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_10e4encdec_en_5.5.0_3.0_1725347000887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_english_bkm_10e4encdec","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_english_bkm_10e4encdec","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_bkm_10e4encdec| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.2 MB| + +## References + +https://huggingface.co/kalese/opus-mt-en-bkm-10e4encdec \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_bkm_10e4encdec_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_bkm_10e4encdec_pipeline_en.md new file mode 100644 index 00000000000000..b4a2dcb7a93cdf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_bkm_10e4encdec_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_english_bkm_10e4encdec_pipeline pipeline MarianTransformer from kalese +author: John Snow Labs +name: opus_maltese_english_bkm_10e4encdec_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_bkm_10e4encdec_pipeline` is a English model originally trained by kalese. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_10e4encdec_pipeline_en_5.5.0_3.0_1725347026433.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_10e4encdec_pipeline_en_5.5.0_3.0_1725347026433.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_english_bkm_10e4encdec_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_english_bkm_10e4encdec_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_bkm_10e4encdec_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|508.7 MB| + +## References + +https://huggingface.co/kalese/opus-mt-en-bkm-10e4encdec + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_dutch_finetuned__marian_theirs_train_val_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_dutch_finetuned__marian_theirs_train_val_en.md new file mode 100644 index 00000000000000..7b142064b457b0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_dutch_finetuned__marian_theirs_train_val_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_english_dutch_finetuned__marian_theirs_train_val MarianTransformer from kalcho100 +author: John Snow Labs +name: opus_maltese_english_dutch_finetuned__marian_theirs_train_val +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_dutch_finetuned__marian_theirs_train_val` is a English model originally trained by kalcho100. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_dutch_finetuned__marian_theirs_train_val_en_5.5.0_3.0_1725346512318.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_dutch_finetuned__marian_theirs_train_val_en_5.5.0_3.0_1725346512318.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_english_dutch_finetuned__marian_theirs_train_val","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_english_dutch_finetuned__marian_theirs_train_val","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_dutch_finetuned__marian_theirs_train_val| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|548.8 MB| + +## References + +https://huggingface.co/kalcho100/opus-mt-en-nl-finetuned__marian_theirs_train_val \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_dutch_finetuned__marian_theirs_train_val_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_dutch_finetuned__marian_theirs_train_val_pipeline_en.md new file mode 100644 index 00000000000000..23c4211562b610 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_dutch_finetuned__marian_theirs_train_val_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_english_dutch_finetuned__marian_theirs_train_val_pipeline pipeline MarianTransformer from kalcho100 +author: John Snow Labs +name: opus_maltese_english_dutch_finetuned__marian_theirs_train_val_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_dutch_finetuned__marian_theirs_train_val_pipeline` is a English model originally trained by kalcho100. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_dutch_finetuned__marian_theirs_train_val_pipeline_en_5.5.0_3.0_1725346539790.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_dutch_finetuned__marian_theirs_train_val_pipeline_en_5.5.0_3.0_1725346539790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_english_dutch_finetuned__marian_theirs_train_val_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_english_dutch_finetuned__marian_theirs_train_val_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_dutch_finetuned__marian_theirs_train_val_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|549.3 MB| + +## References + +https://huggingface.co/kalcho100/opus-mt-en-nl-finetuned__marian_theirs_train_val + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_en.md new file mode 100644 index 00000000000000..b885f0e7d5bbfc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona MarianTransformer from VFiona +author: John Snow Labs +name: opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona` is a English model originally trained by VFiona. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_en_5.5.0_3.0_1725347224706.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_en_5.5.0_3.0_1725347224706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|622.9 MB| + +## References + +https://huggingface.co/VFiona/opus-mt-en-it-finetuned-en-to-it \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_en.md new file mode 100644 index 00000000000000..1721fcb2577ee0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne MarianTransformer from Dwayne +author: John Snow Labs +name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne` is a English model originally trained by Dwayne. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_en_5.5.0_3.0_1725347224538.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_en_5.5.0_3.0_1725347224538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.6 MB| + +## References + +https://huggingface.co/Dwayne/opus-mt-en-ro-finetuned-en-to-ro \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_en.md new file mode 100644 index 00000000000000..598c07d6a2ae3c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic MarianTransformer from Culmenus +author: John Snow Labs +name: opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic` is a English model originally trained by Culmenus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_en_5.5.0_3.0_1725346362576.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_en_5.5.0_3.0_1725346362576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|508.6 MB| + +## References + +https://huggingface.co/Culmenus/opus-mt-de-is-finetuned-de-to-is \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en.md new file mode 100644 index 00000000000000..8490545e130c42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from PontifexMaximus +author: John Snow Labs +name: opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline` is a English model originally trained by PontifexMaximus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725347093704.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725347093704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|521.3 MB| + +## References + +https://huggingface.co/PontifexMaximus/opus-mt-ur-en-finetuned-fa-to-en + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-phayathaibert_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-03-phayathaibert_sentiment_analysis_en.md new file mode 100644 index 00000000000000..11aa2e4884100c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-phayathaibert_sentiment_analysis_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English phayathaibert_sentiment_analysis CamemBertForSequenceClassification from SuratanBoonpong +author: John Snow Labs +name: phayathaibert_sentiment_analysis +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phayathaibert_sentiment_analysis` is a English model originally trained by SuratanBoonpong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phayathaibert_sentiment_analysis_en_5.5.0_3.0_1725325182550.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phayathaibert_sentiment_analysis_en_5.5.0_3.0_1725325182550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("phayathaibert_sentiment_analysis","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("phayathaibert_sentiment_analysis", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phayathaibert_sentiment_analysis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/SuratanBoonpong/Phayathaibert_sentiment_analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-phayathaibert_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-phayathaibert_sentiment_analysis_pipeline_en.md new file mode 100644 index 00000000000000..7ef4345ffede0b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-phayathaibert_sentiment_analysis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English phayathaibert_sentiment_analysis_pipeline pipeline CamemBertForSequenceClassification from SuratanBoonpong +author: John Snow Labs +name: phayathaibert_sentiment_analysis_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phayathaibert_sentiment_analysis_pipeline` is a English model originally trained by SuratanBoonpong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phayathaibert_sentiment_analysis_pipeline_en_5.5.0_3.0_1725325232670.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phayathaibert_sentiment_analysis_pipeline_en_5.5.0_3.0_1725325232670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("phayathaibert_sentiment_analysis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("phayathaibert_sentiment_analysis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phayathaibert_sentiment_analysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/SuratanBoonpong/Phayathaibert_sentiment_analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_fine_tuned_flipkart_reviews_amharic_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_fine_tuned_flipkart_reviews_amharic_en.md new file mode 100644 index 00000000000000..4cad0b7e406709 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_fine_tuned_flipkart_reviews_amharic_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_fine_tuned_flipkart_reviews_amharic XlmRoBertaForSequenceClassification from akshatmehta98 +author: John Snow Labs +name: roberta_base_fine_tuned_flipkart_reviews_amharic +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_fine_tuned_flipkart_reviews_amharic` is a English model originally trained by akshatmehta98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_fine_tuned_flipkart_reviews_amharic_en_5.5.0_3.0_1725327423932.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_fine_tuned_flipkart_reviews_amharic_en_5.5.0_3.0_1725327423932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("roberta_base_fine_tuned_flipkart_reviews_amharic","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("roberta_base_fine_tuned_flipkart_reviews_amharic", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_fine_tuned_flipkart_reviews_amharic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/akshatmehta98/roberta-base-fine-tuned-flipkart-reviews-am \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_offensive_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_offensive_en.md new file mode 100644 index 00000000000000..2bb723fe863127 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_offensive_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_offensive RoBertaForSequenceClassification from cardiffnlp +author: John Snow Labs +name: roberta_base_offensive +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_offensive` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_offensive_en_5.5.0_3.0_1725336993064.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_offensive_en_5.5.0_3.0_1725336993064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_offensive","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_offensive", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_offensive| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|442.0 MB| + +## References + +https://huggingface.co/cardiffnlp/roberta-base-offensive \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_offensive_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_offensive_pipeline_en.md new file mode 100644 index 00000000000000..d978921be91b83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_offensive_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_offensive_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp +author: John Snow Labs +name: roberta_base_offensive_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_offensive_pipeline` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_offensive_pipeline_en_5.5.0_3.0_1725337029401.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_offensive_pipeline_en_5.5.0_3.0_1725337029401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_offensive_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_offensive_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_offensive_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|442.1 MB| + +## References + +https://huggingface.co/cardiffnlp/roberta-base-offensive + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_sentiment_cardiffnlp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_sentiment_cardiffnlp_pipeline_en.md new file mode 100644 index 00000000000000..e4ab3223d92678 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_sentiment_cardiffnlp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_sentiment_cardiffnlp_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp +author: John Snow Labs +name: roberta_base_sentiment_cardiffnlp_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_sentiment_cardiffnlp_pipeline` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_sentiment_cardiffnlp_pipeline_en_5.5.0_3.0_1725337394067.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_sentiment_cardiffnlp_pipeline_en_5.5.0_3.0_1725337394067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_sentiment_cardiffnlp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_sentiment_cardiffnlp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_sentiment_cardiffnlp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|455.1 MB| + +## References + +https://huggingface.co/cardiffnlp/roberta-base-sentiment + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_word_chinese_cluecorpussmall_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_word_chinese_cluecorpussmall_pipeline_zh.md new file mode 100644 index 00000000000000..a3eb26e275a9e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_word_chinese_cluecorpussmall_pipeline_zh.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Chinese roberta_base_word_chinese_cluecorpussmall_pipeline pipeline BertEmbeddings from uer +author: John Snow Labs +name: roberta_base_word_chinese_cluecorpussmall_pipeline +date: 2024-09-03 +tags: [zh, open_source, pipeline, onnx] +task: Embeddings +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_word_chinese_cluecorpussmall_pipeline` is a Chinese model originally trained by uer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_word_chinese_cluecorpussmall_pipeline_zh_5.5.0_3.0_1725323854068.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_word_chinese_cluecorpussmall_pipeline_zh_5.5.0_3.0_1725323854068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_word_chinese_cluecorpussmall_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_word_chinese_cluecorpussmall_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_word_chinese_cluecorpussmall_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|607.3 MB| + +## References + +https://huggingface.co/uer/roberta-base-word-chinese-cluecorpussmall + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_word_chinese_cluecorpussmall_zh.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_word_chinese_cluecorpussmall_zh.md new file mode 100644 index 00000000000000..eb34aa0b96abd4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_word_chinese_cluecorpussmall_zh.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Chinese roberta_base_word_chinese_cluecorpussmall BertEmbeddings from uer +author: John Snow Labs +name: roberta_base_word_chinese_cluecorpussmall +date: 2024-09-03 +tags: [zh, open_source, onnx, embeddings, bert] +task: Embeddings +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_word_chinese_cluecorpussmall` is a Chinese model originally trained by uer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_word_chinese_cluecorpussmall_zh_5.5.0_3.0_1725323818975.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_word_chinese_cluecorpussmall_zh_5.5.0_3.0_1725323818975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = BertEmbeddings.pretrained("roberta_base_word_chinese_cluecorpussmall","zh") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("roberta_base_word_chinese_cluecorpussmall","zh") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_word_chinese_cluecorpussmall| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|zh| +|Size:|607.3 MB| + +## References + +https://huggingface.co/uer/roberta-base-word-chinese-cluecorpussmall \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_autonlp_persian_farsi_473312409_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_autonlp_persian_farsi_473312409_en.md new file mode 100644 index 00000000000000..2432a34b5168f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_autonlp_persian_farsi_473312409_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_classifier_autonlp_persian_farsi_473312409 RoBertaForSequenceClassification from Anamika +author: John Snow Labs +name: roberta_classifier_autonlp_persian_farsi_473312409 +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classifier_autonlp_persian_farsi_473312409` is a English model originally trained by Anamika. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_autonlp_persian_farsi_473312409_en_5.5.0_3.0_1725336898843.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_autonlp_persian_farsi_473312409_en_5.5.0_3.0_1725336898843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_autonlp_persian_farsi_473312409","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_autonlp_persian_farsi_473312409", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_autonlp_persian_farsi_473312409| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|308.7 MB| + +## References + +https://huggingface.co/Anamika/autonlp-fa-473312409 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_large_wanli_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_large_wanli_en.md new file mode 100644 index 00000000000000..4761e2f242e143 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_large_wanli_en.md @@ -0,0 +1,105 @@ +--- +layout: model +title: English RoBertaForSequenceClassification Large Cased model (from alisawuffles) +author: John Snow Labs +name: roberta_classifier_large_wanli +date: 2024-09-03 +tags: [en, open_source, roberta, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-large-wanli` is a English model originally trained by `alisawuffles`. + +## Predicted Entities + +`neutral`, `entailment`, `contradiction` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_large_wanli_en_5.5.0_3.0_1725337224485.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_large_wanli_en_5.5.0_3.0_1725337224485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_large_wanli","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_large_wanli","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.roberta.large.by_alisawuffles").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_classifier_large_wanli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +References + +- https://huggingface.co/alisawuffles/roberta-large-wanli +- https://arxiv.org/abs/2201.05955 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_ehealth_kd_es.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_ehealth_kd_es.md new file mode 100644 index 00000000000000..a5b89acc058d5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_ehealth_kd_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish roberta_large_bne_ehealth_kd RoBertaForTokenClassification from IIC +author: John Snow Labs +name: roberta_large_bne_ehealth_kd +date: 2024-09-03 +tags: [es, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_bne_ehealth_kd` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_bne_ehealth_kd_es_5.5.0_3.0_1725326466226.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_bne_ehealth_kd_es_5.5.0_3.0_1725326466226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_bne_ehealth_kd","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_bne_ehealth_kd", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_bne_ehealth_kd| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|1.3 GB| + +## References + +https://huggingface.co/IIC/roberta-large-bne-ehealth_kd \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_ehealth_kd_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_ehealth_kd_pipeline_es.md new file mode 100644 index 00000000000000..32abde8066f01f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_ehealth_kd_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish roberta_large_bne_ehealth_kd_pipeline pipeline RoBertaForTokenClassification from IIC +author: John Snow Labs +name: roberta_large_bne_ehealth_kd_pipeline +date: 2024-09-03 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_bne_ehealth_kd_pipeline` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_bne_ehealth_kd_pipeline_es_5.5.0_3.0_1725326558077.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_bne_ehealth_kd_pipeline_es_5.5.0_3.0_1725326558077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_bne_ehealth_kd_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_bne_ehealth_kd_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_bne_ehealth_kd_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|1.3 GB| + +## References + +https://huggingface.co/IIC/roberta-large-bne-ehealth_kd + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_nubes_es.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_nubes_es.md new file mode 100644 index 00000000000000..38b1bcf31d4ee5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_nubes_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish roberta_large_bne_nubes RoBertaForTokenClassification from IIC +author: John Snow Labs +name: roberta_large_bne_nubes +date: 2024-09-03 +tags: [es, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_bne_nubes` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_bne_nubes_es_5.5.0_3.0_1725326673785.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_bne_nubes_es_5.5.0_3.0_1725326673785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_bne_nubes","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_bne_nubes", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_bne_nubes| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|1.3 GB| + +## References + +https://huggingface.co/IIC/roberta-large-bne-nubes \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_nubes_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_nubes_pipeline_es.md new file mode 100644 index 00000000000000..e0a2073a3c7c00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_nubes_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish roberta_large_bne_nubes_pipeline pipeline RoBertaForTokenClassification from IIC +author: John Snow Labs +name: roberta_large_bne_nubes_pipeline +date: 2024-09-03 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_bne_nubes_pipeline` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_bne_nubes_pipeline_es_5.5.0_3.0_1725326753068.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_bne_nubes_pipeline_es_5.5.0_3.0_1725326753068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_bne_nubes_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_bne_nubes_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_bne_nubes_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|1.3 GB| + +## References + +https://huggingface.co/IIC/roberta-large-bne-nubes + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_small_pun_detector_v2_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_small_pun_detector_v2_en.md new file mode 100644 index 00000000000000..97ab9250c67d89 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_small_pun_detector_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_small_pun_detector_v2 RoBertaForSequenceClassification from frostymelonade +author: John Snow Labs +name: roberta_small_pun_detector_v2 +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_small_pun_detector_v2` is a English model originally trained by frostymelonade. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_small_pun_detector_v2_en_5.5.0_3.0_1725336534859.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_small_pun_detector_v2_en_5.5.0_3.0_1725336534859.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_small_pun_detector_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_small_pun_detector_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_small_pun_detector_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|85.0 MB| + +## References + +https://huggingface.co/frostymelonade/roberta-small-pun-detector-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_small_pun_detector_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_small_pun_detector_v2_pipeline_en.md new file mode 100644 index 00000000000000..312b70c10e5efc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_small_pun_detector_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_small_pun_detector_v2_pipeline pipeline RoBertaForSequenceClassification from frostymelonade +author: John Snow Labs +name: roberta_small_pun_detector_v2_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_small_pun_detector_v2_pipeline` is a English model originally trained by frostymelonade. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_small_pun_detector_v2_pipeline_en_5.5.0_3.0_1725336539337.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_small_pun_detector_v2_pipeline_en_5.5.0_3.0_1725336539337.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_small_pun_detector_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_small_pun_detector_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_small_pun_detector_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|85.0 MB| + +## References + +https://huggingface.co/frostymelonade/roberta-small-pun-detector-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_checkpoint_23200_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_checkpoint_23200_en.md new file mode 100644 index 00000000000000..dbae2ce8afa85d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_checkpoint_23200_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_checkpoint_23200 XlmRoBertaSentenceEmbeddings from yemen2016 +author: John Snow Labs +name: sent_checkpoint_23200 +date: 2024-09-03 +tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_checkpoint_23200` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_checkpoint_23200_en_5.5.0_3.0_1725333842004.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_checkpoint_23200_en_5.5.0_3.0_1725333842004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_checkpoint_23200","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_checkpoint_23200","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_checkpoint_23200| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/checkpoint-23200 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_checkpoint_23200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_checkpoint_23200_pipeline_en.md new file mode 100644 index 00000000000000..c18ef8ae2d3771 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_checkpoint_23200_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_checkpoint_23200_pipeline pipeline XlmRoBertaSentenceEmbeddings from yemen2016 +author: John Snow Labs +name: sent_checkpoint_23200_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_checkpoint_23200_pipeline` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_checkpoint_23200_pipeline_en_5.5.0_3.0_1725333894089.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_checkpoint_23200_pipeline_en_5.5.0_3.0_1725333894089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_checkpoint_23200_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_checkpoint_23200_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_checkpoint_23200_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/checkpoint-23200 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- XlmRoBertaSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_entitycs_39_pep_malay_xlmr_base_xx.md b/docs/_posts/ahmedlone127/2024-09-03-sent_entitycs_39_pep_malay_xlmr_base_xx.md new file mode 100644 index 00000000000000..e3bd5826315db3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_entitycs_39_pep_malay_xlmr_base_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual sent_entitycs_39_pep_malay_xlmr_base XlmRoBertaSentenceEmbeddings from huawei-noah +author: John Snow Labs +name: sent_entitycs_39_pep_malay_xlmr_base +date: 2024-09-03 +tags: [xx, open_source, onnx, sentence_embeddings, xlm_roberta] +task: Embeddings +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_entitycs_39_pep_malay_xlmr_base` is a Multilingual model originally trained by huawei-noah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_entitycs_39_pep_malay_xlmr_base_xx_5.5.0_3.0_1725334514321.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_entitycs_39_pep_malay_xlmr_base_xx_5.5.0_3.0_1725334514321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_entitycs_39_pep_malay_xlmr_base","xx") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_entitycs_39_pep_malay_xlmr_base","xx") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_entitycs_39_pep_malay_xlmr_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|944.6 MB| + +## References + +https://huggingface.co/huawei-noah/EntityCS-39-PEP_MS-xlmr-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_glot500_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_glot500_base_en.md new file mode 100644 index 00000000000000..0c4ec2780165b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_glot500_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_glot500_base XlmRoBertaSentenceEmbeddings from cis-lmu +author: John Snow Labs +name: sent_glot500_base +date: 2024-09-03 +tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_glot500_base` is a English model originally trained by cis-lmu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_glot500_base_en_5.5.0_3.0_1725333964440.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_glot500_base_en_5.5.0_3.0_1725333964440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_glot500_base","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_glot500_base","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_glot500_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/cis-lmu/glot500-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_less_300000_xlm_roberta_mmar_recipe_10_128_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_less_300000_xlm_roberta_mmar_recipe_10_128_en.md new file mode 100644 index 00000000000000..31be7c4e1f172b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_less_300000_xlm_roberta_mmar_recipe_10_128_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_less_300000_xlm_roberta_mmar_recipe_10_128 XlmRoBertaSentenceEmbeddings from CennetOguz +author: John Snow Labs +name: sent_less_300000_xlm_roberta_mmar_recipe_10_128 +date: 2024-09-03 +tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_less_300000_xlm_roberta_mmar_recipe_10_128` is a English model originally trained by CennetOguz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_less_300000_xlm_roberta_mmar_recipe_10_128_en_5.5.0_3.0_1725333550061.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_less_300000_xlm_roberta_mmar_recipe_10_128_en_5.5.0_3.0_1725333550061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_less_300000_xlm_roberta_mmar_recipe_10_128","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_less_300000_xlm_roberta_mmar_recipe_10_128","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_less_300000_xlm_roberta_mmar_recipe_10_128| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/CennetOguz/less_300000_xlm_roberta_mmar_recipe_10_128 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_less_300000_xlm_roberta_mmar_recipe_10_128_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_less_300000_xlm_roberta_mmar_recipe_10_128_pipeline_en.md new file mode 100644 index 00000000000000..31da4791994540 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_less_300000_xlm_roberta_mmar_recipe_10_128_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_less_300000_xlm_roberta_mmar_recipe_10_128_pipeline pipeline XlmRoBertaSentenceEmbeddings from CennetOguz +author: John Snow Labs +name: sent_less_300000_xlm_roberta_mmar_recipe_10_128_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_less_300000_xlm_roberta_mmar_recipe_10_128_pipeline` is a English model originally trained by CennetOguz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_less_300000_xlm_roberta_mmar_recipe_10_128_pipeline_en_5.5.0_3.0_1725333603647.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_less_300000_xlm_roberta_mmar_recipe_10_128_pipeline_en_5.5.0_3.0_1725333603647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_less_300000_xlm_roberta_mmar_recipe_10_128_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_less_300000_xlm_roberta_mmar_recipe_10_128_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_less_300000_xlm_roberta_mmar_recipe_10_128_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/CennetOguz/less_300000_xlm_roberta_mmar_recipe_10_128 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- XlmRoBertaSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_memo_model_4200_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_memo_model_4200_en.md new file mode 100644 index 00000000000000..900b8894301eb0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_memo_model_4200_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_memo_model_4200 XlmRoBertaSentenceEmbeddings from yemen2016 +author: John Snow Labs +name: sent_memo_model_4200 +date: 2024-09-03 +tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_memo_model_4200` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_memo_model_4200_en_5.5.0_3.0_1725334094327.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_memo_model_4200_en_5.5.0_3.0_1725334094327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_memo_model_4200","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_memo_model_4200","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_memo_model_4200| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/memo_model_4200 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_memo_model_4200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_memo_model_4200_pipeline_en.md new file mode 100644 index 00000000000000..97dc3e99037704 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_memo_model_4200_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_memo_model_4200_pipeline pipeline XlmRoBertaSentenceEmbeddings from yemen2016 +author: John Snow Labs +name: sent_memo_model_4200_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_memo_model_4200_pipeline` is a English model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_memo_model_4200_pipeline_en_5.5.0_3.0_1725334145593.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_memo_model_4200_pipeline_en_5.5.0_3.0_1725334145593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_memo_model_4200_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_memo_model_4200_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_memo_model_4200_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/yemen2016/memo_model_4200 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- XlmRoBertaSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_en.md new file mode 100644 index 00000000000000..7dffbf4e66710a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4 XlmRoBertaSentenceEmbeddings from NbAiLab +author: John Snow Labs +name: sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4 +date: 2024-09-03 +tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4` is a English model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_en_5.5.0_3.0_1725333691360.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_en_5.5.0_3.0_1725333691360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/NbAiLab/nb-roberta-base-ncc-plus-scandi-1e4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_ofa_multi_200_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_ofa_multi_200_en.md new file mode 100644 index 00000000000000..b8c1dd0b489668 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_ofa_multi_200_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_ofa_multi_200 XlmRoBertaSentenceEmbeddings from yihongLiu +author: John Snow Labs +name: sent_ofa_multi_200 +date: 2024-09-03 +tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_ofa_multi_200` is a English model originally trained by yihongLiu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_ofa_multi_200_en_5.5.0_3.0_1725334346556.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_ofa_multi_200_en_5.5.0_3.0_1725334346556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_ofa_multi_200","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_ofa_multi_200","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_ofa_multi_200| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/yihongLiu/ofa-multi-200 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_dutch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_dutch_pipeline_en.md new file mode 100644 index 00000000000000..28e03c364dbe23 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_dutch_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_xlm_roberta_base_finetuned_on_runaways_dutch_pipeline pipeline XlmRoBertaSentenceEmbeddings from Nadav +author: John Snow Labs +name: sent_xlm_roberta_base_finetuned_on_runaways_dutch_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_on_runaways_dutch_pipeline` is a English model originally trained by Nadav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_on_runaways_dutch_pipeline_en_5.5.0_3.0_1725334120734.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_on_runaways_dutch_pipeline_en_5.5.0_3.0_1725334120734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_on_runaways_dutch_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_on_runaways_dutch_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_xlm_roberta_base_finetuned_on_runaways_dutch_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/Nadav/xlm-roberta-base-finetuned-on-runaways-nl + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- XlmRoBertaSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_french_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_french_pipeline_en.md new file mode 100644 index 00000000000000..14ce46e2791a1a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_french_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_xlm_roberta_base_finetuned_on_runaways_french_pipeline pipeline XlmRoBertaSentenceEmbeddings from Nadav +author: John Snow Labs +name: sent_xlm_roberta_base_finetuned_on_runaways_french_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_on_runaways_french_pipeline` is a English model originally trained by Nadav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_on_runaways_french_pipeline_en_5.5.0_3.0_1725334415140.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_on_runaways_french_pipeline_en_5.5.0_3.0_1725334415140.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_on_runaways_french_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_on_runaways_french_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_xlm_roberta_base_finetuned_on_runaways_french_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/Nadav/xlm-roberta-base-finetuned-on-runaways-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- XlmRoBertaSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_indonesian_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_indonesian_en.md new file mode 100644 index 00000000000000..be10b87f65bcd1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_indonesian_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_xlm_roberta_base_indonesian XlmRoBertaSentenceEmbeddings from harish +author: John Snow Labs +name: sent_xlm_roberta_base_indonesian +date: 2024-09-03 +tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_indonesian` is a English model originally trained by harish. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_indonesian_en_5.5.0_3.0_1725333831269.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_indonesian_en_5.5.0_3.0_1725333831269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_indonesian","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_indonesian","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_xlm_roberta_base_indonesian| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|653.1 MB| + +## References + +https://huggingface.co/harish/xlm-roberta-base-ID \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_indonesian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_indonesian_pipeline_en.md new file mode 100644 index 00000000000000..db476e01420bcf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_indonesian_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_xlm_roberta_base_indonesian_pipeline pipeline XlmRoBertaSentenceEmbeddings from harish +author: John Snow Labs +name: sent_xlm_roberta_base_indonesian_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_indonesian_pipeline` is a English model originally trained by harish. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_indonesian_pipeline_en_5.5.0_3.0_1725334022975.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_indonesian_pipeline_en_5.5.0_3.0_1725334022975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_xlm_roberta_base_indonesian_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_indonesian_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_xlm_roberta_base_indonesian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|653.6 MB| + +## References + +https://huggingface.co/harish/xlm-roberta-base-ID + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- XlmRoBertaSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_app_review_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_app_review_en.md new file mode 100644 index 00000000000000..186d047550a855 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_app_review_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sentiment_analysis_app_review DistilBertForSequenceClassification from sivaranjanisundarraj +author: John Snow Labs +name: sentiment_analysis_app_review +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_app_review` is a English model originally trained by sivaranjanisundarraj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_app_review_en_5.5.0_3.0_1725329642507.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_app_review_en_5.5.0_3.0_1725329642507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("sentiment_analysis_app_review","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sentiment_analysis_app_review", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment_analysis_app_review| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/sivaranjanisundarraj/sentiment-analysis-app-review \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_finnlp_thai_nlp_chula_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_finnlp_thai_nlp_chula_en.md new file mode 100644 index 00000000000000..9c2f70633435ba --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_finnlp_thai_nlp_chula_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sentiment_finnlp_thai_nlp_chula CamemBertForSequenceClassification from nlp-chula +author: John Snow Labs +name: sentiment_finnlp_thai_nlp_chula +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_finnlp_thai_nlp_chula` is a English model originally trained by nlp-chula. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_finnlp_thai_nlp_chula_en_5.5.0_3.0_1725324872977.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_finnlp_thai_nlp_chula_en_5.5.0_3.0_1725324872977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("sentiment_finnlp_thai_nlp_chula","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("sentiment_finnlp_thai_nlp_chula", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment_finnlp_thai_nlp_chula| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|394.3 MB| + +## References + +https://huggingface.co/nlp-chula/sentiment-finnlp-th \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_finnlp_thai_nlp_chula_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_finnlp_thai_nlp_chula_pipeline_en.md new file mode 100644 index 00000000000000..c730a424514277 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_finnlp_thai_nlp_chula_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sentiment_finnlp_thai_nlp_chula_pipeline pipeline CamemBertForSequenceClassification from nlp-chula +author: John Snow Labs +name: sentiment_finnlp_thai_nlp_chula_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_finnlp_thai_nlp_chula_pipeline` is a English model originally trained by nlp-chula. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_finnlp_thai_nlp_chula_pipeline_en_5.5.0_3.0_1725324892016.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_finnlp_thai_nlp_chula_pipeline_en_5.5.0_3.0_1725324892016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentiment_finnlp_thai_nlp_chula_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentiment_finnlp_thai_nlp_chula_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment_finnlp_thai_nlp_chula_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|394.4 MB| + +## References + +https://huggingface.co/nlp-chula/sentiment-finnlp-th + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-shanghainese_opus_chinese_serbocroatian_4000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-shanghainese_opus_chinese_serbocroatian_4000_pipeline_en.md new file mode 100644 index 00000000000000..5c6763f2e99626 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-shanghainese_opus_chinese_serbocroatian_4000_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English shanghainese_opus_chinese_serbocroatian_4000_pipeline pipeline MarianTransformer from spycsh +author: John Snow Labs +name: shanghainese_opus_chinese_serbocroatian_4000_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`shanghainese_opus_chinese_serbocroatian_4000_pipeline` is a English model originally trained by spycsh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/shanghainese_opus_chinese_serbocroatian_4000_pipeline_en_5.5.0_3.0_1725346636527.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/shanghainese_opus_chinese_serbocroatian_4000_pipeline_en_5.5.0_3.0_1725346636527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("shanghainese_opus_chinese_serbocroatian_4000_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("shanghainese_opus_chinese_serbocroatian_4000_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|shanghainese_opus_chinese_serbocroatian_4000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|540.6 MB| + +## References + +https://huggingface.co/spycsh/shanghainese-opus-zh-sh-4000 + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-soqbert_en.md b/docs/_posts/ahmedlone127/2024-09-03-soqbert_en.md new file mode 100644 index 00000000000000..0b88196ef8d1ba --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-soqbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English soqbert DistilBertForSequenceClassification from ilert +author: John Snow Labs +name: soqbert +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`soqbert` is a English model originally trained by ilert. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/soqbert_en_5.5.0_3.0_1725329881743.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/soqbert_en_5.5.0_3.0_1725329881743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("soqbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("soqbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|soqbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/ilert/SoQbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-spanish_finnish_all_en.md b/docs/_posts/ahmedlone127/2024-09-03-spanish_finnish_all_en.md new file mode 100644 index 00000000000000..a45331580a7615 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-spanish_finnish_all_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English spanish_finnish_all MarianTransformer from americasnlp-lct-ehu +author: John Snow Labs +name: spanish_finnish_all +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanish_finnish_all` is a English model originally trained by americasnlp-lct-ehu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanish_finnish_all_en_5.5.0_3.0_1725346694631.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanish_finnish_all_en_5.5.0_3.0_1725346694631.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("spanish_finnish_all","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("spanish_finnish_all","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spanish_finnish_all| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|530.5 MB| + +## References + +https://huggingface.co/americasnlp-lct-ehu/es_fi_all \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-spanish_finnish_all_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-spanish_finnish_all_pipeline_en.md new file mode 100644 index 00000000000000..31043d66db1297 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-spanish_finnish_all_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English spanish_finnish_all_pipeline pipeline MarianTransformer from americasnlp-lct-ehu +author: John Snow Labs +name: spanish_finnish_all_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanish_finnish_all_pipeline` is a English model originally trained by americasnlp-lct-ehu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanish_finnish_all_pipeline_en_5.5.0_3.0_1725346721039.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanish_finnish_all_pipeline_en_5.5.0_3.0_1725346721039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("spanish_finnish_all_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("spanish_finnish_all_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spanish_finnish_all_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|531.1 MB| + +## References + +https://huggingface.co/americasnlp-lct-ehu/es_fi_all + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-sql_injection_attack_detection_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-03-sql_injection_attack_detection_distilbert_en.md new file mode 100644 index 00000000000000..95be317087bf16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-sql_injection_attack_detection_distilbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sql_injection_attack_detection_distilbert DistilBertForSequenceClassification from cybersectony +author: John Snow Labs +name: sql_injection_attack_detection_distilbert +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sql_injection_attack_detection_distilbert` is a English model originally trained by cybersectony. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sql_injection_attack_detection_distilbert_en_5.5.0_3.0_1725329782659.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sql_injection_attack_detection_distilbert_en_5.5.0_3.0_1725329782659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("sql_injection_attack_detection_distilbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sql_injection_attack_detection_distilbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sql_injection_attack_detection_distilbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/cybersectony/sql-injection-attack-detection-distilbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-swahili_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-swahili_english_en.md new file mode 100644 index 00000000000000..f8abd17b223f88 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-swahili_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English swahili_english MarianTransformer from Rogendo +author: John Snow Labs +name: swahili_english +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swahili_english` is a English model originally trained by Rogendo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swahili_english_en_5.5.0_3.0_1725347039532.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swahili_english_en_5.5.0_3.0_1725347039532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("swahili_english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("swahili_english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|swahili_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|504.8 MB| + +## References + +https://huggingface.co/Rogendo/sw-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-terjman_large_v2_ar.md b/docs/_posts/ahmedlone127/2024-09-03-terjman_large_v2_ar.md new file mode 100644 index 00000000000000..c74b05783ca305 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-terjman_large_v2_ar.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Arabic terjman_large_v2 MarianTransformer from atlasia +author: John Snow Labs +name: terjman_large_v2 +date: 2024-09-03 +tags: [ar, open_source, onnx, translation, marian] +task: Translation +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`terjman_large_v2` is a Arabic model originally trained by atlasia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/terjman_large_v2_ar_5.5.0_3.0_1725346143946.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/terjman_large_v2_ar_5.5.0_3.0_1725346143946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("terjman_large_v2","ar") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("terjman_large_v2","ar") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|terjman_large_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|ar| +|Size:|691.4 MB| + +## References + +https://huggingface.co/atlasia/Terjman-Large-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-terjman_nano_ar.md b/docs/_posts/ahmedlone127/2024-09-03-terjman_nano_ar.md new file mode 100644 index 00000000000000..9ea8e31e5c3bc6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-terjman_nano_ar.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Arabic terjman_nano MarianTransformer from atlasia +author: John Snow Labs +name: terjman_nano +date: 2024-09-03 +tags: [ar, open_source, onnx, translation, marian] +task: Translation +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`terjman_nano` is a Arabic model originally trained by atlasia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/terjman_nano_ar_5.5.0_3.0_1725346590005.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/terjman_nano_ar_5.5.0_3.0_1725346590005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("terjman_nano","ar") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("terjman_nano","ar") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|terjman_nano| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|ar| +|Size:|265.2 MB| + +## References + +https://huggingface.co/atlasia/Terjman-Nano \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-terjman_nano_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-03-terjman_nano_pipeline_ar.md new file mode 100644 index 00000000000000..1d029fb82bdc68 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-terjman_nano_pipeline_ar.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Arabic terjman_nano_pipeline pipeline MarianTransformer from atlasia +author: John Snow Labs +name: terjman_nano_pipeline +date: 2024-09-03 +tags: [ar, open_source, pipeline, onnx] +task: Translation +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`terjman_nano_pipeline` is a Arabic model originally trained by atlasia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/terjman_nano_pipeline_ar_5.5.0_3.0_1725346679975.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/terjman_nano_pipeline_ar_5.5.0_3.0_1725346679975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("terjman_nano_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("terjman_nano_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|terjman_nano_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|265.7 MB| + +## References + +https://huggingface.co/atlasia/Terjman-Nano + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_pipeline_en.md new file mode 100644 index 00000000000000..5cbeea22925c4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_pipeline pipeline XlmRoBertaForTokenClassification from anonymoussubmissions +author: John Snow Labs +name: tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_pipeline` is a English model originally trained by anonymoussubmissions. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_pipeline_en_5.5.0_3.0_1725323245516.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_pipeline_en_5.5.0_3.0_1725323245516.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|859.3 MB| + +## References + +https://huggingface.co/anonymoussubmissions/tner-xlm-roberta-base-ontonotes5-switchboard-non-normalized-and-normalized + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-tools_a6000_0_00003_en.md b/docs/_posts/ahmedlone127/2024-09-03-tools_a6000_0_00003_en.md new file mode 100644 index 00000000000000..ba769ce863fd49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-tools_a6000_0_00003_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tools_a6000_0_00003 RoBertaForSequenceClassification from rose-e-wang +author: John Snow Labs +name: tools_a6000_0_00003 +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tools_a6000_0_00003` is a English model originally trained by rose-e-wang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tools_a6000_0_00003_en_5.5.0_3.0_1725337721188.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tools_a6000_0_00003_en_5.5.0_3.0_1725337721188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("tools_a6000_0_00003","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("tools_a6000_0_00003", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tools_a6000_0_00003| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/rose-e-wang/tools_a6000_0.00003 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-tools_a6000_0_00003_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-tools_a6000_0_00003_pipeline_en.md new file mode 100644 index 00000000000000..0321e2feaa6b7f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-tools_a6000_0_00003_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tools_a6000_0_00003_pipeline pipeline RoBertaForSequenceClassification from rose-e-wang +author: John Snow Labs +name: tools_a6000_0_00003_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tools_a6000_0_00003_pipeline` is a English model originally trained by rose-e-wang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tools_a6000_0_00003_pipeline_en_5.5.0_3.0_1725337795484.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tools_a6000_0_00003_pipeline_en_5.5.0_3.0_1725337795484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tools_a6000_0_00003_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tools_a6000_0_00003_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tools_a6000_0_00003_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/rose-e-wang/tools_a6000_0.00003 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-tosrobertav2_en.md b/docs/_posts/ahmedlone127/2024-09-03-tosrobertav2_en.md new file mode 100644 index 00000000000000..420c4b3562ae39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-tosrobertav2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tosrobertav2 RoBertaForSequenceClassification from CodeHima +author: John Snow Labs +name: tosrobertav2 +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tosrobertav2` is a English model originally trained by CodeHima. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tosrobertav2_en_5.5.0_3.0_1725336667858.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tosrobertav2_en_5.5.0_3.0_1725336667858.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("tosrobertav2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("tosrobertav2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tosrobertav2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/CodeHima/TOSRobertaV2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-transmodel_arabic_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-transmodel_arabic_english_en.md new file mode 100644 index 00000000000000..7da504b2d0c365 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-transmodel_arabic_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English transmodel_arabic_english MarianTransformer from sofianch +author: John Snow Labs +name: transmodel_arabic_english +date: 2024-09-03 +tags: [en, open_source, onnx, translation, marian] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MarianTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`transmodel_arabic_english` is a English model originally trained by sofianch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/transmodel_arabic_english_en_5.5.0_3.0_1725346915342.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/transmodel_arabic_english_en_5.5.0_3.0_1725346915342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("translation") + +marian = MarianTransformer.pretrained("transmodel_arabic_english","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = MarianTransformer.pretrained("transmodel_arabic_english","en") + .setInputCols(Array("sentence")) + .setOutputCol("translation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|transmodel_arabic_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentences]| +|Output Labels:|[translation]| +|Language:|en| +|Size:|527.9 MB| + +## References + +https://huggingface.co/sofianch/TransModel_ar_en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-triplets_e5_base_500_2183ce_3be9a5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-triplets_e5_base_500_2183ce_3be9a5_pipeline_en.md new file mode 100644 index 00000000000000..95fcbf36023f25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-triplets_e5_base_500_2183ce_3be9a5_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English triplets_e5_base_500_2183ce_3be9a5_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: triplets_e5_base_500_2183ce_3be9a5_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`triplets_e5_base_500_2183ce_3be9a5_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/triplets_e5_base_500_2183ce_3be9a5_pipeline_en_5.5.0_3.0_1725332306217.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/triplets_e5_base_500_2183ce_3be9a5_pipeline_en_5.5.0_3.0_1725332306217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("triplets_e5_base_500_2183ce_3be9a5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("triplets_e5_base_500_2183ce_3be9a5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|triplets_e5_base_500_2183ce_3be9a5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|386.6 MB| + +## References + +https://huggingface.co/rithwik-db/triplets-e5-base-500-2183ce-3be9a5 + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-triplets_e5_base_500_484c6c_en.md b/docs/_posts/ahmedlone127/2024-09-03-triplets_e5_base_500_484c6c_en.md new file mode 100644 index 00000000000000..a958f55a754895 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-triplets_e5_base_500_484c6c_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English triplets_e5_base_500_484c6c E5Embeddings from rithwik-db +author: John Snow Labs +name: triplets_e5_base_500_484c6c +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`triplets_e5_base_500_484c6c` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/triplets_e5_base_500_484c6c_en_5.5.0_3.0_1725332130826.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/triplets_e5_base_500_484c6c_en_5.5.0_3.0_1725332130826.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("triplets_e5_base_500_484c6c","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("triplets_e5_base_500_484c6c","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|triplets_e5_base_500_484c6c| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|378.2 MB| + +## References + +https://huggingface.co/rithwik-db/triplets-e5-base-500-484c6c \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-triplets_e5_base_500_484c6c_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-triplets_e5_base_500_484c6c_pipeline_en.md new file mode 100644 index 00000000000000..3181ab0f4b3997 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-triplets_e5_base_500_484c6c_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English triplets_e5_base_500_484c6c_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: triplets_e5_base_500_484c6c_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`triplets_e5_base_500_484c6c_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/triplets_e5_base_500_484c6c_pipeline_en_5.5.0_3.0_1725332162829.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/triplets_e5_base_500_484c6c_pipeline_en_5.5.0_3.0_1725332162829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("triplets_e5_base_500_484c6c_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("triplets_e5_base_500_484c6c_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|triplets_e5_base_500_484c6c_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|378.2 MB| + +## References + +https://huggingface.co/rithwik-db/triplets-e5-base-500-484c6c + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-tst_tfm_stm_pp_th.md b/docs/_posts/ahmedlone127/2024-09-03-tst_tfm_stm_pp_th.md new file mode 100644 index 00000000000000..0bea8db85db754 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-tst_tfm_stm_pp_th.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Thai tst_tfm_stm_pp CamemBertForSequenceClassification from Ppxndpxdd +author: John Snow Labs +name: tst_tfm_stm_pp +date: 2024-09-03 +tags: [th, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: th +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tst_tfm_stm_pp` is a Thai model originally trained by Ppxndpxdd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tst_tfm_stm_pp_th_5.5.0_3.0_1725325267147.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tst_tfm_stm_pp_th_5.5.0_3.0_1725325267147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("tst_tfm_stm_pp","th") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("tst_tfm_stm_pp", "th") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tst_tfm_stm_pp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|th| +|Size:|394.3 MB| + +## References + +https://huggingface.co/Ppxndpxdd/tst_tfm_stm_pp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-turkish_tonga_tonga_islands_english_finetuned_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-turkish_tonga_tonga_islands_english_finetuned_model_pipeline_en.md new file mode 100644 index 00000000000000..7ef3662f6a61cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-turkish_tonga_tonga_islands_english_finetuned_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English turkish_tonga_tonga_islands_english_finetuned_model_pipeline pipeline MarianTransformer from ckartal +author: John Snow Labs +name: turkish_tonga_tonga_islands_english_finetuned_model_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_tonga_tonga_islands_english_finetuned_model_pipeline` is a English model originally trained by ckartal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_tonga_tonga_islands_english_finetuned_model_pipeline_en_5.5.0_3.0_1725346880724.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_tonga_tonga_islands_english_finetuned_model_pipeline_en_5.5.0_3.0_1725346880724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("turkish_tonga_tonga_islands_english_finetuned_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("turkish_tonga_tonga_islands_english_finetuned_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkish_tonga_tonga_islands_english_finetuned_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|525.8 MB| + +## References + +https://huggingface.co/ckartal/turkish-to-english-finetuned-model + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-varta_bert_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-varta_bert_pipeline_xx.md new file mode 100644 index 00000000000000..f3f292e423ab4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-varta_bert_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual varta_bert_pipeline pipeline BertEmbeddings from rahular +author: John Snow Labs +name: varta_bert_pipeline +date: 2024-09-03 +tags: [xx, open_source, pipeline, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`varta_bert_pipeline` is a Multilingual model originally trained by rahular. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/varta_bert_pipeline_xx_5.5.0_3.0_1725323859896.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/varta_bert_pipeline_xx_5.5.0_3.0_1725323859896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("varta_bert_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("varta_bert_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|varta_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|691.1 MB| + +## References + +https://huggingface.co/rahular/varta-bert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-vietnamese_deberta_small_en.md b/docs/_posts/ahmedlone127/2024-09-03-vietnamese_deberta_small_en.md new file mode 100644 index 00000000000000..171128489a9829 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-vietnamese_deberta_small_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English vietnamese_deberta_small DeBertaEmbeddings from binhquoc +author: John Snow Labs +name: vietnamese_deberta_small +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, deberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vietnamese_deberta_small` is a English model originally trained by binhquoc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vietnamese_deberta_small_en_5.5.0_3.0_1725331631913.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vietnamese_deberta_small_en_5.5.0_3.0_1725331631913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = DeBertaEmbeddings.pretrained("vietnamese_deberta_small","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DeBertaEmbeddings.pretrained("vietnamese_deberta_small","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vietnamese_deberta_small| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[deberta]| +|Language:|en| +|Size:|277.4 MB| + +## References + +https://huggingface.co/binhquoc/vie-deberta-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-vietnamese_deberta_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-vietnamese_deberta_small_pipeline_en.md new file mode 100644 index 00000000000000..49d3cf694fe5dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-vietnamese_deberta_small_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English vietnamese_deberta_small_pipeline pipeline DeBertaEmbeddings from binhquoc +author: John Snow Labs +name: vietnamese_deberta_small_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vietnamese_deberta_small_pipeline` is a English model originally trained by binhquoc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vietnamese_deberta_small_pipeline_en_5.5.0_3.0_1725331645094.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vietnamese_deberta_small_pipeline_en_5.5.0_3.0_1725331645094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("vietnamese_deberta_small_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("vietnamese_deberta_small_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vietnamese_deberta_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|277.4 MB| + +## References + +https://huggingface.co/binhquoc/vie-deberta-small + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-vis_genome_fine_tuned_opus_maltese_english_hausa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-vis_genome_fine_tuned_opus_maltese_english_hausa_pipeline_en.md new file mode 100644 index 00000000000000..93156a3926088a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-vis_genome_fine_tuned_opus_maltese_english_hausa_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English vis_genome_fine_tuned_opus_maltese_english_hausa_pipeline pipeline MarianTransformer from lukmanaj +author: John Snow Labs +name: vis_genome_fine_tuned_opus_maltese_english_hausa_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Translation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vis_genome_fine_tuned_opus_maltese_english_hausa_pipeline` is a English model originally trained by lukmanaj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vis_genome_fine_tuned_opus_maltese_english_hausa_pipeline_en_5.5.0_3.0_1725346911296.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vis_genome_fine_tuned_opus_maltese_english_hausa_pipeline_en_5.5.0_3.0_1725346911296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("vis_genome_fine_tuned_opus_maltese_english_hausa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("vis_genome_fine_tuned_opus_maltese_english_hausa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vis_genome_fine_tuned_opus_maltese_english_hausa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|497.7 MB| + +## References + +https://huggingface.co/lukmanaj/vis-genome-fine-tuned-opus-mt-en-ha + +## Included Models + +- DocumentAssembler +- SentenceDetectorDLModel +- MarianTransformer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-wangchanberta_base_att_spm_uncased_finetuned_thainewspbs_th.md b/docs/_posts/ahmedlone127/2024-09-03-wangchanberta_base_att_spm_uncased_finetuned_thainewspbs_th.md new file mode 100644 index 00000000000000..88e8226c049216 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-wangchanberta_base_att_spm_uncased_finetuned_thainewspbs_th.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Thai wangchanberta_base_att_spm_uncased_finetuned_thainewspbs CamemBertForSequenceClassification from SiraH +author: John Snow Labs +name: wangchanberta_base_att_spm_uncased_finetuned_thainewspbs +date: 2024-09-03 +tags: [th, open_source, onnx, sequence_classification, camembert] +task: Text Classification +language: th +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wangchanberta_base_att_spm_uncased_finetuned_thainewspbs` is a Thai model originally trained by SiraH. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wangchanberta_base_att_spm_uncased_finetuned_thainewspbs_th_5.5.0_3.0_1725325627440.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wangchanberta_base_att_spm_uncased_finetuned_thainewspbs_th_5.5.0_3.0_1725325627440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("wangchanberta_base_att_spm_uncased_finetuned_thainewspbs","th") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = CamemBertForSequenceClassification.pretrained("wangchanberta_base_att_spm_uncased_finetuned_thainewspbs", "th") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wangchanberta_base_att_spm_uncased_finetuned_thainewspbs| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|th| +|Size:|394.3 MB| + +## References + +https://huggingface.co/SiraH/wangchanberta-base-att-spm-uncased-finetuned-ThainewsPBS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-wikipedia_categories_setfit_en.md b/docs/_posts/ahmedlone127/2024-09-03-wikipedia_categories_setfit_en.md new file mode 100644 index 00000000000000..9776764f705ec4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-wikipedia_categories_setfit_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English wikipedia_categories_setfit E5Embeddings from KnutJaegersberg +author: John Snow Labs +name: wikipedia_categories_setfit +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wikipedia_categories_setfit` is a English model originally trained by KnutJaegersberg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wikipedia_categories_setfit_en_5.5.0_3.0_1725344370157.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wikipedia_categories_setfit_en_5.5.0_3.0_1725344370157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("wikipedia_categories_setfit","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("wikipedia_categories_setfit","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wikipedia_categories_setfit| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/KnutJaegersberg/wikipedia_categories_setfit \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-wikipedia_categories_setfit_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-wikipedia_categories_setfit_pipeline_en.md new file mode 100644 index 00000000000000..f901481ddcd01c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-wikipedia_categories_setfit_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English wikipedia_categories_setfit_pipeline pipeline E5Embeddings from KnutJaegersberg +author: John Snow Labs +name: wikipedia_categories_setfit_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wikipedia_categories_setfit_pipeline` is a English model originally trained by KnutJaegersberg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wikipedia_categories_setfit_pipeline_en_5.5.0_3.0_1725344432897.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wikipedia_categories_setfit_pipeline_en_5.5.0_3.0_1725344432897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("wikipedia_categories_setfit_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("wikipedia_categories_setfit_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wikipedia_categories_setfit_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/KnutJaegersberg/wikipedia_categories_setfit + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-with_e5_small_v2_en.md b/docs/_posts/ahmedlone127/2024-09-03-with_e5_small_v2_en.md new file mode 100644 index 00000000000000..51ef8dcf1c06ee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-with_e5_small_v2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English with_e5_small_v2 E5Embeddings from with-madrid +author: John Snow Labs +name: with_e5_small_v2 +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`with_e5_small_v2` is a English model originally trained by with-madrid. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/with_e5_small_v2_en_5.5.0_3.0_1725340203824.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/with_e5_small_v2_en_5.5.0_3.0_1725340203824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +embeddings = E5Embeddings.pretrained("with_e5_small_v2","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("with_e5_small_v2","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|with_e5_small_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|113.6 MB| + +## References + +https://huggingface.co/with-madrid/with-e5-small-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-with_e5_small_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-with_e5_small_v2_pipeline_en.md new file mode 100644 index 00000000000000..a80b49a88f1b9c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-with_e5_small_v2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English with_e5_small_v2_pipeline pipeline E5Embeddings from with-madrid +author: John Snow Labs +name: with_e5_small_v2_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`with_e5_small_v2_pipeline` is a English model originally trained by with-madrid. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/with_e5_small_v2_pipeline_en_5.5.0_3.0_1725340212491.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/with_e5_small_v2_pipeline_en_5.5.0_3.0_1725340212491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("with_e5_small_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("with_e5_small_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|with_e5_small_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|113.6 MB| + +## References + +https://huggingface.co/with-madrid/with-e5-small-v2 + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-withinapps_ndd_petclinic_test_tags_cwadj_en.md b/docs/_posts/ahmedlone127/2024-09-03-withinapps_ndd_petclinic_test_tags_cwadj_en.md new file mode 100644 index 00000000000000..84987d47871cb0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-withinapps_ndd_petclinic_test_tags_cwadj_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English withinapps_ndd_petclinic_test_tags_cwadj DistilBertForSequenceClassification from lgk03 +author: John Snow Labs +name: withinapps_ndd_petclinic_test_tags_cwadj +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_petclinic_test_tags_cwadj` is a English model originally trained by lgk03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_petclinic_test_tags_cwadj_en_5.5.0_3.0_1725330246979.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_petclinic_test_tags_cwadj_en_5.5.0_3.0_1725330246979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("withinapps_ndd_petclinic_test_tags_cwadj","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("withinapps_ndd_petclinic_test_tags_cwadj", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|withinapps_ndd_petclinic_test_tags_cwadj| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/lgk03/WITHINAPPS_NDD-petclinic_test-tags-CWAdj \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-withinapps_ndd_petclinic_test_tags_cwadj_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-withinapps_ndd_petclinic_test_tags_cwadj_pipeline_en.md new file mode 100644 index 00000000000000..da7b3acedcfaf0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-withinapps_ndd_petclinic_test_tags_cwadj_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English withinapps_ndd_petclinic_test_tags_cwadj_pipeline pipeline DistilBertForSequenceClassification from lgk03 +author: John Snow Labs +name: withinapps_ndd_petclinic_test_tags_cwadj_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_petclinic_test_tags_cwadj_pipeline` is a English model originally trained by lgk03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_petclinic_test_tags_cwadj_pipeline_en_5.5.0_3.0_1725330258920.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_petclinic_test_tags_cwadj_pipeline_en_5.5.0_3.0_1725330258920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("withinapps_ndd_petclinic_test_tags_cwadj_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("withinapps_ndd_petclinic_test_tags_cwadj_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|withinapps_ndd_petclinic_test_tags_cwadj_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/lgk03/WITHINAPPS_NDD-petclinic_test-tags-CWAdj + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_r_galen_meddocan_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_r_galen_meddocan_pipeline_es.md new file mode 100644 index 00000000000000..acb433ade72981 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_r_galen_meddocan_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish xlm_r_galen_meddocan_pipeline pipeline XlmRoBertaForTokenClassification from IIC +author: John Snow Labs +name: xlm_r_galen_meddocan_pipeline +date: 2024-09-03 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_galen_meddocan_pipeline` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_galen_meddocan_pipeline_es_5.5.0_3.0_1725348595291.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_galen_meddocan_pipeline_es_5.5.0_3.0_1725348595291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_r_galen_meddocan_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_r_galen_meddocan_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_r_galen_meddocan_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|1.0 GB| + +## References + +https://huggingface.co/IIC/XLM_R_Galen-meddocan + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_arabic_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_arabic_en.md new file mode 100644 index 00000000000000..dc1a7fc8acf7c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_arabic_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_arabic XlmRoBertaEmbeddings from Davlan +author: John Snow Labs +name: xlm_roberta_base_finetuned_arabic +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_arabic` is a English model originally trained by Davlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_arabic_en_5.5.0_3.0_1725343187972.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_arabic_en_5.5.0_3.0_1725343187972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_arabic","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_arabic","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_arabic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/Davlan/xlm-roberta-base-finetuned-arabic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_arabic_pipeline_en.md new file mode 100644 index 00000000000000..13a09a02d9d55c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_arabic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_arabic_pipeline pipeline XlmRoBertaEmbeddings from Davlan +author: John Snow Labs +name: xlm_roberta_base_finetuned_arabic_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_arabic_pipeline` is a English model originally trained by Davlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_arabic_pipeline_en_5.5.0_3.0_1725343238177.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_arabic_pipeline_en_5.5.0_3.0_1725343238177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_arabic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_arabic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_arabic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/Davlan/xlm-roberta-base-finetuned-arabic + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_hcy5561_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_hcy5561_pipeline_en.md new file mode 100644 index 00000000000000..d9c2d45c7d0780 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_hcy5561_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_french_hcy5561_pipeline pipeline XlmRoBertaForTokenClassification from hcy5561 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_french_hcy5561_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_hcy5561_pipeline` is a English model originally trained by hcy5561. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_hcy5561_pipeline_en_5.5.0_3.0_1725323505456.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_hcy5561_pipeline_en_5.5.0_3.0_1725323505456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_hcy5561_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_hcy5561_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_french_hcy5561_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|827.9 MB| + +## References + +https://huggingface.co/hcy5561/xlm-roberta-base-finetuned-panx-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_ttonio_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_ttonio_en.md new file mode 100644 index 00000000000000..73c739d8133bf0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_ttonio_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_french_ttonio XlmRoBertaForTokenClassification from Ttonio +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_french_ttonio +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_ttonio` is a English model originally trained by Ttonio. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ttonio_en_5.5.0_3.0_1725322596229.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ttonio_en_5.5.0_3.0_1725322596229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_ttonio","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_ttonio", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_french_ttonio| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|827.9 MB| + +## References + +https://huggingface.co/Ttonio/xlm-roberta-base-finetuned-panx-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_ttonio_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_ttonio_pipeline_en.md new file mode 100644 index 00000000000000..d21b9b3b2a7961 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_ttonio_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_french_ttonio_pipeline pipeline XlmRoBertaForTokenClassification from Ttonio +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_french_ttonio_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_ttonio_pipeline` is a English model originally trained by Ttonio. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ttonio_pipeline_en_5.5.0_3.0_1725322687965.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ttonio_pipeline_en_5.5.0_3.0_1725322687965.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_ttonio_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_ttonio_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_french_ttonio_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|827.9 MB| + +## References + +https://huggingface.co/Ttonio/xlm-roberta-base-finetuned-panx-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_urashima_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_urashima_en.md new file mode 100644 index 00000000000000..57b53c9c769e89 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_urashima_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_french_urashima XlmRoBertaForTokenClassification from Urashima +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_french_urashima +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_urashima` is a English model originally trained by Urashima. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_urashima_en_5.5.0_3.0_1725322305838.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_urashima_en_5.5.0_3.0_1725322305838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_urashima","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_urashima", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_french_urashima| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|827.9 MB| + +## References + +https://huggingface.co/Urashima/xlm-roberta-base-finetuned-panx-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_urashima_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_urashima_pipeline_en.md new file mode 100644 index 00000000000000..eceb7c6b79d139 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_urashima_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_french_urashima_pipeline pipeline XlmRoBertaForTokenClassification from Urashima +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_french_urashima_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_urashima_pipeline` is a English model originally trained by Urashima. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_urashima_pipeline_en_5.5.0_3.0_1725322396280.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_urashima_pipeline_en_5.5.0_3.0_1725322396280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_urashima_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_urashima_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_french_urashima_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|827.9 MB| + +## References + +https://huggingface.co/Urashima/xlm-roberta-base-finetuned-panx-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_ericpeter_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_ericpeter_en.md new file mode 100644 index 00000000000000..cd37f645d55a3f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_ericpeter_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_ericpeter XlmRoBertaForTokenClassification from EricPeter +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_ericpeter +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ericpeter` is a English model originally trained by EricPeter. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ericpeter_en_5.5.0_3.0_1725323018322.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ericpeter_en_5.5.0_3.0_1725323018322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ericpeter","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ericpeter", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_ericpeter| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/EricPeter/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_ericpeter_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_ericpeter_pipeline_en.md new file mode 100644 index 00000000000000..ff2e4ade1be42e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_ericpeter_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_ericpeter_pipeline pipeline XlmRoBertaForTokenClassification from EricPeter +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_ericpeter_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ericpeter_pipeline` is a English model originally trained by EricPeter. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ericpeter_pipeline_en_5.5.0_3.0_1725323093249.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ericpeter_pipeline_en_5.5.0_3.0_1725323093249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ericpeter_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ericpeter_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_ericpeter_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/EricPeter/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_eunkyung0505_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_eunkyung0505_en.md new file mode 100644 index 00000000000000..1855433e5190e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_eunkyung0505_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_eunkyung0505 XlmRoBertaForTokenClassification from eunkyung0505 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_eunkyung0505 +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_eunkyung0505` is a English model originally trained by eunkyung0505. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_eunkyung0505_en_5.5.0_3.0_1725322881987.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_eunkyung0505_en_5.5.0_3.0_1725322881987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_eunkyung0505","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_eunkyung0505", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_eunkyung0505| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|853.4 MB| + +## References + +https://huggingface.co/eunkyung0505/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_eunkyung0505_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_eunkyung0505_pipeline_en.md new file mode 100644 index 00000000000000..7514f69f218588 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_eunkyung0505_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_eunkyung0505_pipeline pipeline XlmRoBertaForTokenClassification from eunkyung0505 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_eunkyung0505_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_eunkyung0505_pipeline` is a English model originally trained by eunkyung0505. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_eunkyung0505_pipeline_en_5.5.0_3.0_1725322947634.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_eunkyung0505_pipeline_en_5.5.0_3.0_1725322947634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_eunkyung0505_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_eunkyung0505_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_eunkyung0505_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.4 MB| + +## References + +https://huggingface.co/eunkyung0505/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_ffalcao_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_ffalcao_pipeline_en.md new file mode 100644 index 00000000000000..cd4534d07c9bed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_ffalcao_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_ffalcao_pipeline pipeline XlmRoBertaForTokenClassification from ffalcao +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_ffalcao_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ffalcao_pipeline` is a English model originally trained by ffalcao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ffalcao_pipeline_en_5.5.0_3.0_1725349294721.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ffalcao_pipeline_en_5.5.0_3.0_1725349294721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ffalcao_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ffalcao_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_ffalcao_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/ffalcao/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_54data_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_54data_en.md new file mode 100644 index 00000000000000..8429aa04228daf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_54data_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_french_54data XlmRoBertaForTokenClassification from 54data +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_french_54data +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_54data` is a English model originally trained by 54data. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_54data_en_5.5.0_3.0_1725322452538.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_54data_en_5.5.0_3.0_1725322452538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_54data","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_54data", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_french_54data| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|858.2 MB| + +## References + +https://huggingface.co/54data/xlm-roberta-base-finetuned-panx-de-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_54data_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_54data_pipeline_en.md new file mode 100644 index 00000000000000..113c28162c84dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_54data_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_french_54data_pipeline pipeline XlmRoBertaForTokenClassification from 54data +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_french_54data_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_54data_pipeline` is a English model originally trained by 54data. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_54data_pipeline_en_5.5.0_3.0_1725322519151.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_54data_pipeline_en_5.5.0_3.0_1725322519151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_54data_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_54data_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_french_54data_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|858.2 MB| + +## References + +https://huggingface.co/54data/xlm-roberta-base-finetuned-panx-de-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_lijingxin_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_lijingxin_en.md new file mode 100644 index 00000000000000..de42e720ee0519 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_lijingxin_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_french_lijingxin XlmRoBertaForTokenClassification from lijingxin +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_french_lijingxin +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_lijingxin` is a English model originally trained by lijingxin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_lijingxin_en_5.5.0_3.0_1725322403277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_lijingxin_en_5.5.0_3.0_1725322403277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_lijingxin","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_lijingxin", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_french_lijingxin| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|858.2 MB| + +## References + +https://huggingface.co/lijingxin/xlm-roberta-base-finetuned-panx-de-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_nobody138_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_nobody138_en.md new file mode 100644 index 00000000000000..2158bc31ceb0d5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_nobody138_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_french_nobody138 XlmRoBertaForTokenClassification from Nobody138 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_french_nobody138 +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_nobody138` is a English model originally trained by Nobody138. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_nobody138_en_5.5.0_3.0_1725323321077.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_nobody138_en_5.5.0_3.0_1725323321077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_nobody138","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_nobody138", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_french_nobody138| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|858.2 MB| + +## References + +https://huggingface.co/Nobody138/xlm-roberta-base-finetuned-panx-de-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_philophilae_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_philophilae_pipeline_en.md new file mode 100644 index 00000000000000..454606bfe1e69d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_philophilae_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_french_philophilae_pipeline pipeline XlmRoBertaForTokenClassification from Philophilae +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_french_philophilae_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_philophilae_pipeline` is a English model originally trained by Philophilae. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_philophilae_pipeline_en_5.5.0_3.0_1725323619990.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_philophilae_pipeline_en_5.5.0_3.0_1725323619990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_philophilae_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_philophilae_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_french_philophilae_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|857.0 MB| + +## References + +https://huggingface.co/Philophilae/xlm-roberta-base-finetuned-panx-de-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_hoonface_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_hoonface_pipeline_en.md new file mode 100644 index 00000000000000..9ffb7245321e19 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_hoonface_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_hoonface_pipeline pipeline XlmRoBertaForTokenClassification from hoonface +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_hoonface_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_hoonface_pipeline` is a English model originally trained by hoonface. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hoonface_pipeline_en_5.5.0_3.0_1725323093891.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hoonface_pipeline_en_5.5.0_3.0_1725323093891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_hoonface_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_hoonface_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_hoonface_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/hoonface/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_jo_kwsm_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_jo_kwsm_en.md new file mode 100644 index 00000000000000..f74a3819bce1ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_jo_kwsm_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_jo_kwsm XlmRoBertaForTokenClassification from jo-kwsm +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_jo_kwsm +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_jo_kwsm` is a English model originally trained by jo-kwsm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_jo_kwsm_en_5.5.0_3.0_1725322160152.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_jo_kwsm_en_5.5.0_3.0_1725322160152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_jo_kwsm","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_jo_kwsm", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_jo_kwsm| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/jo-kwsm/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_jo_kwsm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_jo_kwsm_pipeline_en.md new file mode 100644 index 00000000000000..222d2f73e7b2b7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_jo_kwsm_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_jo_kwsm_pipeline pipeline XlmRoBertaForTokenClassification from jo-kwsm +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_jo_kwsm_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_jo_kwsm_pipeline` is a English model originally trained by jo-kwsm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_jo_kwsm_pipeline_en_5.5.0_3.0_1725322229460.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_jo_kwsm_pipeline_en_5.5.0_3.0_1725322229460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_jo_kwsm_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_jo_kwsm_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_jo_kwsm_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/jo-kwsm/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_juhyun76_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_juhyun76_en.md new file mode 100644 index 00000000000000..083873ce4ba9bc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_juhyun76_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_juhyun76 XlmRoBertaForTokenClassification from juhyun76 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_juhyun76 +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_juhyun76` is a English model originally trained by juhyun76. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_juhyun76_en_5.5.0_3.0_1725321696884.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_juhyun76_en_5.5.0_3.0_1725321696884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_juhyun76","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_juhyun76", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_juhyun76| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|841.2 MB| + +## References + +https://huggingface.co/juhyun76/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_en.md new file mode 100644 index 00000000000000..a22184d61347ef --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_mlvprasadofficial XlmRoBertaForTokenClassification from mlvprasadofficial +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_mlvprasadofficial +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_mlvprasadofficial` is a English model originally trained by mlvprasadofficial. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_en_5.5.0_3.0_1725322610781.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_en_5.5.0_3.0_1725322610781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_mlvprasadofficial","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_mlvprasadofficial", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_mlvprasadofficial| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|851.7 MB| + +## References + +https://huggingface.co/mlvprasadofficial/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_pipeline_en.md new file mode 100644 index 00000000000000..10a48784caf01c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_pipeline pipeline XlmRoBertaForTokenClassification from mlvprasadofficial +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_pipeline` is a English model originally trained by mlvprasadofficial. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_pipeline_en_5.5.0_3.0_1725322683537.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_pipeline_en_5.5.0_3.0_1725322683537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_mlvprasadofficial_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|851.8 MB| + +## References + +https://huggingface.co/mlvprasadofficial/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_natnova_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_natnova_en.md new file mode 100644 index 00000000000000..904b4512d4a251 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_natnova_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_natnova XlmRoBertaForTokenClassification from natnova +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_natnova +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_natnova` is a English model originally trained by natnova. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_natnova_en_5.5.0_3.0_1725321747430.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_natnova_en_5.5.0_3.0_1725321747430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_natnova","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_natnova", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_natnova| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/natnova/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_natnova_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_natnova_pipeline_en.md new file mode 100644 index 00000000000000..f65618fa21e9f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_natnova_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_natnova_pipeline pipeline XlmRoBertaForTokenClassification from natnova +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_natnova_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_natnova_pipeline` is a English model originally trained by natnova. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_natnova_pipeline_en_5.5.0_3.0_1725321817914.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_natnova_pipeline_en_5.5.0_3.0_1725321817914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_natnova_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_natnova_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_natnova_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/natnova/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_photonmz_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_photonmz_en.md new file mode 100644 index 00000000000000..98d44eb6aa9bc5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_photonmz_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_photonmz XlmRoBertaForTokenClassification from photonmz +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_photonmz +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_photonmz` is a English model originally trained by photonmz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_photonmz_en_5.5.0_3.0_1725323033147.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_photonmz_en_5.5.0_3.0_1725323033147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_photonmz","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_photonmz", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_photonmz| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/photonmz/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_tieincred_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_tieincred_pipeline_en.md new file mode 100644 index 00000000000000..50d6298bbda0bf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_tieincred_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_tieincred_pipeline pipeline XlmRoBertaForTokenClassification from TieIncred +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_tieincred_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_tieincred_pipeline` is a English model originally trained by TieIncred. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tieincred_pipeline_en_5.5.0_3.0_1725348465079.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tieincred_pipeline_en_5.5.0_3.0_1725348465079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_tieincred_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_tieincred_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_tieincred_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/TieIncred/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_param_mehta_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_param_mehta_en.md new file mode 100644 index 00000000000000..969b32985a0502 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_param_mehta_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_italian_param_mehta XlmRoBertaForTokenClassification from param-mehta +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_italian_param_mehta +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_param_mehta` is a English model originally trained by param-mehta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_param_mehta_en_5.5.0_3.0_1725321980238.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_param_mehta_en_5.5.0_3.0_1725321980238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_param_mehta","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_param_mehta", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_italian_param_mehta| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|820.7 MB| + +## References + +https://huggingface.co/param-mehta/xlm-roberta-base-finetuned-panx-it \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_saqidr_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_saqidr_en.md new file mode 100644 index 00000000000000..799d63c6f377e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_saqidr_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_italian_saqidr XlmRoBertaForTokenClassification from saqidr +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_italian_saqidr +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_saqidr` is a English model originally trained by saqidr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_saqidr_en_5.5.0_3.0_1725323173326.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_saqidr_en_5.5.0_3.0_1725323173326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_saqidr","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_saqidr", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_italian_saqidr| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|816.7 MB| + +## References + +https://huggingface.co/saqidr/xlm-roberta-base-finetuned-panx-it \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_pharmaconer_mmenendezg_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_pharmaconer_mmenendezg_en.md new file mode 100644 index 00000000000000..97cef894213cf0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_pharmaconer_mmenendezg_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_pharmaconer_mmenendezg RoBertaForTokenClassification from mmenendezg +author: John Snow Labs +name: xlm_roberta_base_pharmaconer_mmenendezg +date: 2024-09-03 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_pharmaconer_mmenendezg` is a English model originally trained by mmenendezg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_pharmaconer_mmenendezg_en_5.5.0_3.0_1725326272489.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_pharmaconer_mmenendezg_en_5.5.0_3.0_1725326272489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +tokenClassifier = RoBertaForTokenClassification.pretrained("xlm_roberta_base_pharmaconer_mmenendezg","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("xlm_roberta_base_pharmaconer_mmenendezg", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_pharmaconer_mmenendezg| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|837.9 MB| + +## References + +https://huggingface.co/mmenendezg/xlm-roberta-base-pharmaconer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_pharmaconer_mmenendezg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_pharmaconer_mmenendezg_pipeline_en.md new file mode 100644 index 00000000000000..50023189d6162a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_pharmaconer_mmenendezg_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_pharmaconer_mmenendezg_pipeline pipeline RoBertaForTokenClassification from mmenendezg +author: John Snow Labs +name: xlm_roberta_base_pharmaconer_mmenendezg_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_pharmaconer_mmenendezg_pipeline` is a English model originally trained by mmenendezg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_pharmaconer_mmenendezg_pipeline_en_5.5.0_3.0_1725326356527.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_pharmaconer_mmenendezg_pipeline_en_5.5.0_3.0_1725326356527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_pharmaconer_mmenendezg_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_pharmaconer_mmenendezg_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_pharmaconer_mmenendezg_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|837.9 MB| + +## References + +https://huggingface.co/mmenendezg/xlm-roberta-base-pharmaconer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_romanian_ner_ronec_pipeline_ro.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_romanian_ner_ronec_pipeline_ro.md new file mode 100644 index 00000000000000..26eb677c8cf7d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_romanian_ner_ronec_pipeline_ro.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Moldavian, Moldovan, Romanian xlm_roberta_base_romanian_ner_ronec_pipeline pipeline XlmRoBertaForTokenClassification from EvanD +author: John Snow Labs +name: xlm_roberta_base_romanian_ner_ronec_pipeline +date: 2024-09-03 +tags: [ro, open_source, pipeline, onnx] +task: Named Entity Recognition +language: ro +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_romanian_ner_ronec_pipeline` is a Moldavian, Moldovan, Romanian model originally trained by EvanD. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_romanian_ner_ronec_pipeline_ro_5.5.0_3.0_1725349161655.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_romanian_ner_ronec_pipeline_ro_5.5.0_3.0_1725349161655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_romanian_ner_ronec_pipeline", lang = "ro") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_romanian_ner_ronec_pipeline", lang = "ro") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_romanian_ner_ronec_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ro| +|Size:|800.3 MB| + +## References + +https://huggingface.co/EvanD/xlm-roberta-base-romanian-ner-ronec + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmr_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlmr_finetuned_en.md new file mode 100644 index 00000000000000..dc8c6c6f4428a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmr_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlmr_finetuned XlmRoBertaEmbeddings from kietnt0603 +author: John Snow Labs +name: xlmr_finetuned +date: 2024-09-03 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_finetuned` is a English model originally trained by kietnt0603. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_en_5.5.0_3.0_1725342964442.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_en_5.5.0_3.0_1725342964442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +embeddings = XlmRoBertaEmbeddings.pretrained("xlmr_finetuned","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("xlmr_finetuned","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmr_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/kietnt0603/xlmr-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmr_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlmr_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..34e9da11823fa8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmr_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlmr_finetuned_pipeline pipeline XlmRoBertaEmbeddings from kietnt0603 +author: John Snow Labs +name: xlmr_finetuned_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_finetuned_pipeline` is a English model originally trained by kietnt0603. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_pipeline_en_5.5.0_3.0_1725343022060.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_pipeline_en_5.5.0_3.0_1725343022060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmr_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmr_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmr_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/kietnt0603/xlmr-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmr_qa_extraction_finnish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlmr_qa_extraction_finnish_pipeline_en.md new file mode 100644 index 00000000000000..7d356f36088d3e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmr_qa_extraction_finnish_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlmr_qa_extraction_finnish_pipeline pipeline XlmRoBertaForTokenClassification from TurkuNLP +author: John Snow Labs +name: xlmr_qa_extraction_finnish_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_qa_extraction_finnish_pipeline` is a English model originally trained by TurkuNLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_qa_extraction_finnish_pipeline_en_5.5.0_3.0_1725322200321.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_qa_extraction_finnish_pipeline_en_5.5.0_3.0_1725322200321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmr_qa_extraction_finnish_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmr_qa_extraction_finnish_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmr_qa_extraction_finnish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|836.6 MB| + +## References + +https://huggingface.co/TurkuNLP/xlmr-qa-extraction-fi + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_verdict_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_verdict_pipeline_xx.md new file mode 100644 index 00000000000000..b272e048591a96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_verdict_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual xlmroberta_classifier_verdict_pipeline pipeline XlmRoBertaForSequenceClassification from saattrupdan +author: John Snow Labs +name: xlmroberta_classifier_verdict_pipeline +date: 2024-09-03 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_classifier_verdict_pipeline` is a Multilingual model originally trained by saattrupdan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_classifier_verdict_pipeline_xx_5.5.0_3.0_1725328845798.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_classifier_verdict_pipeline_xx_5.5.0_3.0_1725328845798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_classifier_verdict_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_classifier_verdict_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_classifier_verdict_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|982.1 MB| + +## References + +https://huggingface.co/saattrupdan/verdict-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_verdict_xx.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_verdict_xx.md new file mode 100644 index 00000000000000..1e236d640df02c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_verdict_xx.md @@ -0,0 +1,104 @@ +--- +layout: model +title: Multilingual XlmRobertaForSequenceClassification Cased model (from saattrupdan) +author: John Snow Labs +name: xlmroberta_classifier_verdict +date: 2024-09-03 +tags: [en, de, fr, es, ru, ar, pt, pl, it, nl, tr, zh, ca, fi, ro, da, el, ko, sv, cs, ja, th, hu, bg, et, sl, hi, vi, lv, lt, fa, hr, sk, ur, ta, bn, eu, uk, sr, is, te, ml, "no", ka, mr, tl, cy, si, hy, km, my, ne, kn, gu, bs, am, pa, ps, or, ug, lo, ht, sd, open_source, xlm_roberta, sequence_classification, classification, xx, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRobertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `verdict-classifier` is a Multilingual model originally trained by `saattrupdan`. + +## Predicted Entities + +`factual`, `misinformation`, `other` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_classifier_verdict_xx_5.5.0_3.0_1725328780396.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_classifier_verdict_xx_5.5.0_3.0_1725328780396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = XlmRoBertaForSequenceClassification.pretrained("xlmroberta_classifier_verdict","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = XlmRoBertaForSequenceClassification.pretrained("xlmroberta_classifier_verdict","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("xx.classify.xlmr_roberta").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_classifier_verdict| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|982.1 MB| + +## References + +References + +- https://huggingface.co/saattrupdan/verdict-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_flood_base_finetuned_panx_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_flood_base_finetuned_panx_pipeline_xx.md new file mode 100644 index 00000000000000..63b27fd3fa40ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_flood_base_finetuned_panx_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual xlmroberta_ner_flood_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from flood +author: John Snow Labs +name: xlmroberta_ner_flood_base_finetuned_panx_pipeline +date: 2024-09-03 +tags: [xx, open_source, pipeline, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_flood_base_finetuned_panx_pipeline` is a Multilingual model originally trained by flood. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_flood_base_finetuned_panx_pipeline_xx_5.5.0_3.0_1725348725750.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_flood_base_finetuned_panx_pipeline_xx_5.5.0_3.0_1725348725750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_flood_base_finetuned_panx_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_flood_base_finetuned_panx_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_flood_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|858.2 MB| + +## References + +https://huggingface.co/flood/xlm-roberta-base-finetuned-panx-de-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_flood_base_finetuned_panx_xx.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_flood_base_finetuned_panx_xx.md new file mode 100644 index 00000000000000..881d8d7d2fe55b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_flood_base_finetuned_panx_xx.md @@ -0,0 +1,112 @@ +--- +layout: model +title: Multilingual XLMRobertaForTokenClassification Base Cased model (from flood) +author: John Snow Labs +name: xlmroberta_ner_flood_base_finetuned_panx +date: 2024-09-03 +tags: [de, fr, open_source, xlm_roberta, ner, xx, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de-fr` is a Multilingual model originally trained by `flood`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_flood_base_finetuned_panx_xx_5.5.0_3.0_1725348660297.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_flood_base_finetuned_panx_xx_5.5.0_3.0_1725348660297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_flood_base_finetuned_panx","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_flood_base_finetuned_panx","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("xx.ner.xlmr_roberta.base_finetuned_panx.by_flood").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_flood_base_finetuned_panx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|xx| +|Size:|858.2 MB| + +## References + +References + +- https://huggingface.co/flood/xlm-roberta-base-finetuned-panx-de-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jboever_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jboever_base_finetuned_panx_de.md new file mode 100644 index 00000000000000..d38d42a9c50a1f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jboever_base_finetuned_panx_de.md @@ -0,0 +1,113 @@ +--- +layout: model +title: German XLMRobertaForTokenClassification Base Cased model (from jdeboever) +author: John Snow Labs +name: xlmroberta_ner_jboever_base_finetuned_panx +date: 2024-09-03 +tags: [de, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `jdeboever`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jboever_base_finetuned_panx_de_5.5.0_3.0_1725348345419.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jboever_base_finetuned_panx_de_5.5.0_3.0_1725348345419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_jboever_base_finetuned_panx","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_jboever_base_finetuned_panx","de") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_jdeboever").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_jboever_base_finetuned_panx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|853.8 MB| + +## References + +References + +- https://huggingface.co/jdeboever/xlm-roberta-base-finetuned-panx-de +- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jonfrank_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jonfrank_base_finetuned_panx_de.md new file mode 100644 index 00000000000000..404df9223836ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jonfrank_base_finetuned_panx_de.md @@ -0,0 +1,113 @@ +--- +layout: model +title: German XLMRobertaForTokenClassification Base Cased model (from jonfrank) +author: John Snow Labs +name: xlmroberta_ner_jonfrank_base_finetuned_panx +date: 2024-09-03 +tags: [de, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `jonfrank`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jonfrank_base_finetuned_panx_de_5.5.0_3.0_1725349440807.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jonfrank_base_finetuned_panx_de_5.5.0_3.0_1725349440807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_jonfrank_base_finetuned_panx","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_jonfrank_base_finetuned_panx","de") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_jonfrank").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_jonfrank_base_finetuned_panx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|853.8 MB| + +## References + +References + +- https://huggingface.co/jonfrank/xlm-roberta-base-finetuned-panx-de +- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jonfrank_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jonfrank_base_finetuned_panx_pipeline_de.md new file mode 100644 index 00000000000000..21b91aa51e78f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jonfrank_base_finetuned_panx_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German xlmroberta_ner_jonfrank_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from jonfrank +author: John Snow Labs +name: xlmroberta_ner_jonfrank_base_finetuned_panx_pipeline +date: 2024-09-03 +tags: [de, open_source, pipeline, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_jonfrank_base_finetuned_panx_pipeline` is a German model originally trained by jonfrank. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jonfrank_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725349507537.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jonfrank_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725349507537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_jonfrank_base_finetuned_panx_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_jonfrank_base_finetuned_panx_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_jonfrank_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|853.8 MB| + +## References + +https://huggingface.co/jonfrank/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_mertyrgn_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_mertyrgn_base_finetuned_panx_de.md new file mode 100644 index 00000000000000..452ddcaba097f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_mertyrgn_base_finetuned_panx_de.md @@ -0,0 +1,113 @@ +--- +layout: model +title: German XLMRobertaForTokenClassification Base Cased model (from mertyrgn) +author: John Snow Labs +name: xlmroberta_ner_mertyrgn_base_finetuned_panx +date: 2024-09-03 +tags: [de, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `mertyrgn`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_mertyrgn_base_finetuned_panx_de_5.5.0_3.0_1725347785722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_mertyrgn_base_finetuned_panx_de_5.5.0_3.0_1725347785722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_mertyrgn_base_finetuned_panx","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_mertyrgn_base_finetuned_panx","de") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_mertyrgn").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_mertyrgn_base_finetuned_panx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|853.8 MB| + +## References + +References + +- https://huggingface.co/mertyrgn/xlm-roberta-base-finetuned-panx-de +- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_naam_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_naam_base_finetuned_panx_pipeline_de.md new file mode 100644 index 00000000000000..88d14575225b5e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_naam_base_finetuned_panx_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German xlmroberta_ner_naam_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from naam +author: John Snow Labs +name: xlmroberta_ner_naam_base_finetuned_panx_pipeline +date: 2024-09-03 +tags: [de, open_source, pipeline, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_naam_base_finetuned_panx_pipeline` is a German model originally trained by naam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_naam_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725348752902.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_naam_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725348752902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_naam_base_finetuned_panx_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_naam_base_finetuned_panx_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_naam_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|853.8 MB| + +## References + +https://huggingface.co/naam/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_robkayinto_base_finetuned_panx_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_robkayinto_base_finetuned_panx_en.md new file mode 100644 index 00000000000000..c916033d5298b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_robkayinto_base_finetuned_panx_en.md @@ -0,0 +1,113 @@ +--- +layout: model +title: English XLMRobertaForTokenClassification Base Cased model (from robkayinto) +author: John Snow Labs +name: xlmroberta_ner_robkayinto_base_finetuned_panx +date: 2024-09-03 +tags: [en, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-en` is a English model originally trained by `robkayinto`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_robkayinto_base_finetuned_panx_en_5.5.0_3.0_1725348040476.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_robkayinto_base_finetuned_panx_en_5.5.0_3.0_1725348040476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_robkayinto_base_finetuned_panx","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_robkayinto_base_finetuned_panx","en") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.ner.xlmr_roberta.xtreme.base_finetuned.by_robkayinto").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_robkayinto_base_finetuned_panx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|826.4 MB| + +## References + +References + +- https://huggingface.co/robkayinto/xlm-roberta-base-finetuned-panx-en +- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_robkayinto_base_finetuned_panx_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_robkayinto_base_finetuned_panx_pipeline_en.md new file mode 100644 index 00000000000000..736671f789f65e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_robkayinto_base_finetuned_panx_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlmroberta_ner_robkayinto_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from robkayinto +author: John Snow Labs +name: xlmroberta_ner_robkayinto_base_finetuned_panx_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_robkayinto_base_finetuned_panx_pipeline` is a English model originally trained by robkayinto. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_robkayinto_base_finetuned_panx_pipeline_en_5.5.0_3.0_1725348136921.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_robkayinto_base_finetuned_panx_pipeline_en_5.5.0_3.0_1725348136921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_robkayinto_base_finetuned_panx_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_robkayinto_base_finetuned_panx_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_robkayinto_base_finetuned_panx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|826.4 MB| + +## References + +https://huggingface.co/robkayinto/xlm-roberta-base-finetuned-panx-en + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_victen_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_victen_base_finetuned_panx_de.md new file mode 100644 index 00000000000000..b65e584a791614 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_victen_base_finetuned_panx_de.md @@ -0,0 +1,113 @@ +--- +layout: model +title: German XLMRobertaForTokenClassification Base Cased model (from victen) +author: John Snow Labs +name: xlmroberta_ner_victen_base_finetuned_panx +date: 2024-09-03 +tags: [de, open_source, xlm_roberta, ner, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `victen`. + +## Predicted Entities + +`PER`, `LOC`, `ORG` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_victen_base_finetuned_panx_de_5.5.0_3.0_1725348005876.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_victen_base_finetuned_panx_de_5.5.0_3.0_1725348005876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_victen_base_finetuned_panx","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("ner") + +ner_converter = NerConverter()\ + .setInputCols(["document", "token", "ner"])\ + .setOutputCol("ner_chunk") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_victen_base_finetuned_panx","de") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val ner_converter = new NerConverter() + .setInputCols(Array("document", "token', "ner")) + .setOutputCol("ner_chunk") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_victen").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_victen_base_finetuned_panx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|853.8 MB| + +## References + +References + +- https://huggingface.co/victen/xlm-roberta-base-finetuned-panx-de +- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_am.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_am.md new file mode 100644 index 00000000000000..392c74ae356ab0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_am.md @@ -0,0 +1,110 @@ +--- +layout: model +title: Amharic Named Entity Recognition (from mbeukman) +author: John Snow Labs +name: xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic +date: 2024-09-03 +tags: [xlm_roberta, ner, token_classification, am, open_source, onnx] +task: Named Entity Recognition +language: am +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Named Entity Recognition model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-amharic-finetuned-ner-amharic` is a Amharic model orginally trained by `mbeukman`. + +## Predicted Entities + +`PER`, `ORG`, `LOC`, `DATE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_am_5.5.0_3.0_1725347711771.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_am_5.5.0_3.0_1725347711771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\ + .setInputCols(["document"])\ + .setOutputCol("sentence") + +tokenizer = Tokenizer() \ + .setInputCols("sentence") \ + .setOutputCol("token") + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic","am") \ + .setInputCols(["sentence", "token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier]) + +data = spark.createDataFrame([["ስካርቻ nlp እወዳለሁ"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val tokenizer = new Tokenizer() + .setInputCols(Array("sentence")) + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic","am") + .setInputCols(Array("sentence", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier)) + +val data = Seq("ስካርቻ nlp እወዳለሁ").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|am| +|Size:|1.0 GB| + +## References + +References + +- https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-amharic-finetuned-ner-amharic +- https://arxiv.org/abs/2103.11811 +- https://github.com/Michael-Beukman/NERTransfer +- https://www.apache.org/licenses/LICENSE-2.0 +- https://github.com/Michael-Beukm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_pipeline_am.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_pipeline_am.md new file mode 100644 index 00000000000000..7726f1bfdbc6f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_pipeline_am.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Amharic xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_pipeline pipeline XlmRoBertaForTokenClassification from mbeukman +author: John Snow Labs +name: xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_pipeline +date: 2024-09-03 +tags: [am, open_source, pipeline, onnx] +task: Named Entity Recognition +language: am +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_pipeline` is a Amharic model originally trained by mbeukman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_pipeline_am_5.5.0_3.0_1725347761303.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_pipeline_am_5.5.0_3.0_1725347761303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_pipeline", lang = "am") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_pipeline", lang = "am") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlmroberta_ner_xlm_roberta_base_finetuned_amharic_finetuned_ner_amharic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|am| +|Size:|1.0 GB| + +## References + +https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-amharic-finetuned-ner-amharic + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xml_roberta_climate_change_implicit_v01_en.md b/docs/_posts/ahmedlone127/2024-09-03-xml_roberta_climate_change_implicit_v01_en.md new file mode 100644 index 00000000000000..cbb8af1de2b2ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xml_roberta_climate_change_implicit_v01_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xml_roberta_climate_change_implicit_v01 XlmRoBertaForSequenceClassification from liserman +author: John Snow Labs +name: xml_roberta_climate_change_implicit_v01 +date: 2024-09-03 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xml_roberta_climate_change_implicit_v01` is a English model originally trained by liserman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xml_roberta_climate_change_implicit_v01_en_5.5.0_3.0_1725328139516.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xml_roberta_climate_change_implicit_v01_en_5.5.0_3.0_1725328139516.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = DocumentAssembler() \ + .setInputCol('text') \ + .setOutputCol('document') + +tokenizer = Tokenizer() \ + .setInputCols(['document']) \ + .setOutputCol('token') + +sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xml_roberta_climate_change_implicit_v01","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xml_roberta_climate_change_implicit_v01", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xml_roberta_climate_change_implicit_v01| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|846.7 MB| + +## References + +https://huggingface.co/liserman/xml-roberta-climate-change-implicit-v01 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-03-xml_roberta_climate_change_implicit_v01_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xml_roberta_climate_change_implicit_v01_pipeline_en.md new file mode 100644 index 00000000000000..0b0933781a46d5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-03-xml_roberta_climate_change_implicit_v01_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xml_roberta_climate_change_implicit_v01_pipeline pipeline XlmRoBertaForSequenceClassification from liserman +author: John Snow Labs +name: xml_roberta_climate_change_implicit_v01_pipeline +date: 2024-09-03 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xml_roberta_climate_change_implicit_v01_pipeline` is a English model originally trained by liserman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xml_roberta_climate_change_implicit_v01_pipeline_en_5.5.0_3.0_1725328216369.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xml_roberta_climate_change_implicit_v01_pipeline_en_5.5.0_3.0_1725328216369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xml_roberta_climate_change_implicit_v01_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xml_roberta_climate_change_implicit_v01_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xml_roberta_climate_change_implicit_v01_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|846.7 MB| + +## References + +https://huggingface.co/liserman/xml-roberta-climate-change-implicit-v01 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file